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  • 1.
    Abrahamsson, Annelie
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology.
    Rzepecka, Anna
    Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lundberg, Peter
    Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Dabrosin, Charlotta
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology.
    Dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment in vivo2016In: Oncoimmunology, ISSN 2162-4011, E-ISSN 2162-402X, Vol. 5, no 10, e1229723Article in journal (Refereed)
    Abstract [en]

    Inflammation is one of the hallmarks of carcinogenesis. High mammographic density has been associated with increased risk of breast cancer but the mechanisms behind are poorly understood. We evaluated whether breasts with different mammographic densities exhibited differences in the inflammatory microenvironment.Postmenopausal women attending the mammography-screening program were assessed having extreme dense, n = 20, or entirely fatty breasts (nondense), n = 19, on their regular mammograms. Thereafter, the women were invited for magnetic resonance imaging (MRI), microdialysis for the collection of extracellular molecules in situ and a core tissue biopsy for research purposes. On the MRI, lean tissue fraction (LTF) was calculated for a continuous measurement of breast density. LTF confirmed the selection from the mammograms and gave a continuous measurement of breast density. Microdialysis revealed significantly increased extracellular in vivo levels of IL-6, IL-8, vascular endothelial growth factor, and CCL5 in dense breast tissue as compared with nondense breasts. Moreover, the ratio IL-1Ra/IL-1 was decreased in dense breasts. No differences were found in levels of IL-1, IL-1Ra, CCL2, leptin, adiponectin, or leptin:adiponectin ratio between the two breast tissue types. Significant positive correlations between LTF and the pro-inflammatory cytokines as well as between the cytokines were detected. Stainings of the core biopsies exhibited increased levels of immune cells in dense breast tissue.Our data show that dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment and, if confirmed in a larger cohort, suggests novel targets for prevention therapies for women with dense breast tissue.

  • 2.
    Adelöf, Anna
    et al.
    Fackspråk och informatik, Regler och tillstånd, Socialstyrelsen.
    Lindberg, Christina
    Fackspråk och informatik, Regler och tillstånd, Socialstyrelsen.
    Barlow, Lotti
    Fackspråk och informatik, Regler och tillstånd, Socialstyrelsen.
    Gerdin, Ulla
    Fackspråk och informatik, Regler och tillstånd, Socialstyrelsen.
    Bränd Persson, Kristina
    Fackspråk och informatik, Regler och tillstånd, Socialstyrelsen.
    Ericsson, Erika
    Fackspråk och informatik, Regler och tillstånd, Socialstyrelsen.
    Testi, Stefano
    Fackspråk och informatik, Regler och tillstånd, Socialstyrelsen.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Förvaltning av SNOMED CT som en del i det nationella fackspråket för vård och omsorg2011Report (Other (popular science, discussion, etc.))
    Abstract [sv]

    Förvaltningsrapporten fokuserar på Snomed CT, eftersom det redan i dag finns rutiner för förvaltningar av termbanken och nationella hälsorelaterade klassifikationer. Ett särskilt utvecklingsarbete kommer att krävas för dessa delar.

    Rapporten tar upp syfte och mål med förvaltningen. Utöver det redogör rapporten för vilka konkreta ansvarsområden som ingår i förvaltningen av Snomed CT. Målet för förvaltningen är att Socialstyrelsen regelbundet ska kunna tillhandahålla en kontrollerad och uppdaterad release av Snomed CT. Det skulle möjliggöra användning inom vård och omsorg. Rapporten tar även upp behovet av kompetens, utbildning och finansiella resurser.

  • 3.
    Adolfsson, Karin
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Visual Evaluation of 3D Image Enhancement2006Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Technologies in image acquisition have developed and often provide image volumes in more than two dimensions. Computer tomography and magnet resonance imaging provide image volumes in three spatial dimensions. The image enhancement methods have developed as well and in this thesis work 3D image enhancement with filter networks is evaluated.

    The aims of this work are; to find a method which makes the initial parameter settings in the 3D image enhancement processing easier, to compare 2D and 3D processed image volumes visualized with different visualization techniques and to give an illustration of the benefits with 3D image enhancement processing visualized using these techniques.

    The results of this work are;

    1. a parameter setting tool that makes the initial parameter setting much easier and

    2. an evaluation of 3D image enhancement with filter networks that shows a significant enhanced image quality in 3D processed image volumes with a high noise level compared to the 2D processed volumes. These results are shown in slices, MIP and volume rendering. The differences are even more pronounced if the volume is presented in a different projection than the volume is 2D processed in.

  • 4.
    Agebratt, Christian
    et al.
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Ström, Edvin
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Romu, Thobias
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Dahlqvist Leinhard, Olof
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.
    Borga, Magnus
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Leandersson, Per
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Occupational and Environmental Medicine Center.
    Nyström, Fredrik H.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Endocrinology.
    A Randomized Study of the Effects of Additional Fruit and Nuts Consumption on Hepatic Fat Content, Cardiovascular Risk Factors and Basal Metabolic Rate2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 1, e0147149- p.Article in journal (Refereed)
    Abstract [en]

    Background

    Fruit has since long been advocated as a healthy source of many nutrients, however, the high content of sugars in fruit might be a concern.

    Objectives

    To study effects of an increased fruit intake compared with similar amount of extra calories from nuts in humans.

    Methods

    Thirty healthy non-obese participants were randomized to either supplement the diet with fruits or nuts, each at +7 kcal/kg bodyweight/day for two months. Major endpoints were change of hepatic fat content (HFC, by magnetic resonance imaging, MRI), basal metabolic rate (BMR, with indirect calorimetry) and cardiovascular risk markers.

    Results

    Weight gain was numerically similar in both groups although only statistically significant in the group randomized to nuts (fruit: from 22.15±1.61 kg/m2 to 22.30±1.7 kg/m2, p = 0.24 nuts: from 22.54±2.26 kg/m2 to 22.73±2.28 kg/m2, p = 0.045). On the other hand BMR increased in the nut group only (p = 0.028). Only the nut group reported a net increase of calories (from 2519±721 kcal/day to 2763±595 kcal/day, p = 0.035) according to 3-day food registrations. Despite an almost three-fold reported increased fructose-intake in the fruit group (from 9.1±6.0 gram/day to 25.6±9.6 gram/day, p<0.0001, nuts: from 12.4±5.7 gram/day to 6.5±5.3 gram/day, p = 0.007) there was no change of HFC. The numerical increase in fasting insulin was statistical significant only in the fruit group (from 7.73±3.1 pmol/l to 8.81±2.9 pmol/l, p = 0.018, nuts: from 7.29±2.9 pmol/l to 8.62±3.0 pmol/l, p = 0.14). Levels of vitamin C increased in both groups while α-tocopherol/cholesterol-ratio increased only in the fruit group.

    Conclusions

    Although BMR increased in the nut-group only this was not linked with differences in weight gain between groups which potentially could be explained by the lack of reported net caloric increase in the fruit group. In healthy non-obese individuals an increased fruit intake seems safe from cardiovascular risk perspective, including measurement of HFC by MRI.

  • 5.
    Ahlström, Christer
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
    Nonlinear phonocardiographic Signal Processing2008Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The aim of this thesis work has been to develop signal analysis methods for a computerized cardiac auscultation system, the intelligent stethoscope. In particular, the work focuses on classification and interpretation of features derived from the phonocardiographic (PCG) signal by using advanced signal processing techniques.

    The PCG signal is traditionally analyzed and characterized by morphological properties in the time domain, by spectral properties in the frequency domain or by nonstationary properties in a joint time-frequency domain. The main contribution of this thesis has been to introduce nonlinear analysis techniques based on dynamical systems theory to extract more information from the PCG signal. Especially, Takens' delay embedding theorem has been used to reconstruct the underlying system's state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction. In this thesis, the PCG signal's structure in state space has been exploited in several applications. Change detection based on recurrence time statistics was used in combination with nonlinear prediction to remove obscuring heart sounds from lung sound recordings in healthy test subjects. Sample entropy and mutual information were used to assess the severity of aortic stenosis (AS) as well as mitral insufficiency (MI) in dogs. A large number of, partly nonlinear, features was extracted and used for distinguishing innocent murmurs from murmurs caused by AS or MI in patients with probable valve disease. Finally, novel work related to very accurate localization of the first heart sound by means of ECG-gated ensemble averaging was conducted. In general, the presented nonlinear processing techniques have shown considerably improved results in comparison with other PCG based techniques.

    In modern health care, auscultation has found its main role in primary or in home health care, when deciding if special care and more extensive examinations are required. Making a decision based on auscultation is however difficult, why a simple tool able to screen and assess murmurs would be both time- and cost-saving while relieving many patients from needless anxiety. In the emerging field of telemedicine and home care, an intelligent stethoscope with decision support abilities would be of great value.

    List of papers
    1. A method for accurate localization of the first heart sound and possible applications
    Open this publication in new window or tab >>A method for accurate localization of the first heart sound and possible applications
    2008 (English)In: Physiological Measurement, ISSN 0967-3334, E-ISSN 1361-6579, Vol. 29, no 3, 417-428 p.Article in journal (Refereed) Published
    Abstract [en]

    We have previously developed a method for localization of the first heart sound (S1) using wavelet denoising and ECG-gated peak-picking. In this study, an additional enhancement step based on cross-correlation and ECG-gated ensemble averaging (EA) is presented. The main objective of the improved method was to localize S1 with very high temporal accuracy in (pseudo-) real time. The performance of S1 detection and localization, with and without EA enhancement, was evaluated on simulated as well as experimental data. The simulation study showed that EA enhancement reduced the localization error considerably and that S1 could be accurately localized at much lower signal-to-noise ratios. The experimental data were taken from ten healthy subjects at rest and during invoked hyper- and hypotension. For this material, the number of correct S1 detections increased from 91% to 98% when using EA enhancement. Improved performance was also demonstrated when EA enhancement was used for continuous tracking of blood pressure changes and for respiration monitoring via the electromechanical activation time. These are two typical applications where accurate localization of S1 is essential for the results.

    Place, publisher, year, edition, pages
    Institutionen för medicinsk teknik, 2008
    Keyword
    ensemble averaging, detection, localization, heart sound, bioacoustics
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-11856 (URN)10.1088/0967-3334/29/3/011 (DOI)
    Note
    Original publication: C Ahlstrom, T Länne, P Ask and A Johansson, A method for accurate localization of the first heart sound and possible applications, 2008, Physiological Measurement, (29), 3, 417-428. http://dx.doi.org/10.1088/0967-3334/29/3/011. Copyright: Institute of Physics and IOP Publishing Limited, http://www.iop.org/EJ/journal/PMAvailable from: 2008-05-20 Created: 2008-05-20 Last updated: 2017-12-13
    2. Assessing Aortic Stenosis using Sample Entropy of the Phonocardiographic Signal in Dogs
    Open this publication in new window or tab >>Assessing Aortic Stenosis using Sample Entropy of the Phonocardiographic Signal in Dogs
    Show others...
    2008 (English)In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 55, no 8, 2107-2109 p.Article in journal (Refereed) Published
    Abstract [en]

    In aortic valve stenosis (AS), heart murmurs arise as an effect of turbulent blood flow distal to the obstructed valves. With increasing AS severity, the flow becomes more unstable, and the ensuing murmur becomes more complex. We hypothesize that these hemodynamic flow changes can be quantified based on the complexity of the phonocardiographic (PCG) signal. In this study, sample entropy (SampEn) was investigated as a measure of complexity using a dog model. Twenty-seven boxer dogs with various degrees of AS were examined with Doppler echocardiography, and the peak aortic flow velocity (Vmax) was used as a reference of AS severity. SampEn correlated to Vmax with R = 0.70 using logarithmic regression. In a separate analysis, significant differences were found between physiologic murmurs and murmurs caused by AS (p < 0.05), and the area under a receiver operating characteristic curve was calculated to 0.96. Comparison with previously presented PCG measures for AS assessment showed improved performance when using SampEn, especially for differentiation between physiological murmurs and murmurs caused by mild AS. Studies in patients will be needed to properly assess the technique in humans.

    Keyword
    Aortic stenosis (AS), bioacoustics, heart sound, murmur, sample entropy (SampEn)
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-13042 (URN)10.1109/TBME.2008.923767 (DOI)
    Available from: 2008-03-20 Created: 2008-03-20 Last updated: 2017-12-13
    3. Assessing mitral regurgitation attributable to myxomatous mitral valve disease in dogs using signal analysis of heart sounds and murmurs
    Open this publication in new window or tab >>Assessing mitral regurgitation attributable to myxomatous mitral valve disease in dogs using signal analysis of heart sounds and murmurs
    Show others...
    2008 (English)Article in journal (Refereed) Submitted
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-13043 (URN)
    Available from: 2008-03-20 Created: 2008-03-20 Last updated: 2009-03-26
    4. Feature Extraction for Systolic Heart Murmur Classification
    Open this publication in new window or tab >>Feature Extraction for Systolic Heart Murmur Classification
    Show others...
    2006 (English)In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 34, no 11, 1666-1677 p.Article in journal (Refereed) Published
    Abstract [en]

    Heart murmurs are often the first signs of pathological changes of the heart valves, and they are usually found during auscultation in the primary health care. Distinguishing a pathological murmur from a physiological murmur is however difficult, why an “intelligent stethoscope” with decision support abilities would be of great value. Phonocardiographic signals were acquired from 36 patients with aortic valve stenosis, mitral insufficiency or physiological murmurs, and the data were analyzed with the aim to find a suitable feature subset for automatic classification of heart murmurs. Techniques such as Shannon energy, wavelets, fractal dimensions and recurrence quantification analysis were used to extract 207 features. 157 of these features have not previously been used in heart murmur classification. A multi-domain subset consisting of 14, both old and new, features was derived using Pudil’s sequential floating forward selection (SFFS) method. This subset was compared with several single domain feature sets. Using neural network classification, the selected multi-domain subset gave the best results; 86% correct classifications compared to 68% for the first runner-up. In conclusion, the derived feature set was superior to the comparative sets, and seems rather robust to noisy data.

    Keyword
    Auscultation, Bioacoustics, Feature selection, Heart sounds, Valvular disease
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-13044 (URN)10.1007/s10439-006-9187-4 (DOI)
    Available from: 2008-03-20 Created: 2008-03-20 Last updated: 2017-12-13
    5. Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction
    Open this publication in new window or tab >>Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction
    2005 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 12, no 12, 812-815 p.Article in journal (Refereed) Published
    Abstract [en]

    Heart sounds (HS) obscure the interpretation of lung sounds (LS). This letter presents a new method to detect and remove this undesired disturbance. The HS detection algorithm is based on a recurrence time statistic that is sensitive to changes in a reconstructed state space. Signal segments that are found to contain HS are removed, and the arising missing parts are replaced with predicted LS using a nonlinear prediction scheme. The prediction operates in the reconstructed state space and uses an iterated integrated nearest trajectory algorithm. The HS detection algorithm detects HS with an error rate of 4% false positives and 8% false negatives. The spectral difference between the reconstructed LS signal and an LS signal with removed HS was 0.34/spl plusmn/0.25, 0.50/spl plusmn/0.33, 0.46/spl plusmn/0.35, and 0.94/spl plusmn/0.64 dB/Hz in the frequency bands 20-40, 40-70, 70-150, and 150-300 Hz, respectively. The cross-correlation index was found to be 99.7%, indicating excellent similarity between actual LS and predicted LS. Listening tests performed by a skilled physician showed high-quality auditory results.

    Place, publisher, year, edition, pages
    Institutionen för medicinsk teknik, 2005
    Keyword
    Bioacoustics, heart sound (HS), lung sound (LS), nonlinear prediction, recurrence time statistics
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-11857 (URN)10.1109/LSP.2005.859528 (DOI)
    Note
    Original publication: Ahlstrom, C., Liljefeldt, O., Hult, P. and Ask, P., Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction, 2005, IEEE Signal Processing Letters, (12), 12, 812-815. http://dx.doi.org/10.1109/LSP.2005.859528. Copyright: IEEE, http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=97Available from: 2008-05-20 Created: 2008-05-20 Last updated: 2017-12-13
  • 6.
    Ahlström, Christer
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Processing of the Phonocardiographic Signal: methods for the intelligent stethoscope2006Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Phonocardiographic signals contain bioacoustic information reflecting the operation of the heart. Normally there are two heart sounds, and additional sounds indicate disease. If a third heart sound is present it could be a sign of heart failure whereas a murmur indicates defective valves or an orifice in the septal wall. The primary aim of this thesis is to use signal processing tools to improve the diagnostic value of this information. More specifically, three different methods have been developed:

    • A nonlinear change detection method has been applied to automatically detect heart sounds. The first and the second heart sounds can be found using recurrence times of the first kind while the third heart sound can be found using recurrence times of the second kind. Most third heart sound occurrences were detected (98 %), but the amount of false extra detections was rather high (7 % of the heart cycles).

    • Heart sounds obscure the interpretation of lung sounds. A new method based on nonlinear prediction has been developed to remove this undesired disturbance. High similarity was obtained when comparing actual lung sounds with lung sounds after removal of heart sounds.

    • Analysis methods such as Shannon energy, wavelets and recurrence quantification analysis were used to extract information from the phonocardiographic signal. The most prominent features, determined by a feature selection method, were used to create a new feature set for heart murmur classification. The classification result was 86 % when separating patients with aortic stenosis, mitral insufficiency and physiological murmurs.

    The derived methods give reasonable results, and they all provide a step forward in the quest for an intelligent stethoscope, a universal phonocardiography tool able to enhance auscultation by improving sound quality, emphasizing abnormal events in the heart cycle and distinguishing different heart murmurs.

    List of papers
    1. Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction
    Open this publication in new window or tab >>Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction
    2005 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 12, no 12, 812-815 p.Article in journal (Refereed) Published
    Abstract [en]

    Heart sounds (HS) obscure the interpretation of lung sounds (LS). This letter presents a new method to detect and remove this undesired disturbance. The HS detection algorithm is based on a recurrence time statistic that is sensitive to changes in a reconstructed state space. Signal segments that are found to contain HS are removed, and the arising missing parts are replaced with predicted LS using a nonlinear prediction scheme. The prediction operates in the reconstructed state space and uses an iterated integrated nearest trajectory algorithm. The HS detection algorithm detects HS with an error rate of 4% false positives and 8% false negatives. The spectral difference between the reconstructed LS signal and an LS signal with removed HS was 0.34/spl plusmn/0.25, 0.50/spl plusmn/0.33, 0.46/spl plusmn/0.35, and 0.94/spl plusmn/0.64 dB/Hz in the frequency bands 20-40, 40-70, 70-150, and 150-300 Hz, respectively. The cross-correlation index was found to be 99.7%, indicating excellent similarity between actual LS and predicted LS. Listening tests performed by a skilled physician showed high-quality auditory results.

    Place, publisher, year, edition, pages
    Institutionen för medicinsk teknik, 2005
    Keyword
    Bioacoustics, heart sound (HS), lung sound (LS), nonlinear prediction, recurrence time statistics
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-11857 (URN)10.1109/LSP.2005.859528 (DOI)
    Note
    Original publication: Ahlstrom, C., Liljefeldt, O., Hult, P. and Ask, P., Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction, 2005, IEEE Signal Processing Letters, (12), 12, 812-815. http://dx.doi.org/10.1109/LSP.2005.859528. Copyright: IEEE, http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=97Available from: 2008-05-20 Created: 2008-05-20 Last updated: 2017-12-13
    2. Detection of the 3rd Heart Sound using Recurrence Time Statistics
    Open this publication in new window or tab >>Detection of the 3rd Heart Sound using Recurrence Time Statistics
    2006 (English)In: Proc. 31st IEEE Int. Conf. on Acoustics, Speech and Signal Processing, Toulouse, France, 2006, 2006, 1040-1043 p.Conference paper, Published paper (Other academic)
    Abstract [en]

    The 3rd heart sound (S3) is normally heard during auscultation of younger individuals, but it is also common in many patients with heart failure. Compared to the 1st and 2nd heart sounds, S3 has low amplitude and low frequency content, making it hard to detect (both manually for the physician and automatically by a detection algorithm). We present an algorithm based on a recurrence time statistic which is sensitive to changes in a reconstructed state space, particularly for detection of transitions with very low energy. Heart sound signals from ten children were used in this study. Most S3 occurrences were detected (98 %), but the amount of false extra detections was rather high (7% of the heart cycles). In conclusion, the method seems capable of detecting S3 with high accuracy and robustness.

    Series
    IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings, ISSN 1520-6149
    Keyword
    acoustic, signal detection, bioacoustics, signal reconstruction, statistics, heart sound, auscultation, heart failure, reconstructed state space, recurrence time statistics
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-14058 (URN)
    Available from: 2006-10-09 Created: 2006-10-09 Last updated: 2009-04-21
    3. Feature Extraction for Systolic Heart Murmur Classification
    Open this publication in new window or tab >>Feature Extraction for Systolic Heart Murmur Classification
    Show others...
    2006 (English)In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 34, no 11, 1666-1677 p.Article in journal (Refereed) Published
    Abstract [en]

    Heart murmurs are often the first signs of pathological changes of the heart valves, and they are usually found during auscultation in the primary health care. Distinguishing a pathological murmur from a physiological murmur is however difficult, why an “intelligent stethoscope” with decision support abilities would be of great value. Phonocardiographic signals were acquired from 36 patients with aortic valve stenosis, mitral insufficiency or physiological murmurs, and the data were analyzed with the aim to find a suitable feature subset for automatic classification of heart murmurs. Techniques such as Shannon energy, wavelets, fractal dimensions and recurrence quantification analysis were used to extract 207 features. 157 of these features have not previously been used in heart murmur classification. A multi-domain subset consisting of 14, both old and new, features was derived using Pudil’s sequential floating forward selection (SFFS) method. This subset was compared with several single domain feature sets. Using neural network classification, the selected multi-domain subset gave the best results; 86% correct classifications compared to 68% for the first runner-up. In conclusion, the derived feature set was superior to the comparative sets, and seems rather robust to noisy data.

    Keyword
    Auscultation, Bioacoustics, Feature selection, Heart sounds, Valvular disease
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-13044 (URN)10.1007/s10439-006-9187-4 (DOI)
    Available from: 2008-03-20 Created: 2008-03-20 Last updated: 2017-12-13
  • 7.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Rask, Peter
    University Hospital, Örebro, Sweden .
    Karlsson, Jan-Erik
    County Hospital Ryhov, Jönköping, Sweden.
    Nylander, Eva
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Dahlström, Ulf
    Linköping University, Department of Medicine and Care, Cardiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Cardiology.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Assessment of Suspected Aortic Stenosis by Auto Mutual Information Analysis of Murmurs2007In: Engineering in Medicine and Biology Society, 2007. EMBS 2007, 2007, 1945-1948 p.Conference paper (Refereed)
    Abstract [en]

    Mild sclerotic thickening of the aortic valve affects 25% of the population, and the condition causes aortic valve stenosis (AS) in 2% of adults above 65 years. Echocardiography is today the clinical standard for assessing AS. However, a cost effective and uncomplicated technique that can be used for decision support in the primary health care would be of great value. In this study, recorded phonocardiographic signals were analyzed using the first local minimum of the auto mutual information (AMI) function. The AMI method measures the complexity in the sound signal, which is related to the amount of turbulence in the blood flow and thus to the severity of the stenosis. Two previously developed phonocardiographic methods for assessing AS severity were used for comparison, the murmur energy ratio and the sound spectral averaging technique. Twenty-nine patients with suspected AS were examined with Doppler echocardiography. The aortic jet velocity was used as a reference of AS severity, and it was found to correlate with the AMI method, the murmur energy ratio and the sound spectral averaging technique with the correlation coefficient R = 0.82, R = 0.73 and R = 0.76, respectively.

  • 8.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Arts and Sciences.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Detection of the 3(rd) heart sound using recurrence time statistics2006In: 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Vols 1-13, 2006, Vol. 1-13, 2288-2291 p.Conference paper (Refereed)
    Abstract [en]

    The 3(rd) heart sound (S3) is normally heard during auscultation of younger individuals, but it is also common in many patients with heart failure. Compared to the 1(st) and 2(nd) heart sounds, S3 has low amplitude and low frequency content, making it hard to detect (both manually for the physician and automatically by a detection algorithm). We present an algorithm based on a recurrence time statistic which is sensitive to changes in a reconstructed state space, particularly for detection of transitions with very low energy. Heart sound signals from ten children were used in this study. Most S3 occurrences were detected (98%), but the amount of false extra detections was rather high (7% of the heart cycles). In conclusion, the method seems capable of detecting S3 with high accuracy and robustness.

  • 9.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Detection of the 3rd Heart Sound using Recurrence Time Statistics2006In: Proc. 31st IEEE Int. Conf. on Acoustics, Speech and Signal Processing, Toulouse, France, 2006, 2006, 1040-1043 p.Conference paper (Other academic)
    Abstract [en]

    The 3rd heart sound (S3) is normally heard during auscultation of younger individuals, but it is also common in many patients with heart failure. Compared to the 1st and 2nd heart sounds, S3 has low amplitude and low frequency content, making it hard to detect (both manually for the physician and automatically by a detection algorithm). We present an algorithm based on a recurrence time statistic which is sensitive to changes in a reconstructed state space, particularly for detection of transitions with very low energy. Heart sound signals from ten children were used in this study. Most S3 occurrences were detected (98 %), but the amount of false extra detections was rather high (7% of the heart cycles). In conclusion, the method seems capable of detecting S3 with high accuracy and robustness.

  • 10.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Thresholding distance plots using true recurrence points2006In: Acoustics, Speech and Signal Processing, 2006. ICASSP 2006, IEEE , 2006, 688-691 p.Conference paper (Refereed)
    Abstract [en]

    Recurrence plots (RP) visualize multi-dimensional state spaces and represent the recurrence of states of a system. Recurrence points can be divided into true recurrence points and false recurrence points (also called sojourn points). We introduce the true recurrence point recurrence plot, TRP, a variant of the traditional RP excluding the sojourn points. This is a cleaned up RP free from recurrence points originating from tangential motion, and hence a more robust representation of unstable periodic orbits. The method is demonstrated with three simple systems, a periodic sine wave, a quasi-periodic torus and the x-component of the chaotic Lorenz system

  • 11.
    Ahlström, Christer
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Wheeze analysis and detection with non-linear phase-space embedding2005In: Nordic Baltic Conference Biomedical Engineering and Medical Physics,2005, Umeå: IFMBE , 2005, 305- p.Conference paper (Refereed)
  • 12.
    Ahlström, Christer
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Rask, P
    Karlsson, J-E
    Nylander, Eva
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Dahlström, Ulf
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Cardiology. Östergötlands Läns Landsting, Heart Centre, Department of Cardiology.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Using the intelligent stethoscope for extraction of features for systolic heart murmur classification2006In: World Congress on Medical Physics and Biomedical Engineering WC2006,2006, 2006Conference paper (Other academic)
  • 13.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Rask, Peter
    Örebro university.
    Karlsson, Jan-Erik
    Nylander, Eva
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Dahlström, Ulf
    Linköping University, Department of Medicine and Health Sciences, Cardiology . Linköping University, Faculty of Health Sciences.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Feature Extraction for Systolic Heart Murmur Classification2006In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 34, no 11, 1666-1677 p.Article in journal (Refereed)
    Abstract [en]

    Heart murmurs are often the first signs of pathological changes of the heart valves, and they are usually found during auscultation in the primary health care. Distinguishing a pathological murmur from a physiological murmur is however difficult, why an “intelligent stethoscope” with decision support abilities would be of great value. Phonocardiographic signals were acquired from 36 patients with aortic valve stenosis, mitral insufficiency or physiological murmurs, and the data were analyzed with the aim to find a suitable feature subset for automatic classification of heart murmurs. Techniques such as Shannon energy, wavelets, fractal dimensions and recurrence quantification analysis were used to extract 207 features. 157 of these features have not previously been used in heart murmur classification. A multi-domain subset consisting of 14, both old and new, features was derived using Pudil’s sequential floating forward selection (SFFS) method. This subset was compared with several single domain feature sets. Using neural network classification, the selected multi-domain subset gave the best results; 86% correct classifications compared to 68% for the first runner-up. In conclusion, the derived feature set was superior to the comparative sets, and seems rather robust to noisy data.

  • 14.
    Ahlström, Christer
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Schmekel, Birgitta
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Automatisk detektering av ronki med icke-linjära metoder2004In: Svenska Läkaresällskapets riksstämma,2004, 2004, 66-66 p.Conference paper (Other academic)
  • 15.
    Ahlström, Christer
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Schmekel, Birgitta
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Wheeze detection with nonlinear statespace embedding2004In: International Lung Sound Association,2004, 2004, 38-39 p.Conference paper (Other academic)
  • 16.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
    Höglund, Katja
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
    Häggström, Jens
    Kvart, Clarence
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
    Assessing Aortic Stenosis using Sample Entropy of the Phonocardiographic Signal in Dogs2008In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 55, no 8, 2107-2109 p.Article in journal (Refereed)
    Abstract [en]

    In aortic valve stenosis (AS), heart murmurs arise as an effect of turbulent blood flow distal to the obstructed valves. With increasing AS severity, the flow becomes more unstable, and the ensuing murmur becomes more complex. We hypothesize that these hemodynamic flow changes can be quantified based on the complexity of the phonocardiographic (PCG) signal. In this study, sample entropy (SampEn) was investigated as a measure of complexity using a dog model. Twenty-seven boxer dogs with various degrees of AS were examined with Doppler echocardiography, and the peak aortic flow velocity (Vmax) was used as a reference of AS severity. SampEn correlated to Vmax with R = 0.70 using logarithmic regression. In a separate analysis, significant differences were found between physiologic murmurs and murmurs caused by AS (p < 0.05), and the area under a receiver operating characteristic curve was calculated to 0.96. Comparison with previously presented PCG measures for AS assessment showed improved performance when using SampEn, especially for differentiation between physiological murmurs and murmurs caused by mild AS. Studies in patients will be needed to properly assess the technique in humans.

  • 17.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Höglund, Katja
    Dept. of Anatomy and Physiology, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Häggström, Jens
    Dept. of Clinical Sciences, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Kvart, Clarence
    Dept. of Anatomy and Physiology, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Distinguishing Innocent Murmurs from Murmurs caused by Aortic Stenosis by Recurrence Quantification Analysis2006In: ROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 18, Canakkale, Turkey: World Academy of Science, Engineering and Technology (W A S E T) , 2006, 40-45 p.Conference paper (Refereed)
    Abstract [en]

    It is sometimes difficult to differentiate between innocent murmurs and pathological murmurs during auscultation. In these difficult cases, an intelligent stethoscope with decision support abilities would be of great value. In this study, using a dog model, phonocardiographic recordings were obtained from 27 boxer dogs with various degrees of aortic stenosis (AS) severity. As a reference for severity assessment, continuous wave Doppler was used. The data were analyzed with recurrence quantification analysis (RQA) with the aim to find features able to distinguish innocent murmurs from murmurs caused by AS. Four out of eight investigated RQA features showed significant differences between innocent murmurs and pathological murmurs. Using a plain linear discriminant analysis classifier, the best pair of features (recurrence rate and entropy) resulted in a sensitivity of 90% and a specificity of 88%. In conclusion, RQA provide valid features which can be used for differentiation between innocent murmurs and murmurs caused by AS.

  • 18.
    Ahlström, Christer
    et al.
    Swedish National Rd and Transport Research Institute VTI, S-58195 Linkoping, Sweden.
    Jansson, Sabina
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Anund, Anna
    Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Rehabilitation Medicine. Swedish National Rd and Transport Research Institute VTI, S-58195 Linkoping, Sweden.
    Local changes in the wake electroencephalogram precedes lane departures2017In: Journal of Sleep Research, ISSN 0962-1105, E-ISSN 1365-2869, Vol. 26, no 6, 816-819 p.Article in journal (Refereed)
    Abstract [en]

    The objective of this exploratory study is to investigate if lane departures are associated with local sleep, measured via source-localized electroencephalography (EEG) theta power in the 5-9 Hz frequency range. Thirty participants drove in an advanced driving simulator, resulting in 135 lane departures at high levels of self-reported sleepiness. These lane departures were compared to matching non-departures at the same sleepiness level within the same individual. There was no correspondence between lane departures and global theta activity. However, at the local level an increased risk for lane departures was associated with increased theta content in brain regions related to motor function.

  • 19.
    Ahlström, Christer
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Johansson, Anders
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Chaotic dynamics of respiratory sounds2006In: Chaos, Solitons & Fractals, ISSN 0960-0779, E-ISSN 1873-2887, Vol. 29, no 5, 1054-1062 p.Article in journal (Refereed)
    Abstract [en]

    There is a growing interest in nonlinear analysis of respiratory sounds (RS), but little has been done to justify the use of nonlinear tools on such data. The aim of this paper is to investigate the stationarity, linearity and chaotic dynamics of recorded RS. Two independent data sets from 8 + 8 healthy subjects were recorded and investigated. The first set consisted of lung sounds (LS) recorded with an electronic stethoscope and the other of tracheal sounds (TS) recorded with a contact accelerometer. Recurrence plot analysis revealed that both LS and TS are quasistationary, with the parts corresponding to inspiratory and expiratory flow plateaus being stationary. Surrogate data tests could not provide statistically sufficient evidence regarding the nonlinearity of the data. The null hypothesis could not be rejected in 4 out of 32 LS cases and in 15 out of 32 TS cases. However, the Lyapunov spectra, the correlation dimension (D2) and the Kaplan-Yorke dimension (DKY) all indicate chaotic behavior. The Lyapunov analysis showed that the sum of the exponents was negative in all cases and that the largest exponent was found to be positive. The results are partly ambiguous, but provide some evidence of chaotic dynamics of RS, both concerning LS and TS. The results motivate continuous use of nonlinear tools for analysing RS data. © 2005 Elsevier Ltd. All rights reserved.

  • 20.
    Ahlström, Christer
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Johansson, Anders
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Länne, Toste
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    A respiration monitor based on electrocardiographic and photoplethysmographic sensor fusion2004In: IEEE Engineering in Medical and Biological Society,2004, Piscataway, N.J. USA: IEEEEMBS , 2004, 2311- p.Conference paper (Refereed)
  • 21.
    Ahlström, Christer
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Johansson, Anders
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Länne, Toste
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Monitorering av andning and blodtrycksförändringar baserat på EKG och hjärtljud2007In: Medicinteknik dagarna,2007, 2007Conference paper (Other academic)
  • 22.
    Ahlström, Christer
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Johansson, Anders
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Uhlin, Fredrik
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Nephrology.
    Länne, Toste
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Noninvasive investigation of blood pressure changes using the pulse wave transit time: A novel approach in the monitoring of hemodialysis patients2005In: Journal of Artificial Organs, ISSN 1434-7229, E-ISSN 1619-0904, Vol. 8, no 3, 192-197 p.Article in journal (Refereed)
    Abstract [en]

    Severe blood pressure changes are well known in hemodialysis. Detection and prediction of these are important for the well-being of the patient and for optimizing treatment. New noninvasive methods for this purpose are required. The pulse wave transit time technique is an indirect estimation of blood pressure, and our intention is to investigate whether this technique is applicable for hemodialysis treatment. A measurement setup utilizing lower body negative pressure and isometric contraction was used to simulate dialysis-related blood pressure changes in normal test subjects. Systolic blood pressure levels were compared to different pulse wave transit times, including and excluding the cardiac preejection period. Based on the results of these investigations, a pulse wave transit time technique adapted for dialysis treatment was developed and tried out on patients. To determine systolic blood pressure in the normal group, the total pulse wave transit time was found most suitable (including the cardiac preejection period). Correlation coefficients were r = 0.80 ± 0.06 (mean ± SD) overall and r = 0.81 ± 0.16 and r = 0.09 ± 0.62 for the hypotension and hypertension phases, respectively. When applying the adapted technique in dialysis patients, large blood pressure variations could easily be detected when present. Pulse wave transit time is correlated to systolic blood pressure within the acceptable range for a trend-indicating system. The method's applicability for dialysis treatment requires further studies. The results indicate that large sudden pressure drops, like those seen in sudden hypovolemia, can be detected. © The Japanese Society for Artificial Organs 2005.

  • 23.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering.
    Liljefeldt, Olle
    Hult, Peter
    Linköping University, Department of Biomedical Engineering.
    Ask, Per
    Linköping University, Department of Biomedical Engineering.
    Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction.2005In: Medicinteknikdagarna, 2005, Vol. 12, 812-815 p.Conference paper (Other academic)
    Abstract [en]

    Heart sounds (HS) obscure the interpretation of lung sounds (LS). This letter presents a new method to detect and remove this undesired disturbance. The HS detection algorithm is based on a recurrence time statistic that is sensitive to changes in a reconstructed state space. Signal segments that are found to contain HS are removed, and the arising missing parts are replaced with predicted LS using a nonlinear prediction scheme. The prediction operates in the reconstructed state space and uses an iterated integrated nearest trajectory algorithm. The HS detection algorithm detects HS with an error rate of 4% false positives and 8% false negatives. The spectral difference between the reconstructed LS signal and an LS signal with removed HS was 0 34 0 25, 0 50 0 33, 0 46 0 35, and 0 94 0 64 dB/Hz in the frequency bands 20–40, 40–70, 70–150, and 150–300 Hz, respectively. The cross-correlation index was found to be 99.7%, indicating excellent similarity between actual LS and predicted LS. Listening tests performed by a skilled physician showed high-quality auditory results.

  • 24.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Liljefeldt, Olle
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction2005In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 12, no 12, 812-815 p.Article in journal (Refereed)
    Abstract [en]

    Heart sounds (HS) obscure the interpretation of lung sounds (LS). This letter presents a new method to detect and remove this undesired disturbance. The HS detection algorithm is based on a recurrence time statistic that is sensitive to changes in a reconstructed state space. Signal segments that are found to contain HS are removed, and the arising missing parts are replaced with predicted LS using a nonlinear prediction scheme. The prediction operates in the reconstructed state space and uses an iterated integrated nearest trajectory algorithm. The HS detection algorithm detects HS with an error rate of 4% false positives and 8% false negatives. The spectral difference between the reconstructed LS signal and an LS signal with removed HS was 0.34/spl plusmn/0.25, 0.50/spl plusmn/0.33, 0.46/spl plusmn/0.35, and 0.94/spl plusmn/0.64 dB/Hz in the frequency bands 20-40, 40-70, 70-150, and 150-300 Hz, respectively. The cross-correlation index was found to be 99.7%, indicating excellent similarity between actual LS and predicted LS. Listening tests performed by a skilled physician showed high-quality auditory results.

  • 25.
    Ahlström, Christer
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
    Länne, Toste
    Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
    Johansson, Anders
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Health Sciences.
    A method for accurate localization of the first heart sound and possible applications2008In: Physiological Measurement, ISSN 0967-3334, E-ISSN 1361-6579, Vol. 29, no 3, 417-428 p.Article in journal (Refereed)
    Abstract [en]

    We have previously developed a method for localization of the first heart sound (S1) using wavelet denoising and ECG-gated peak-picking. In this study, an additional enhancement step based on cross-correlation and ECG-gated ensemble averaging (EA) is presented. The main objective of the improved method was to localize S1 with very high temporal accuracy in (pseudo-) real time. The performance of S1 detection and localization, with and without EA enhancement, was evaluated on simulated as well as experimental data. The simulation study showed that EA enhancement reduced the localization error considerably and that S1 could be accurately localized at much lower signal-to-noise ratios. The experimental data were taken from ten healthy subjects at rest and during invoked hyper- and hypotension. For this material, the number of correct S1 detections increased from 91% to 98% when using EA enhancement. Improved performance was also demonstrated when EA enhancement was used for continuous tracking of blood pressure changes and for respiration monitoring via the electromechanical activation time. These are two typical applications where accurate localization of S1 is essential for the results.

  • 26.
    Ahn, Henrik Casimir
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Jodal, M.
    Lindhagen, J
    Lundgren, O.
    Nilsson, Gert
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Salerud, Göran
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Bestämning av tunntarmsblodflödet med laser Doppler teknik1984In: Läkarsällskapets Riksstämma,1984, 1984Conference paper (Other academic)
  • 27.
    Ahn, Henrik Casimir
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Johansson, K.
    Lindhagen, J.
    Nilsson, Gert
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Salerud, Göran
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Förändringar av blodflödet i ventrikeln i samband med mätt med laser Dopplerteknik1984In: Läkarsällskapets Riksstämma,1984, 1984Conference paper (Other academic)
  • 28.
    Ahn, Henrik Casimir
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Johansson, K.
    Lindhagen, J.
    Salerud, Göran
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Laser Doppler flowmetry in the assessment of gastric blood flow1984In: man. Scand J of Gastroenterology,1984, 1984, 98:33-98:33 p.Conference paper (Other academic)
  • 29.
    Ahn, Henrik Casimir
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Lindhagen, J.
    Nilsson, Gert
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Salerud, Göran
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Jodal, M.
    Lundgren, O.
    Evaluation of Laser Doppler Flowmetry in the assessment of blood flow in the small intestine1984In: Third World Congress of Microcirculation,1984, 1984Conference paper (Other academic)
  • 30.
    Ahn, Henrik Casimir
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Lindhagen, J
    Nilsson, Gert
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Salerud, Göran
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Jodal, M
    Lundgren, O
    Evaluation of Laser Doppler Flowmetry in the assessment of intestinal blood flow1985In: Gastroenterology, ISSN 0016-5085, E-ISSN 1528-0012, Vol. 4, no 88, 951-957 p.Article in journal (Refereed)
    Abstract [en]

      

  • 31.
    Akbarian-Tefaghi, Ladan
    et al.
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Akram, Harith
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Johansson, Johannes
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Zrinzo, Ludvic
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Kefalopoulou, Zinovia
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Limousin, Patricia
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Joyce, Eileen
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Hariz, Marwan
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Foltynie, Tom
    Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, London, UK.
    Refining the Deep Brain Stimulation Target within the Limbic Globus Pallidus Internus for Tourette Syndrome2017In: Stereotactic and Functional Neurosurgery, ISSN 1011-6125, E-ISSN 1423-0372, Vol. 95, no 4, 251-258 p.Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Deep brain stimulation (DBS) in patients with severe, refractory Tourette syndrome (TS) has demonstrated promising but variable results thus far. The thalamus and anteromedial globus pallidus internus (amGPi) have been the most commonly stimulated sites within the cortico-striato thalamic circuit, but an optimal target is yet to be elucidated.

    OBJECTIVES: This study of 15 patients with long-term amGPi DBS for severe TS investigated whether a specific anatomical site within the amGPi correlated with optimal clinical outcome for the measures of tics, obsessive compulsive behaviour (OCB), and mood.

    METHODS: Validated clinical assessments were used to measure tics, OCB, quality of life, anxiety, and depression before DBS and at the latest follow-up (17-82 months). Electric field simulations were created for each patient using information on electrode location and individual stimulation parameters. A subsequent regression analysis correlated these patient-specific simulations to percentage changes in outcome measures in order to identify any significant voxels related to clinical improvement.

    RESULTS: A region within the ventral limbic GPi, specifically on the medial medullary lamina in the pallidum at the level of the AC-PC, was significantly associated with improved tics but not mood or OCB outcome.

    CONCLUSIONS: This study adds further support to the application of DBS in a tic-related network, though factors such as patient sample size and clinical heterogeneity remain as limitations and replication is required.

    The full text will be freely available from 2018-08-05 15:57
  • 32.
    Almeida, Eduardo Carlos Venancio de
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
    Development of a wearable sensor system for real-time control of knee prostheses2012Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
    Abstract [en]

    It was demonstrated in recent studies that Complementary Limb Motion Estimation (CLME) is robust approach for controlling active knee prostheses. A wearable sensor system is then needed to provide inputs to the controller in a real-time platform. In the present work, a wearable sensor system based on magnetic and inertial measurement units (MIMU) together with a simple calibration procedure were proposed. This sensor system was intended to substitute and extend the capabilities of a previous device based on potentiometers and gyroscopes. The proposed sensor system and calibration were validated with an Optical Tracking System (OTS) in a standard gait lab and first results showed that the proposed solution had a performance comparable to similar studies in the literature.

  • 33.
    Almeida, Rosimary
    Linköping University, Department of Biomedical Engineering, Center for Medical Image Science and Visualization. Linköping University, The Institute of Technology.
    Severity of illness versus severity of disease: definitions and applications1996Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Outcome assessment should consist of two basic steps - "selection of a meaningful outcome" and "determination of what caused the outcome". The latter step requires comparisons, and therefore information about the initial status of the patients. Severity ratings attempt to group patients with similar initial status so that outcome comparisons are meaningful. They are consequently an essential ingredient in outcome assessment.

    This thesis aims at expanding the knowledge about outcome measurement focusing on the severity of a case with regard to definitions and applications of severity measures. Further, theoretical knowledge is integrated with practical needs for outcome assessment and methodology is developed for modelling the use of resources and interpreting the association between different severity measures.

    As with illness and disease, severity of illness and severity of disease are interchangeable terms in medical literature. Based on a holistic theory of health, these terms were differentiated. Severity of a case was described by two basic components - severity of disease and severity of illness. Essentially, severity of illness concerns suffering and disability, and severity of disease concerns risk of death, risk of suffering and risk of disability. These definitions were the core of a set of criteria for classifying severity measures or outcome measures.

    The role of a disease severity score in explaining resources use (e.g., intensity of technology utilization and length of hospital stay) in a neonatal intensive care unit was investigated. A disease severity score based on the death risk of the initial diagnosis was found to be an indicator of intensity of therapeutic technology together with gestational age and Apgar score. However, it does not show statistical significance to explain length of stay, which was explained by intensity of diagnostic technology and birthweight.

    The demand for patient classification systems (standard systems to describe a patient's condition) on a national and local level was investigated. There is little experience in the use of these systems, but at the same time there is a demand from the nurse managers for standard measures of a patient's need for care.

    There is still little knowledge about the association between severity of illness and severity of disease. This association was studied for patients with ulcerative colitis using data analysis techniques for dimension reduction such as cluster analysis, homogeneity analysis and non linear principal components analysis. A non linear relationship between illness and disease severity measures was found. The overall clinical judgement of disease activity was more related to illness patterns than symptoms or endoscopy and laboratory findings. In addition, the two measures of illness severity (Sickness Impact Profile and Rating Form for Inflammatory Bowel Disease Patient Concerns) were found to represent complementary information about a patient's illness experience. This illustrates the importance of conceptual knowledge in the selection process of an illness measure for outcome evaluations. These findings also reinforce the need for the development of systems to support interpretation of these kinds of complex associations, as traditional statistics have been shown to be of limited value under these circumstances.

  • 34.
    Almqvist, Ulf
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Sjörs, Anna
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Validation of MobileMe: a psychophysiological recording system – from a motion sickness perspective2006Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    MobileMe is a recently developed system for monitoring and recording physiological variables. It is wireless, and can therefore be suitable for field research, for example when measuring motion sickness symptoms.

    The aim of this thesis was to conclude whether the MobileMe recording system was valid for research studies. A validation study, consisting of two parts and including 10 subjects, was performed. The first part was a laboratory study, where data from MobileMe and a reference equipment were compared. A field study was also performed, onboard a combat boat, to determine the equipment’s validity in uncontrolled environments. Furthermore, the field study included an investigation of motion sickness symptoms, and provided data for evaluation of motion sickness rating scales.

    Statistical results from the laboratory study, and results from evaluation of data from the field study, showed that MobileMe was valid in both controlled and uncontrolled environments.

  • 35.
    Alonso, Fabiola
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
    Modeling and simulation of DBS – comparison between leads and stimulation modes2014Conference paper (Other academic)
  • 36.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Hemm-Ode, Simone
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology. University of Applied Sciences and Arts Northwestern Switzerland.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Influence on Deep Brain Stimulation from Lead Design, Operating Mode and Tissue Impedance Changes – A Simulation Study2015In: Brain Disorders and Therapy, ISSN 2168-975X, Vol. 4, no 3, 1000169Article in journal (Refereed)
    Abstract [en]

    Background: Deep brain stimulation (DBS) systems in current mode and new lead designs are recently available. To switch between DBS-systems remains complicated as clinicians may lose their reference for programming. Simulations can help increase the understanding.

    Objective: To quantitatively investigate the electric field (EF) around two lead designs simulated to operate in voltage and current mode under two time points following implantation.

    Methods: The finite element method was used to model Lead 3389 (Medtronic) and 6148 (St Jude) with homogenous surrounding grey matter and a peri-electrode space (PES) of 250 μm. The PES-impedance mimicked the acute (extracellular fluid) and chronic (fibrous tissue) time-point. Simulations at different amplitudes of voltage and current (n=236) were performed using two different contacts. Equivalent current amplitudes were extracted by matching the shape and maximum EF of the 0.2 V/mm isolevel.

    Results: The maximum EF extension at 0.2 V/mm varied between 2-5 mm with a small difference between the leads. In voltage mode EF increased about 1 mm at acute compared to the chronic PES. Current mode presented the opposite relationship. Equivalent EFs for lead 3389 at 3 V were found for 7 mA (acute) and 2.2 mA (chronic).

    Conclusions: Simulations showed a major impact on the electric field extension between postoperative time points. This may explain the clinical decisions to reprogram the amplitude weeks after implantation. Neither the EF extension nor intensity is considerably influenced by the lead design.

  • 37.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Latorre, Malcolm
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Göransson, Nathanael
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Zsigmond, Peter
    Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery. Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences.
    Wårdell, karin
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Investigation into Deep Brain Stimulation Lead Designs: A Patient-Specific Simulation Study2016In: Brain Sciences, ISSN 2076-3425, E-ISSN 2076-3425, Vol. 6, no 3, 1-16 p.Article in journal (Refereed)
    Abstract [en]

    New deep brain stimulation (DBS) electrode designs offer operation in voltage and current mode and capability to steer the electric field (EF). The aim of the study was to compare the EF distributions of four DBS leads at equivalent amplitudes (3 V and 3.4 mA). Finite element method (FEM) simulations (n = 38) around cylindrical contacts (leads 3389, 6148) or equivalent contact configurations (leads 6180, SureStim1) were performed using homogeneous and patient-specific (heterogeneous) brain tissue models. Steering effects of 6180 and SureStim1 were compared with symmetric stimulation fields. To make relative comparisons between simulations, an EF isolevel of 0.2 V/mm was chosen based on neuron model simulations (n = 832) applied before EF visualization and comparisons. The simulations show that the EF distribution is largely influenced by the heterogeneity of the tissue, and the operating mode. Equivalent contact configurations result in similar EF distributions. In steering configurations, larger EF volumes were achieved in current mode using equivalent amplitudes. The methodology was demonstrated in a patient-specific simulation around the zona incerta and a “virtual” ventral intermediate nucleus target. In conclusion, lead design differences are enhanced when using patient-specific tissue models and current stimulation mode.

  • 38.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering.
    Latorre, Malcolm
    Linköping University, Department of Biomedical Engineering.
    Zsigmond, Peter
    Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery. Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering.
    Brain Stimulation Steering of the Electric Field: A Patient-Specific Simulation Study2016Conference paper (Refereed)
  • 39.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Vogel, Dorian
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Hemm-Ode, Simone
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Institute for Medical and Analytical Technologies and Department of Biomedical Engineering, University of Applied Sciences and Art Northwestern Switzerland.
    Comparison between intraoperative and chronic and deep brain stimulation2017Conference paper (Refereed)
    Abstract [en]

    INTRODUCTION

    The success of the deep brain stimulation (DBS) therapy relies primarily in the localization of the implanted electrode, implying the need of utmost accuracy in the targeting process. Intraoperative microelectrode recording and stimulation tests are a common procedure before implanting the permanent DBS lead to determine the optimal position with a large therapeutic window where side effects are avoided and the best improvement of the symptoms is achieved. Differences in dimensions and operating modes exist between the exploration and the permanent DBS electrode which might lead to different stimulation fields, even when ideal placement is achieved. The aim of this investigation is to compare the electric field (EF) distribution around the intraoperative and the chronic electrode, assuming that both have exactly the same position.

    METHODS

    3D models of the intraoperative exploration electrode and the chronically implanted DBS lead 3389 (Medtronic Inc., USA) were developed using COMSOL 5.2 (COMSOL AB, Sweden). Patient-specific MR images were used to determine the conductive medium around the electrode. The exploration electrode and the first DBS contact were set to current and voltage respectively (0.2mA(V) - 3 mA(V) in 0.1 mA(V) steps). The intraoperative model included the grounded guide tube used to introduce the exploration electrode; for the chronic DBS model, the outer boundaries were grounded and the inactive contacts were set to floating potential considering a monopolar configuration. The localization of the exploration and the chronic electrode was set according to the planned trajectory. The EF was visualized and compared in terms of volume and extension using a fixed isocontour of 0.2 V/mm.

    RESULTS

    The EF distribution simulated for the exploration electrode showed the influence of the parallel trajectory and the grounded guide tube. For an amplitude of e.g. 2 mA/2 V, the EF extension of the intraoperative was 0.6 mm larger than the chronic electrode at the target level; the corresponding difference in volume was 76.1 mm3.

    CONCLUSION

    Differences in the EF shape between the exploration and the chronic DBS electrode have been observed using patient-specific models. The larger EF extension obtained for the exploration electrode responds to its higher impedance and the use of current controlled stimulation. The presence of EF around the guide tube and the influence of the parallel trajectory require further experimental and clinical evaluation.

  • 40.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
    Comparison of deep brain stimulation systems2014In: Poster Presentations, 2014, Vol. 29, 1173-1173 p., Suppl 1Conference paper (Other academic)
    Abstract [en]

    Objective: To quantitatively compare the electric field generated by voltage and current controlled deep brain stimulation systems.

    Background: Traditionally deep brain stimulation (DBS) systems have used voltage control however more recently, current controlled systems have been approved to treat Parkinson's disease and related movement disorders. In the endeavor of understanding the behavior of DBS systems a common approach is the use of computer models suitable to simulate the electric field, current density and other related electric parameters.

    Methods: 2D finite element models based on commercially available DBS systems have been built for each system: I. Model 3389, Medtronic Inc., USA for voltage control; and II. Model 6142, St Jude Medical Inc. USA for current control. The brain tissue has been simplified to homogeneous and isotropic medium. The electric settings correspond to a monopolar configuration, using one of the four contacts available as the active electrode and the outer boundary of the tissue as the reference. Three simulations were performed to mimic different stages of the leads implantation: a) an original stage where the brain tissue is considered as pure gray matter, b) an acute stage that simulates the leakage of cerebral spinal fluid immediately after the electrodes' insertion; and c) a chronic stage mimicking fibrous tissue created around the electrodes some weeks after implantation. Both systems were submitted to the same conditions using as active electrode the third contact from the tip of the lead. The comparison is based on the maximal distance reached by the isopotential of 0.2 V/mm.

    Results: The simulations showed that voltage controlled stimulation systems are more susceptible to changes in the electrical conductivity of the medium i.e. change over time of the tissue around the electrode. This agrees with the adjustment of the stimulation amplitude often necessary a few weeks postoperatively. Current controlled stimulation in turn, presented a linear behavior of the distance reached at different stimulation amplitudes at all stages.

    Conclusions: Current controlled stimulation might be a good option due to its linear behavior over time, nevertheless more studies including a more realistic brain model, different designs of DBS electrodes and different electric parameter, are needed to encourage the use of this type of systems.

  • 41.
    Alonso, Fabiola
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Electric Field Comparison of Deep Brain Stimulation Lead Designs - a Stimulation Study2016Conference paper (Refereed)
  • 42.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Latorre, Malcolm
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Comparison of Three Deep Brain Stimulation Lead Designs under Voltage and Current Modes2015In: WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, 2015, VOLS 1 AND 2 / [ed] David A. Jaffray, Springer, 2015, Vol. 51, 1196-1199 p.Conference paper (Refereed)
    Abstract [en]

    Since the introduction of deep brain stimulation (DBS) the technique has been dominated by Medtronic sys-tems. In recent years, new DBS systems have become available for patients, and some are in clinical trials. The present study aims to evaluate three DBS leads operated in either voltage or current mode. 3D finite element method (FEM) models were built in combination with a neuron model for this purpose. The axon diameter was set to D = 5 μm and simulations performed in both voltage (0.5-5 V) and current (0.5-5 mA) mode. The evaluation was achieved based on the distance from the lead for neural activation and the electric field (EF) extension at 0.1 V/mm. The results showed that the neural activation distance agrees well between the leads with an activation distance dif-ference less than 0.5 mm. The shape of the field at the 0.1 V/mm isopotential surface in 3D is mostly spherical in shape around the activated section of the steering lead.

  • 43.
    Alonso, Fabiola
    et al.
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Latorre, Malcolm
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, Faculty of Science & Engineering.
    Neural Activation Compared to Electric Field Extension of Three DBS Lead Designs2015Conference paper (Refereed)
    Abstract [en]

    SINCE the introduction of deep brain stimulation (DBS) about 20 years ago, the stimulation technique has been dominated by Medtronic DBS-system setup. In recent years, new DBS systems have become available, of which some are in clinical trials or available to patients [1]. In the present study three different lead designs are investigated via computer simulation:

    Medtronic 3389, St. Jude 6148 and Sapiens SureStim. The aim was to compare the neural activation distance and the electric field (EF) maximum spatial extension for each lead.

    A 3D finite element method model was built using COMSOL Multiphysics 4.4a (COMSOL AB, Stockholm, Sweden) to simulate the electric potential around the DBS lead. Brain tissue was modelled as a homogeneous volume of grey matter (electric conductivity of 0.09 S/m). The electrode-tissue interface was modelled with a 250μm thick peri-electrode space mimicking the fibrous tissue which covers the lead at the chronic stimulation stage (σ = 0.06S/m, equivalent to white matter electric conductivity). The stimulation amplitude was set to 1V in monopolar configuration using C1 electrode or equivalent in all cases. Each simulated electric potential distribution was exported to MatLab (The MathWorks, USA) and used as input to a cable neuron simulation.

    An axon cable model with 21 nodes based on the concept by Åström et al., [2] was set up in MatLab and combined with the exported field distributions. The model considered a 5 μm thick neuron, a pulse width of 60 μs and a drive potential ranging from 0.5 V to 5 V in 0.5 V steps.

    The SureStim lead results showed a shorter neural activation distance and EF extension. The distance to the isolevel of 0.2 V/mm is close to the neural activation distance at each stimulation amplitude, and we conclude that the electric field is a suitable predictor to visualize the stimulated regions.

  • 44.
    Alonso Orozco, Fabiola
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Finite Element Method Modelling and Simulations for Comparisonbetween Deep Brain Stimulation Electrodes2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The Deep Brain Stimulation (DBS) is an invasive therapy that alleviates the symptoms of several neurological disorders by electrically stimulating specific regions of the brain, generally within the basal ganglia. Until now Medtronic DBS system is the only approved by the Food and Drug Administration, nevertheless European and Australian countries  have recently approved St. Jude DBS systems to treat Parkinson’s disease and related movement disorders.

         Traditionally, voltage-controlled stimulation (the type of systems provided by Medtronic) has been used and clinicians are familiar with its settings; however the knowledge about systems based in current-controlled stimulation (St. Jude systems) is rather scarce. One of the key factors for a successful therapy is the optimal selection of the electrical parameters for stimulation. Due to the critical zone where the surgery is performed, modeling and simulations of DBS systems have been extensively used to observe how the electric field is distributed in the brain tissue and ultimately to help the clinicians to select the best parameters.

         In this thesis two finite element models of the DBS systems mentioned above have been developed; five examinations were designed, based on the physical and electrical differences between the systems, to observe and quantitatively compare the electric field distribution.

        The aim of this thesis was to investigate the differences between two representative models of each company but moreover to contribute with information regarding current-controlled stimulation.

    The results obtained are expected to be useful for further investigations where the magnitude and distribution of the electric field generated by this type of electrodes are needed.

  • 45.
    Andersen, Per Øivin
    et al.
    University of Bergen, Norway.
    Babic, Ankica
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. University of Bergen, Norway.
    Mobile-supported life charting for bipolar patients - user requirements study2013In: MEDINFO 2013: proceedings of the 14th World Congress on Medical and Health Informatics / [ed] Christoph Ulrich Lehmann, Elske Ammenwerth, Christian Nøhr, IOS Press, 2013, 1111- p.Conference paper (Other academic)
    Abstract [en]

    It is assumed that bipolar disorder patients can benefit from monitoring their mood, sleep, medicine intake and behavior which could be both done by patients themselves and in cooperation with health care professionals. This study aims at understanding what is required from a computerized system, as seen from the view of therapists and the patients, and how the newer mobile technologies (smart phones and tablets) can be utilized to support development of such a system. The study focuses on several existing solutions available either freely or on the market. Then these solutions are evaluated by both patients and medical professionals as a part of the system requirements study to be used in a new system development that will utilize mobile technologies to support the performance and patient outcomes.

  • 46. Anderson, C.
    et al.
    Andersson, T.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
    Changes in skin circulation after microdialysis probe insertion visualized by laser Doppler perfusion imaging1994In: Journal of Investigative Dermatology, ISSN 0022-202X, E-ISSN 1523-1747, Vol. 102, no 5, 807-811 p.Article in journal (Refereed)
    Abstract [en]

    Microdialysis makes possible in vivo estimation of endogenous and exogenous substances in the dermal extracellular space. Insertion of the microdialysis probe and its subsequent presence in the skin may affect both the reactivity of the skin test site and the measurement of target substances. Laser Doppler flowmetry is a non-invasive method for estimating cutaneous blood flow. A further development of this technique, laser Doppler perfusion imaging, has been used to study the time course of the circulatory changes caused in the area of microdialysis probe insertion. Laser Doppler perfusion imaging was performed prior to, during, and after microdialysis probe insertion in the skin of the ventral forearm in three subjects. Probe insertion caused an increase in skin blood perfusion in the whole test area. About 15 min after probe insertion, the flare, which is presumed to be of chiefly axon reflex origin, began to subside and the circulatory response could be seen to center around the site of insertion and the tip of the probe. Skin perfusion levels had returned to near normal levels within 60 min. Local anesthesia of the point of guide insertion inhibited the flare, but did not affect circulatory reactivity in the skin nearby. Both microdialysis and laser Doppler perfusion imaging seem to be promising new methods in dermatologic research.

  • 47. Anderson, C.
    et al.
    Svensson, .
    Sjögren, F.
    Andersson, T.
    Wårdell, Karin
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
    Human in vivo microdialysis technique can be used to measure cytokines in contact reactions.1995In: Current Problems in Dermatology, ISSN 1421-5721, E-ISSN 1662-2944, Vol. 23, 121-130 p.Article in journal (Refereed)
  • 48.
    Anderson, Chris
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Biomedicine and Surgery, Division of dermatology and venereology. Östergötlands Läns Landsting, Centre for Medicine, Department of Dermatology and Venerology in Östergötland.
    Lindén, Maria
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    High resolution laser Doppler perfusion imaging for visualisation of changes in skin circulation after microdialysis probe insertion1996In: Jadassohn Centenary Congress,1996, 1996Conference paper (Other academic)
  • 49.
    Anderson, Chris
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Biomedicine and Surgery, Division of dermatology and venereology. Östergötlands Läns Landsting, Centre for Medicine, Department of Dermatology and Venerology in Östergötland.
    Wårdell, Karin
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Analysis of laser Doppler perfusion images from contact reactions1996In: Jadassohn Centenary Congress,1996, 1996Conference paper (Other academic)
  • 50.
    Andersson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Automatic vertebrae detection and labeling in sagittal magnetic resonance images2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Radiologists are often plagued by limited time for completing their work, with an ever increasing workload. A picture archiving and communication system (PACS) is a platform for daily image reviewing that improves their work environment, and on that platform for example spinal MR images can be reviewed. When reviewing spinal images a radiologist wants vertebrae labels, and in Sectra's PACS platform there is a good opportunity for implementing an automatic method for spinal labeling. In this thesis a method for performing automatic spinal labeling, called a vertebrae classifier, is presented. This method should remove the need for radiologists to perform manual spine labeling, and could be implemented in Sectra's PACS software to improve radiologists overall work experience.Spine labeling is the process of marking vertebrae centres with a name on a spinal image. The method proposed in this thesis for performing that process was developed using a machine learning approach for vertebrae detection in sagittal MR images. The developed classifier works for both the lumbar and the cervical spine, but it is optimized for the lumbar spine. During the development three different methods for the purpose of vertebrae detection were evaluated. Detection is done on multiple sagittal slices. The output from the detection is then labeled using a pictorial structure based algorithm which uses a trained model of the spine to correctly assess correct labeling.

    The suggested method achieves 99.6% recall and 99.9% precision for the lumbar spine. The cervical spine achieves slightly worse performance, with 98.1% for both recall and precision. This result was achieved by training the proposed method on 43 images and validated with 89 images for the lumbar spine. The cervical spine was validated using 26 images. These results are promising, especially for the lumbar spine. However, further evaluation is needed to test the method in a clinical setting.

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