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Ahlström, Christer
Publications (10 of 32) Show all publications
Thorslund, B., Ahlström, C., Peters, B., Eriksson, O., Lidestam, B. & Lyxell, B. (2014). Cognitive workload and visual behavior in elderly drivers with hearing loss. European Transport Research Review, 6(4), 377-385
Open this publication in new window or tab >>Cognitive workload and visual behavior in elderly drivers with hearing loss
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2014 (English)In: European Transport Research Review, ISSN 1867-0717, E-ISSN 1866-8887, Vol. 6, no 4, p. 377-385Article in journal (Refereed) Published
Abstract [en]

Purpose

To examine eye tracking data and compare visual behavior in individuals with normal hearing (NH) and with moderate hearing loss (HL) during two types of driving conditions: normal driving and driving while performing a secondary task.

Methods

24 participants with HL and 24 with NH were exposed to normal driving and to driving with a secondary task (observation and recall of 4 visually displayed letters). Eye movement behavior was assessed during normal driving by the following performance indicators: number of glances away from the road; mean duration of glances away from the road; maximum duration of glances away from the road; and percentage of time looking at the road. During driving with the secondary task, eye movement data were assessed in terms of number of glances to the secondary task display, mean duration of glances to the secondary task display, and maximum duration of glances to the secondary task display. The secondary task performance was assessed as well, counting the number of correct letters, the number of skipped letters, and the number of correct letters ignoring order.

Results

While driving with the secondary task, drivers with HL looked twice as often in the rear-view mirror than during normal driving and twice as often as drivers with NH regardless of condition. During secondary task, the HL group looked away from the road more frequently but for shorter durations than the NH group. Drivers with HL had fewer correct letters and more skipped letters than drivers with NH.

Conclusions

Differences in visual behavior between drivers with NH and with HL are bound to the driving condition. Driving with a secondary task, drivers with HL spend as much time looking away from the road as drivers with NH, however with more frequent and shorter glances away. Secondary task performance is lower for the HL group, suggesting this group is less willing to perform this task. The results also indicate that drivers with HL use fewer but more focused glances away than drivers with NH, they also perform a visual scan of the surrounding traffic environment before looking away towards the secondary task display.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2014
Keywords
Hearing loss; Driving simulator; Visual behavior; Cognitive workload
National Category
Social Sciences Interdisciplinary Other Medical Sciences not elsewhere specified
Identifiers
urn:nbn:se:liu:diva-111932 (URN)10.1007/s12544-014-0139-z (DOI)000209729200003 ()2-s2.0-84920249351 (Scopus ID)
Available from: 2014-11-10 Created: 2014-11-10 Last updated: 2018-01-11Bibliographically approved
Ahlström, C., Nystrom, M., Holmqvist, K., Fors, C., Sandberg, D., Anund, A., . . . Akerstedt, T. (2013). Fit-for-duty test for estimation of drivers sleepiness level: Eye movements improve the sleep/wake predictor. Transportation Research Part C: Emerging Technologies, 26, 20-32
Open this publication in new window or tab >>Fit-for-duty test for estimation of drivers sleepiness level: Eye movements improve the sleep/wake predictor
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2013 (English)In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 26, p. 20-32Article in journal (Refereed) Published
Abstract [en]

Driver sleepiness contributes to a considerable proportion of road accidents, and a fit-for-duty test able to measure a drivers sleepiness level might improve traffic safety. The aim of this study was to develop a fit-for-duty test based on eye movement measurements and on the sleep/wake predictor model (SWP, which predicts the sleepiness level) and evaluate the ability to predict severe sleepiness during real road driving. Twenty-four drivers participated in an experimental study which took place partly in the laboratory, where the fit-for-duty data were acquired, and partly on the road, where the drivers sleepiness was assessed. A series of four measurements were conducted over a 24-h period during different stages of sleepiness. Two separate analyses were performed; a variance analysis and a feature selection followed by classification analysis. In the first analysis it was found that the SWP and several eye movement features involving anti-saccades, pro-saccades, smooth pursuit, pupillometry and fixation stability varied significantly with different stages of sleep deprivation. In the second analysis, a feature set was determined based on floating forward selection. The correlation coefficient between a linear combination of the acquired features and subjective sleepiness (Karolinska sleepiness scale, KSS) was found to be R = 0.73 and the correct classification rate of drivers who reached high levels of sleepiness (KSS andgt;= 8) in the subsequent driving session was 82.4% (sensitivity = 80.0%, specificity = 84.2% and AUC = 0.86). Future improvements of a fit-for-duty test should focus on how to account for individual differences and situational/contextual factors in the test, and whether it is possible to maintain high sensitive/specificity with a shorter test that can be used in a real-life environment, e.g. on professional drivers.

Place, publisher, year, edition, pages
Elsevier, 2013
Keywords
Fit-for-duty test, Eye movements, Driver sleepiness, Field study
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-90685 (URN)10.1016/j.trc.2012.07.008 (DOI)000315421300002 ()
Note

Funding Agencies|Swedish Transport Administration||VINNOVA, the Swedish Governmental Agency for Innovation Systems||

Available from: 2013-04-03 Created: 2013-04-03 Last updated: 2017-12-06
Rattfält, L., Ahlström, C., Eneling, M., Ragnemalm, B., Hult, P., Lindén, M. & Ask, P. (2009). A platform for physiological signals including an intelligent stethoscope. In: Jos Sloten, Pascal Verdonck, Marc Nyssen, Jens Haueisen (Ed.), 4th European Conference of the International Federation for Medical and Biological Engineering: ECIFMBE 2008 23–27 November 2008 Antwerp, Belgium. Paper presented at 4th European Conference of the International Federation for Medical and Biological Engineering (ECIFMBE), (pp. 1038-1041). Paper presented at 4th European Conference of the International Federation for Medical and Biological Engineering (ECIFMBE),. Springer Berlin/Heidelberg, 22
Open this publication in new window or tab >>A platform for physiological signals including an intelligent stethoscope
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2009 (English)In: 4th European Conference of the International Federation for Medical and Biological Engineering: ECIFMBE 2008 23–27 November 2008 Antwerp, Belgium / [ed] Jos Sloten, Pascal Verdonck, Marc Nyssen, Jens Haueisen, Springer Berlin/Heidelberg, 2009, Vol. 22, p. 1038-1041Chapter in book (Refereed)
Abstract [en]

We have developed a physiological signal platform where presently phonocardiographic (PCG) and electrocardiographic (ECG) signals can be acquired and on which our signal analysis techniques can be implemented. The platform can also be used to store patient data, to enable comparison over time and invoke distance consultation if necessary. Our studies so far indicate that with our signal analysis techniques of heart sounds we are able to separate normal subject from those with aortic stenosis and mitral insufficiency. Further we are able to identify the third heart sound. The platform is being tested in a primary health care setting.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2009
Series
IFMBE Proceedings, ISSN 1680-0737
Keywords
monitoring; distributed care; intelligent stethoscope
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:liu:diva-116925 (URN)10.1007/978-3-540-89208-3_247 (DOI)978-3-540-89207-6 (ISBN)
Conference
4th European Conference of the International Federation for Medical and Biological Engineering (ECIFMBE),
Note

4th European Conference of the International Federation for Medical and Biological Engineering (ECIFMBE), Antwerp, BELGIUM, NOV 23-27, 2008

Available from: 2015-04-09 Created: 2015-04-09 Last updated: 2016-08-30
Hurtig-Wennlof, A., Ahlström, C., Egerlid, R., Resare, M., Ask, P. & Rask, P. (2009). Heart sounds are altered by open cardiac surgery. Experimental and Clinical Cardiology, 14(2), 18-20
Open this publication in new window or tab >>Heart sounds are altered by open cardiac surgery
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2009 (English)In: Experimental and Clinical Cardiology, ISSN 1205-6626, Vol. 14, no 2, p. 18-20Article in journal (Refereed) Published
Abstract [en]

BACKGROUND AND OBJECTIVE: Patients have reported that they perceive their own heart sounds differently after open cardiac surgery than before the surgery. The present study was designed to investigate whether changes in heart sounds can be quantitatively measured. METHOD: Heart sounds were recorded from 57 patients undergoing coronary artery bypass graft (CABG) surgery and from a control group of 10 subjects. The so-called Hjorth descriptors and the main frequency peak were compared before and after surgery to determine whether the characteristics of the heart sounds had changed. RESULTS: At a group level, the first heart sound was found to be significantly different after CABG surgery. Generally, the heart sounds shifted toward a lower frequency after surgery in the CABG group. No significant changes were found in the control group. CONCLUSIONS: Heart sounds are altered after CABG surgery. The changes are objectively quantifiable and may also be subjectively perceived by the patients.

Keywords
Cardiac surgery; Counselling; Heart sound; Phonocardiography
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-53017 (URN)
Available from: 2010-01-14 Created: 2010-01-14 Last updated: 2010-01-14
Ljungvall, I., Ahlström, C., Hoglund, K., Hult, P., Kvart, C., Borgarelli, M., . . . Haggstrom , J. (2009). Use of signal analysis of heart sounds and murmurs to assess severity of mitral valve regurgitation attributable to myxomatous mitral valve disease in dogs. AMERICAN JOURNAL OF VETERINARY RESEARCH, 70(5), 604-613
Open this publication in new window or tab >>Use of signal analysis of heart sounds and murmurs to assess severity of mitral valve regurgitation attributable to myxomatous mitral valve disease in dogs
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2009 (English)In: AMERICAN JOURNAL OF VETERINARY RESEARCH, ISSN 0002-9645 , Vol. 70, no 5, p. 604-613Article in journal (Refereed) Published
Abstract [en]

Objective-To investigate use of signal analysis of heart sounds and murmurs in assessing severity of mitral valve regurgitation (mitral regurgitation [MR]) in dogs with myxomatous mitral valve disease (MMVD).

Animals-77 client-owned dogs.

Procedures-Cardiac sounds were recorded from dogs evaluated by use of auscultatory and echocardiographic classification systems. Signal analysis techniques were developed to extract 7 sound variables (first frequency peak, murmur energy ratio, murmur duration > 200 Hz, sample entropy and first minimum of the auto mutual information function of the murmurs, and energy ratios of the first heart sound [S1] and second heart sound [S2]).

Results-Significant associations were detected between severity of MR and all sound variables, except the energy ratio of S1. An increase in severity of MR resulted in greater contribution of higher frequencies, increased signal irregularity, and decreased energy ratio of S2. The optimal combination of variables for distinguishing dogs with high-intensity murmurs from other dogs was energy ratio of S2 and murmur duration > 200 Hz (sensitivity, 79%; specificity, 71%) by use of the auscultatory classification. By use of the echocardiographic classification, corresponding variables were auto mutual information, first frequency peak, and energy ratio of S2 (sensitivity, 88%; specificity, 82%).

Conclusions and Clinical Relevance-Most of the investigated sound variables were significantly associated with severity of MR, which indicated a powerful diagnostic potential for monitoring MMVD. Signal analysis techniques could be valuable for clinicians when performing risk assessment or determining whether special care and more extensive examinations are required.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-18291 (URN)10.2460/ajvr.70.5.604 (DOI)
Available from: 2009-05-17 Created: 2009-05-15 Last updated: 2009-06-08
Ahlström, C., Länne, T., Ask, P. & Johansson, A. (2008). A method for accurate localization of the first heart sound and possible applications. Physiological Measurement, 29(3), 417-428
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, p. 417-428Article 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
Keywords
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
Ahlström, C., Höglund, K., Hult, P., Häggström, J., Kvart, C. & Ask, P. (2008). Assessing Aortic Stenosis using Sample Entropy of the Phonocardiographic Signal in Dogs. IEEE Transactions on Biomedical Engineering, 55(8), 2107-2109
Open this publication in new window or tab >>Assessing Aortic Stenosis using Sample Entropy of the Phonocardiographic Signal in Dogs
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2008 (English)In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 55, no 8, p. 2107-2109Article 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.

Keywords
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
Ljungvall, I., Ahlström, C., Höglund, K., Hult, P., Kvart, C., Borgarelli, M., . . . Häggström, J. (2008). 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
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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
Ahlström, C. (2008). Nonlinear phonocardiographic Signal Processing. (Doctoral dissertation). : Institutionen för medicinsk teknik
Open this publication in new window or tab >>Nonlinear phonocardiographic Signal Processing
2008 (English)Doctoral 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.

Place, publisher, year, edition, pages
Institutionen för medicinsk teknik, 2008. p. 213
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1168
Keywords
Signal analysis methods, computerized cardiac auscultation system, phonocardiographic (PCG) signal, mitral insufficiency (MI), time- and cost-saving
National Category
Medical Laboratory and Measurements Technologies
Identifiers
urn:nbn:se:liu:diva-11302 (URN)978-91-7393-947-8 (ISBN)
Public defence
2008-04-25, Elsa Brändströmsalen, Universitetssjukhuset, Linköping, 09:00 (English)
Opponent
Supervisors
Available from: 2008-03-20 Created: 2008-03-20 Last updated: 2009-04-21
Ahlström, C., Ask, P., Rask, P., Karlsson, J.-E., Nylander, E., Dahlström, U. & Hult, P. (2007). Assessment of Suspected Aortic Stenosis by Auto Mutual Information Analysis of Murmurs. In: Engineering in Medicine and Biology Society, 2007. EMBS 2007. Paper presented at 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), 22-26 August 2007, Lyon, France (pp. 1945-1948).
Open this publication in new window or tab >>Assessment of Suspected Aortic Stenosis by Auto Mutual Information Analysis of Murmurs
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2007 (English)In: Engineering in Medicine and Biology Society, 2007. EMBS 2007, 2007, p. 1945-1948Conference paper, Published 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.

Series
IEEE Engineering in Medicine and Biology Society. Conference Proceedings, ISSN 1557-170X
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38632 (URN)10.1109/IEMBS.2007.4352698 (DOI)45125 (Local ID)978-1-4244-0787-3 (ISBN)e-978-1-4244-0788-0 (ISBN)45125 (Archive number)45125 (OAI)
Conference
29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), 22-26 August 2007, Lyon, France
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-09-26Bibliographically approved
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