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  • 1.
    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, p. 1945-1948Conference 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.

  • 2.
    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, p. 2288-2291Conference 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.

  • 3.
    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, p. 1040-1043Conference 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.

  • 4.
    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, p. 688-691Conference 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

  • 5.
    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, p. 305-Conference paper (Refereed)
  • 6.
    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)
  • 7.
    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, p. 1666-1677Article 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.

  • 8.
    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, p. 66-66Conference paper (Other academic)
  • 9.
    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, p. 38-39Conference paper (Other academic)
  • 10.
    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, p. 2107-2109Article 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.

  • 11.
    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, p. 40-45Conference 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.

  • 12.
    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, p. 1054-1062Article 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.

  • 13.
    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, p. 812-815Conference 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.

  • 14.
    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, p. 812-815Article 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.

    Download full text (pdf)
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  • 15.
    Ask, Per
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Ekstrand, Kristina
    Katrineholm City, Sweden.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Lindén, Maria
    Mälardalen University, Västerås, Sweden.
    Pettersson, Nils-Erik
    Örebro County Council, Sweden.
    NovaMedTech - a regional program for supporting new medical technologies in personalized health care2012In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 177, p. 71-5Article in journal (Refereed)
    Abstract [en]

    NovaMedTech is an initiative funded from EU structural funds for supporting new medical technologies for personalized health care. It aims at bringing these technologies into clinical use and to the health care market. The program has participants from health care, industry and academia in East middle Sweden. The first three year period of the program was successful in terms of product concepts tried clinically, and number of products brought to a commercialization phase. Further, the program has led to a large number of scientific publications. Among projects supported, we can mention: Intelligent sensor networks; A digital pen to collect medical information about health status from patients; A web-based intelligent stethoscope; Methodologies to measure local blood flow and nutrition using optical techniques; Blood flow assessment from ankle pressure measurements; Technologies for pressure ulcer prevention; An IR thermometer for improved accuracy; A technique that identifies individuals prone to commit suicide among depressed patients; Detection of infectious disease using an electronic nose; Identification of the lactate threshold from breath; Obesity measurements using special software and MR camera; and An optical probe guided tumor resection. During the present three years period emphasis will be on entrepreneurial activities supporting the commercialization and bringing products to the market.

  • 16.
    Ask, Per
    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.
    Fjallbrant, T
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Bioacoustic techniques is applicable to primary health care2001In: PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: BUILDING NEW BRIDGES AT THE FRONTIERS OF ENGINEERING AND MEDICINE, 2001, Vol. 23, p. 1911-1914Conference paper (Refereed)
    Abstract [en]

    The stethoscope has been used diagnostically for nearly two hundred years to assess the heart function. We can envision the intelligent stethoscope which combines the advantages of the traditional instrument with advanced functionality for analysis of the signal and other information support. The bioacoustic technique is basically simple and robust and fits therefore into a scenario where investigations are performed in a distributed health care system as in primary health care or even home health care. We have focused on detection of respiratory sounds and third heart sounds. The later is performed with a new wavelet technique which makes it possible to automatically detect and identify the sounds and possibly relate them to myocardial insufficiency.

  • 17.
    Claesson, Fredrik
    et al.
    Flodafors Lego AB.
    Andersson, Roger
    Katrineholms kommun.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    CeMIDCARE - Kunskapscentrum för medicinsk teknik och innovationer inom distribuerad närvård.2006Conference paper (Other academic)
  • 18.
    Danbolt, Christina
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuroscience. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Clinical Pathology and Clinical Genetics.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Arts and Sciences.
    Grahn, Lita Tibbling
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Validation and characterization of the computerized laryngeal analyzer (CLA) technique.1999In: Dysphagia (New York. Print), ISSN 0179-051X, E-ISSN 1432-0460, Vol. 14, no 4, p. 191-195Article in journal (Refereed)
    Abstract [en]

    The aim of this study was to investigate the response characteristics of the Computerized Laryngeal Analyzer (CLA) and the validity of the noninvasive CLA method to detect swallowing-induced laryngeal elevation correctly. Two healthy adults and two experimental models were used in the study. The CLA technique identified all swallowing events but was unable to discriminate between swallowing and other movements of the tongue or the neck. The computer program produced a derivated response to a square wave signal. Stepwise bending increments of the sensor displayed a linear amplitude response. The degree of laryngeal elevation could not be estimated with the CLA technique, and it was not possible to draw any reliable conclusions from the recordings as to whether the larynx was moving upward or downward.

  • 19.
    Danbolt, Christina
    et al.
    Linköping University, Department of Neuroscience and Locomotion, Oto-Rhiono-Laryngology and Head & Neck Surgery. Linköping University, Faculty of Health Sciences.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Tibbling Grahn, Lita
    Linköping University, Department of Neuroscience and Locomotion, Oto-Rhiono-Laryngology and Head & Neck Surgery. Linköping University, Faculty of Health Sciences.
    Ask, Per
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Validation and characterization of the computerized laryngeal analyzer (CLA) technique1999In: Dysphagia (New York. Print), ISSN 0179-051X, E-ISSN 1432-0460, Vol. 14, no 4, p. 191-195Article in journal (Refereed)
    Abstract [en]

    The aim of this study was to investigate the response characteristics of the Computerized Laryngeal Analyzer (CLA) and the validity of the noninvasive CLA method to detect swallowing-induced laryngeal elevation correctly. Two healthy adults and two experimental models were used in the study. The CLA technique identified all swallowing events but was unable to discriminate between swallowing and other movements of the tongue or the neck. The computer program produced a derivated response to a square wave signal. Stepwise bending increments of the sensor displayed a linear amplitude response. The degree of laryngeal elevation could not be estimated with the CLA technique, and it was not possible to draw any reliable conclusions from the recordings as to whether the larynx was moving upward or downward.

  • 20.
    Eneling, Martin
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Wickström, M
    Linköping University, Department of Biomedical Engineering.
    Johansson, Anders
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Vätternrundan.  Fjärr-registrering av fysiologiska parametrar under idrottsutövning.2006Conference paper (Other academic)
  • 21.
    Gharebhaghi, Arash
    et al.
    Linköping University, Department of Biomedical Engineering.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Graphic User Interface for Heart Sound Signal Analysis2010Conference paper (Other academic)
  • 22.
    Gharehbaghi, Arash
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Dutoit, Thierry
    TCTS Lab,University of Mons, Belgium.
    Sepehri, Amir
    ICT research center, Amir Kabir University, Tehran, Iran.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Ask, Per
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    An Automatic Tool for Pediatric Heart Sounds SegmentationManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper, we present a novel algorithm for pediatric heart sound segmentation, incorporated into a graphical user interface. The algorithm employs both the Electrocardiogram (ECG) and Phonocardiogram (PCG) signals for an efficient segmentation under pathological circumstances.First, the ECG signal is invoked in order to determine the beginning and end points of each cardiac cycle by using wavelet transform technique. Then, first and second heart sounds within the cycles are identified over the PCG signal by paying attention to the spectral properties of the sounds. The algorithm is applied on 120 recordings of normal and pathological children, totally containing 1976 cardiac cycles. The accuracy of the segmentation algorithm is 97% for S1 and 94% for S2 identification while all the cardiac cycles are correctly determined.

  • 23. Hagström, Careline
    et al.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Intelligenta, robusta och trådlösa sensorer för hem- och primärvården.2004In: Svenska läkaresällskapets riksstämma, 2004, p. 24-27Conference paper (Other academic)
  • 24.
    Hoglund, K.
    et al.
    Höglund, K., Department of Anatomy and Physiology, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.
    Ahlström, Christer
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Haggstrom, J.
    Häggström, J., Department of Clinical Sciences, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Kvart, C.
    Department of Anatomy and Physiology, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, 750 07 Uppsala, Sweden.
    Time-frequency and complexity analyses for differentiation of physiologic murmurs from heart murmurs caused by aortic stenosis in boxers2007In: American Journal of Veterinary Research, ISSN 0002-9645, E-ISSN 1943-5681, Vol. 68, no 9, p. 962-969Article in journal (Refereed)
    Abstract [en]

    Objective - To investigate whether time-frequency and complexity analyses of heart murmurs can be used to differentiate physiologic murmurs from murmurs caused by aortic stenosis (AS) in Boxers. Animals - 27 Boxers with murmurs. Procedures - Dogs were evaluated via auscultation and echocardiography. Analyses of time-frequency properties (TFPs, ie, maximal murmur frequency and duration of murmur frequency > 200 Hz) and correlation dimension (T2) of murmurs were performed on phonocardiographic sound data. Time-frequency property and T2 analyses of low-intensity murmurs in 16 dogs without AS were performed at 7 weeks and 12 months of age. Additionally, TFP and T2 analyses were performed on data obtained from 11 adult AS-affected dogs with murmurs. Results - In dogs with low-intensity murmurs, TFP or T2 values at 7 weeks and 12 months did not differ significantly. For differentiation of physiologic murmurs from murmurs caused by mild AS, duration of murmur frequency > 200 Hz was useful and the combination assessment of duration of frequency > 200 Hz and T2 of the murmur had a sensitivity of 94% and a specificity of 82%. Maximal murmur frequency did not differentiate dogs with AS from those without AS. Conclusions and Clinical Relevance - Results suggested that assessment of the duration of murmur frequency > 200 Hz can be used to distinguish physiologic heart murmurs from murmurs caused by mild AS in Boxers. Combination of this analysis with T2 analysis may be a useful complementary method for diagnostic assessment of cardiovascular function in dogs.

  • 25.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Bioacoustic principles used in monitoring and diagnostic applications2002Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The idea behind this work is linked to the experience gained from the long use of the stethoscope, and to the fact that sound originating from the body is a mechanical fingerprint, reflecting the human body functions.

    The aims of this thesis have been to develop bioacoustic systems using modern medical signal processing in three applications. The first was to develop a method for monitor the respiration, the second was to develop a detection method for the third heart sound and, the third was to study a swallowing detection technique and look into the potential of bioacoustic development in this area.

    Respiratory monitoring is of vital importance in several clinical situations. A bioacoustic signal analysis approach has been developed for monitoring of respiration. This approach includes strategies to differentiate between inspiration and expiration. In two different patient groups, the method has managed to detect 98% of the respiratory cycles.

    The third heart sound has been found to be related to heart failure. A tailored wavelet technique has been developed fur detection of the third heart sound. The method has been used in children and in patients with heart failure. The wavelet metod detected 87% of the third heart sounds and only 2% were classified as false positive.

    An investigation of an existing method for swallowing detection, computerized laryngeal analyser (CLA), was performed toghether with a pilot study involving swallowing sounds for the detection. The CLA technique was found to be inadequate for swallowing detection. The bioacoustic approach showed promise for detection of swallows.

    We expect in the future that bioacoustics will be an important medical field, for diagnosis, monitoring, rehabilitation and education. The methods show potential for increased use, both in hospital and primary care.

    List of papers
    1. A bioacoustic method for timing of the different phases of the breathing cycle and monitoring of breathing frequency
    Open this publication in new window or tab >>A bioacoustic method for timing of the different phases of the breathing cycle and monitoring of breathing frequency
    2000 (English)In: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 22, no 6, p. 425-433Article in journal (Refereed) Published
    Abstract [en]

    It is well known that the flow of air through the trachea during respiration causes vibrations in the tissue near the trachea, which propagate to the surface of the body and can be picked up by a microphone placed on the throat over the trachea. Since the vibrations are a direct result of the airflow, accurate timing of inspiration and expiration is possible. This paper presents a signal analysis solution for automated monitoring of breathing and calculation of the breathing frequency. The signal analysis approach uses tracheal sound variables in the time and frequency domains, as well as the characteristics of the disturbances that can be used to discriminate tracheal sound from noise. One problem associated with the bioacoustic method is its sensitivity for acoustic disturbances, because the microphone tends to pick up all vibrations, independent of their origin. A signal processing method was developed that makes the bioacoustic method clinically useful in a broad variety of situations, for example in intensive care and during certain heart examinations, where information about both the precise timing and the phases of breathing is crucial.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-26691 (URN)10.1016/S1350-4533(00)00050-3 (DOI)11279 (Local ID)11279 (Archive number)11279 (OAI)
    Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2017-12-13
    2. An improved bioacoustic method for monitoring of respiration
    Open this publication in new window or tab >>An improved bioacoustic method for monitoring of respiration
    Show others...
    2004 (English)In: Technology and Health Care, ISSN 0928-7329, E-ISSN 1878-7401, Vol. 12, no 4, p. 323-332Article in journal (Refereed) Published
    Abstract [en]

    Reliable monitoring of respiration plays an important role in a broad spectrum of applications. Today, there are several methods for monitoring respiration, but none of them has proved to be satisfactory in all respects. We have recently developed a bioacoustic method that can accurately time respiration from tracheal sounds. The aim of this study is to tailor this bioacoustic method for monitoring purposes by introducing dedicated signal processing. The method was developed on a material of ten patients and then tested in another ten patients treated in an intensive care unit. By studying the differences in the variation of the spectral content between the different phases of respiration, the described method can distinguish between inspiration and expiration and can extract respiration frequency, and respiration pause periods. The system detected 98% of the inspirations and 99% of the expirations. This method for respiration monitoring has the advantage of being simple, robust and the sensor does not need to be placed closed to the face. A commercial heart microphone was used and we anticipate that further improvement in performance can be achieved trough optimization of sensor design.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-22249 (URN)1416 (Local ID)1416 (Archive number)1416 (OAI)
    Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2017-12-13
    3. Detection of the third heart sound using a tailored wavelet approach
    Open this publication in new window or tab >>Detection of the third heart sound using a tailored wavelet approach
    2004 (English)In: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 42, no 2, p. 253-258Article in journal (Refereed) Published
    Abstract [en]

    The third heart sound is normally heard during auscultation of younger individuals but disappears with increasing age. However, this sound can appear in patients with heart failure and is thus of potential diagnostic use in these patients. Auscultation of the heart involves a high degree of subjectivity. Furthermore, the third heart sound has low amplitude and a low-frequency content compared with the first and second heart sounds, which makes it difficult for the human ear to detect this sound. It is our belief that it would be of great help to the physician to receive computer-based support through an intelligent stethoscope, to determine whether a third heart sound is present or not. A precise, accurate and low-cost instrument of this kind would potentially provide objective means for the detection of early heart failure, and could even be used in primary health care. In the first step, phonocardiograms from ten children, all known to have a third heart sound, were analysed, to provide knowledge about the sound features without interference from pathological sounds. Using this knowledge, a tailored wavelet analysis procedure was developed to identify the third heart sound automatically, a technique that was shown to be superior to Fourier transform techniques. In the second step, the method was applied to phonocardiograms from heart patients known to have heart failure. The features of the third heart sound in children and of that in patients were shown to be similar. This resulted in a method for the automatic detection of third heart sounds. The method was able to detect third heart sounds effectively (90%), with a low false detection rate (3.7%), which supports its clinical use. The detection rate was almost equal in both the children and patient groups. The method is therefore capable of detecting, not only distinct and clearly visible/audible third heart sounds found in children, but also third heart sounds in phonocardiograms from patients suffering from heart failure.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-22211 (URN)10.1007/BF02344639 (DOI)1369 (Local ID)1369 (Archive number)1369 (OAI)
    Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2017-12-13
    4. Bioacoustic detection of the third heart sound: a preliminary patient study
    Open this publication in new window or tab >>Bioacoustic detection of the third heart sound: a preliminary patient study
    Show others...
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Body sounds are related to mechanical processes in the body. Thus, the heart can be seen as a sound generator and the heart sounds as mechanical fingerprints of myocardial function.

    This sound normally occurs in children but disappear with maturation. The sound can also appear in patients with heart failure. The sound is characterized by its low amplitude and low frequency content, which makes it difficult to identify by the use of the traditional stethoscope.

    We have recently developed a wavelet based method for detection of the third heart sound. Our intention with this study was to investigate if a third heart sound could be identified in patients with a diagnosis of heart failure attending the heart failure clinic using this detection method. It was also our intention to compare our method with auscultation using a conventional phonocardiography, and characterizing the patients with echocardiography.

    Using the wavelet method (study 1), 87% of the third heart sounds that were identified from the recordings (with the visual method as a reference) were detected, 12% were missed and 2% were false positive. In study 2, the wavelet detection method identified all (100%) of patients with identified third heart sound and regular phonocardiography identified 2 (13%) of the subjects.

    Keywords
    Noninvasive, Third heart sound, Wavelet, Heart failure, Heart sounds, Phonocardiogram, Auscultation, Echocardiography
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-86738 (URN)
    Available from: 2013-01-02 Created: 2013-01-02 Last updated: 2013-09-26
    5. Validation and characterization of the computerized laryngeal analyzer (CLA) technique
    Open this publication in new window or tab >>Validation and characterization of the computerized laryngeal analyzer (CLA) technique
    1999 (English)In: Dysphagia (New York. Print), ISSN 0179-051X, E-ISSN 1432-0460, Vol. 14, no 4, p. 191-195Article in journal (Refereed) Published
    Abstract [en]

    The aim of this study was to investigate the response characteristics of the Computerized Laryngeal Analyzer (CLA) and the validity of the noninvasive CLA method to detect swallowing-induced laryngeal elevation correctly. Two healthy adults and two experimental models were used in the study. The CLA technique identified all swallowing events but was unable to discriminate between swallowing and other movements of the tongue or the neck. The computer program produced a derivated response to a square wave signal. Stepwise bending increments of the sensor displayed a linear amplitude response. The degree of laryngeal elevation could not be estimated with the CLA technique, and it was not possible to draw any reliable conclusions from the recordings as to whether the larynx was moving upward or downward.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-32932 (URN)10.1007/PL00009605 (DOI)18883 (Local ID)18883 (Archive number)18883 (OAI)
    Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2017-12-13
  • 26.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    NovaMedTech2009Conference paper (Other academic)
  • 27.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    NovaMedTech – Innovationer för morgondagens vård genom samverkan med vård, akademi och industri2010Conference paper (Other (popular science, discussion, etc.))
    Abstract [sv]

    Med en kraftig ökning av andelen äldre i befolkningen ställs allt större krav på sjukvården. Ny medicinsk teknik utgör en möjlig väg att göra vården effektivare. Utgående från detta är NovaMedTech en innovativ miljö som stöds av EUs Strukturfond och som skall bidra till att stärka ny utveckling av medicinsk teknik inom regionen Östra Mellansverige dvs de fyra länen Sörmland, Västmanland, Örebro och Östergötland. I programmet tas ett samlat grepp genom att vård, akademi och industri samverkar mellan de olika länen. Satsningen stärks av länens kompletterande styrkor.

    NovaMedTech satsar genom ekonomiskt stöd från EU-strukturfondsprogram via Tillväxtverket på de två olika produktområden: Medicinsk teknik för distribuerad vård och personlig hälsa och Medicinsk teknik för bildbaserad diagnostik och terapi. Vi stöder ett 30-tal konkreta projekt mot klinisk testning och kommersialisering av produkter och tjänster.

    Genom NovaMedTech utvecklas även en innovativ miljö där ett brett nätverk har skapats och där dess aktörer har givits möjlighet att samverka, utbyta erfarenheter, identifiera nya idéer mm. Viktiga framgångsfaktorer för NovaMedTech har varit en god regional förankring, en mångfald av aktörer inom vård, akademi och näringsliv, att satsningen bygger på redan befintliga utvecklingsstrukturer i form av nätverk, innovationsstöd, inkubatorverksamhet, nyföretagarstöd, såddfinansiering, hälsoekonomisk analys och entreprenörskapssatsningar mm, samt att NovaMedTech har en stark koppling till näringslivet.

    Produktområdet Medicinsk teknik för distribuerad vård och personlig hälsa handlar om teknik för fysiologisk övervakning av patienter i hemmiljö samt teknik för diagnostik inom närvård/primärvård. I framtiden bör patientinformation och mätdata överföras istället för att patienter transporteras. Lösningar kan innefatta teknik för ”point of care”-diagnostik inom närvård/primärvård. Med medicinsk teknik för personlig hälsa avser vi monitorering av patienter med risk för att utveckla en viss sjukdom eller som har en kronisk sjukdom. Bland delprojekt som vi arbetar med kan nämnas: Tekniska metoder för att patienter kan bo kvar i sin hemmiljö, Informationsteknik för att underlätta patientens vardagsbestyr, Mät- och kommunikationsplattformar för fysiologiska signaler/labprover, Trådlös informationsöverföring, Journalsystem för distribuerad vård samt Monitorering/övervakning av fysiologiska parameter kopplade till kroniska sjudomar

    Medicinsk teknik för bildbaserad diagnostik och terapi blir allt viktigare i en högteknologisk sjukvård. Vi arbetar med att vidareutveckla tekniken framför allt genom att på nya sätt processa bildinformationen. Exempel på delprojket som vi driver är: Avbildning av vävnad med hjälp av mikrovågstomografi, Utveckling av ny MR-teknik för hjärtundersökning, Avancerad bildbehandling av datortomografibilder och mikroskopbilder och Medicinska bilder för att simulera och styra behandling.

    Projektet har pågått i ca 2 år och bland hittills uppnådda resultat kan nämnas ca 60 identifierade produktidéer, att 20 produktidéer har tagits till klinisk evaluering, att 9 prototyper har kommit till en kommersialiseringsfas och att 3 nya företag hittills har bildats genom NovaMedTechs medverkan.

  • 28.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    NovaMedTech. Nya Medicintekniska Produkter och tjänster för Morgondagens Vård och Omsorg.2008Conference paper (Other academic)
  • 29.
    Hult, Peter
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Ahlström, Christer
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Rattfält, Linda
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Hagström, Caroline
    Medicinsk teknik Örebro universitetssjukhus.
    Pettersson, Nils-Erik
    Medicinsk teknik Örebro universitetssjukhus.
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    The intelligent stethoscope as a tool in modern health care2005In: Nordic Baltic Conference Biomedical Engineering and Medical Physics,2005, Umeå: IFMBE , 2005, p. 79-Conference paper (Refereed)
  • 30.
    Hult, Peter
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Ahlström, Christer
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Rattfält, Linda
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Hagström, Cecilia
    Örebro University Hospital .
    Pettersson, Nils-Erik
    Örebro University Hospital .
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    The intelligent stethoscope2005In: EMBEC05,2005, Prag: IFMBE , 2005Conference paper (Refereed)
  • 31.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering.
    Alod, Tanja
    Linköping University, Department of Biomedical Engineering.
    Rattfält, Linda
    Linköping University, Department of Biomedical Engineering.
    Textile electrodes - An alternative as ECG electrodes in home health care?2006Conference paper (Other academic)
    Abstract [en]

    The use of electrocardiogram (ECG) is a well known and widely used method. However, when the home health care is expanding, new demands for ECG equipment is seen. It would be desirable if electrodes would be more comfortable to use, especially for long-time registrations. The contact between electrodes and skin becomes worse with time and electrodes can also irritate the skin. With textile technology of today, yarns can be created with leading materials [1]. Thin threads of metal are spun into yarn and can be used for weaving or knitting fabrics. These fabrics can be used as electrodes for ECG registration, with the advantage of textile properties. By integrating such electrodes in clothes, the electrodes could become more wearable and more suitable for some ECG registrations [2, 3, 4] . The difficulty of distinguishing QRS-complexes will be used for studying signals from textile electrodes. In this study, three different textile sensors was compared in order to investigate influences in the ECG signal caused by material, size or structure. Such influences could contaminate the signal with different types of noise and make it difficult to distinguish the characteristics of the ECG [5].

  • 32.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Ask, Per
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Fjällbrant, Tore
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Detection of the third heart sound using a tailored wavelet approach2004In: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 42, no 2, p. 253-258Article in journal (Refereed)
    Abstract [en]

    The third heart sound is normally heard during auscultation of younger individuals but disappears with increasing age. However, this sound can appear in patients with heart failure and is thus of potential diagnostic use in these patients. Auscultation of the heart involves a high degree of subjectivity. Furthermore, the third heart sound has low amplitude and a low-frequency content compared with the first and second heart sounds, which makes it difficult for the human ear to detect this sound. It is our belief that it would be of great help to the physician to receive computer-based support through an intelligent stethoscope, to determine whether a third heart sound is present or not. A precise, accurate and low-cost instrument of this kind would potentially provide objective means for the detection of early heart failure, and could even be used in primary health care. In the first step, phonocardiograms from ten children, all known to have a third heart sound, were analysed, to provide knowledge about the sound features without interference from pathological sounds. Using this knowledge, a tailored wavelet analysis procedure was developed to identify the third heart sound automatically, a technique that was shown to be superior to Fourier transform techniques. In the second step, the method was applied to phonocardiograms from heart patients known to have heart failure. The features of the third heart sound in children and of that in patients were shown to be similar. This resulted in a method for the automatic detection of third heart sounds. The method was able to detect third heart sounds effectively (90%), with a low false detection rate (3.7%), which supports its clinical use. The detection rate was almost equal in both the children and patient groups. The method is therefore capable of detecting, not only distinct and clearly visible/audible third heart sounds found in children, but also third heart sounds in phonocardiograms from patients suffering from heart failure.

  • 33.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Ask, Per
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    A bioacoustic method for timing of the different phases of the breathing cycle and monitoring of breathing frequency2000In: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 22, no 6, p. 425-433Article in journal (Refereed)
    Abstract [en]

    It is well known that the flow of air through the trachea during respiration causes vibrations in the tissue near the trachea, which propagate to the surface of the body and can be picked up by a microphone placed on the throat over the trachea. Since the vibrations are a direct result of the airflow, accurate timing of inspiration and expiration is possible. This paper presents a signal analysis solution for automated monitoring of breathing and calculation of the breathing frequency. The signal analysis approach uses tracheal sound variables in the time and frequency domains, as well as the characteristics of the disturbances that can be used to discriminate tracheal sound from noise. One problem associated with the bioacoustic method is its sensitivity for acoustic disturbances, because the microphone tends to pick up all vibrations, independent of their origin. A signal processing method was developed that makes the bioacoustic method clinically useful in a broad variety of situations, for example in intensive care and during certain heart examinations, where information about both the precise timing and the phases of breathing is crucial.

  • 34.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Fjällbrant, T.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Hildén, Katrin
    Linköping University, Department of Medicine and Care. Linköping University, Faculty of Health Sciences.
    Dahlström, Ulf
    Linköping University, Department of Medicine and Care. Linköping University, Faculty of Health Sciences.
    Wranne, Bengt
    Linköping University, Department of Medicine and Care. Linköping University, Faculty of Health Sciences.
    Ask, Per
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Bioacoustic detection of the third heart sound: a preliminary patient studyManuscript (preprint) (Other academic)
    Abstract [en]

    Body sounds are related to mechanical processes in the body. Thus, the heart can be seen as a sound generator and the heart sounds as mechanical fingerprints of myocardial function.

    This sound normally occurs in children but disappear with maturation. The sound can also appear in patients with heart failure. The sound is characterized by its low amplitude and low frequency content, which makes it difficult to identify by the use of the traditional stethoscope.

    We have recently developed a wavelet based method for detection of the third heart sound. Our intention with this study was to investigate if a third heart sound could be identified in patients with a diagnosis of heart failure attending the heart failure clinic using this detection method. It was also our intention to compare our method with auscultation using a conventional phonocardiography, and characterizing the patients with echocardiography.

    Using the wavelet method (study 1), 87% of the third heart sounds that were identified from the recordings (with the visual method as a reference) were detected, 12% were missed and 2% were false positive. In study 2, the wavelet detection method identified all (100%) of patients with identified third heart sound and regular phonocardiography identified 2 (13%) of the subjects.

  • 35.
    Hult, Peter
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Fjällbrant, T
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Detection of the third heart sound using a tailored wavelet approach.2004In: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 42, no 2, p. 253-258Article in journal (Refereed)
    Abstract [en]

    The third heart sound is normally heard during auscultation of younger individuals but disappears with increasing age. However, this sound can appear in patients with heart failure and is thus of potential diagnostic use in these patients. Auscultation of the heart involves a high degree of subjectivity. Furthermore, the third heart sound has low amplitude and a low-frequency content compared with the first and second heart sounds, which makes it difficult for the human ear to detect this sound. It is our belief that it would be of great help to the physician to receive computer-based support through an intelligent stethoscope, to determine whether a third heart sound is present or not. A precise, accurate and low-cost instrument of this kind would potentially provide objective means for the detection of early heart failure, and could even be used in primary health care. In the first step, phonocardiograms from ten children, all known to have a third heart sound, were analysed, to provide knowledge about the sound features without interference from pathological sounds. Using this knowledge, a tailored wavelet analysis procedure was developed to identify the third heart sound automatically, a technique that was shown to be superior to Fourier transform techniques. In the second step, the method was applied to phonocardiograms from heart patients known to have heart failure. The features of the third heart sound in children and of that in patients were shown to be similar. This resulted in a method for the automatic detection of third heart sounds. The method was able to detect third heart sounds effectively (90%), with a low false detection rate (3.7%), which supports its clinical use. The detection rate was almost equal in both the children and patient groups. The method is therefore capable of detecting, not only distinct and clearly visible/audible third heart sounds found in children, but also third heart sounds in phonocardiograms from patients suffering from heart failure.

  • 36.
    Hult, Peter
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Fjällbrant, Tore
    Dahle, S
    Danielsson, P
    Ask, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    A method for respiration in monitoring by use of a bioacoustic signal2000In: Medical signal and information processing MEDSIP,2000, IET , 2000, p. 22-25Conference paper (Refereed)
    Abstract [en]

    The sound that generates during the act of respiration can be picked up by a bioacoustic sensor, a specially designed microphone. The aim of the work was to describe a method for monitoring of respiration and where the start and stop of the respiration phases can be timed accurately. A method is presented where the time position of the different respiration phases can be determined by a time resolution of 51 ms. A microphone applied over the trachea and the features of the respiration sounds frequency content was used for the development of the method

  • 37.
    Hult, Peter
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Fjällbrant, Tore
    Hildén, Karin
    Linköping University, Department of Medicine and Care. Linköping University, Faculty of Health Sciences.
    Dahlström, Ulf
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Cardiology. Östergötlands Läns Landsting, Heart Centre, Department of Cardiology.
    Wranne, Bengt
    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.
    Detection of the third heart sound using a tailored wavelet approach: Method verification2005In: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 43, no 2, p. 212-217Article in journal (Refereed)
    Abstract [en]

    Heart sounds can be considered as mechanical fingerprints of myocardial function. The third heart sound normally occurs in children but disappears with maturation. The sound can also appear in patients with heart failure. The sound is characterised by its low-amplitude and low-frequency content, which makes it difficult to identify by the traditional use of the stethoscope. A wavelet-based method has recently been developed for detection of the third heart sound. This study investigated if the third heart sound could be identified in patients with heart failure using this detection method. The method was also compared with auscultation using conventional phonocardiography and with characterisation of the patients with echocardiography. In the first study, 87% of the third heart sounds were detected using the wavelet method, 12% were missed, and 6% were false positive. In study 2, the wavelet-detection method identified 87% of the patients using the third heart sound, and regular phonocardiography identified two (25%) of the subjects. © IFMBE: 2005.

  • 38.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Fjällbrant, Tore
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Engdahl, O.
    Linköping University, Department of Medical and Health Sciences, Anesthesiology. Linköping University, Faculty of Health Sciences.
    Ask, Per
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    An improved bioacoustic method for monitoring of respiration2004In: Technology and Health Care, ISSN 0928-7329, E-ISSN 1878-7401, Vol. 12, no 4, p. 323-332Article in journal (Refereed)
    Abstract [en]

    Reliable monitoring of respiration plays an important role in a broad spectrum of applications. Today, there are several methods for monitoring respiration, but none of them has proved to be satisfactory in all respects. We have recently developed a bioacoustic method that can accurately time respiration from tracheal sounds. The aim of this study is to tailor this bioacoustic method for monitoring purposes by introducing dedicated signal processing. The method was developed on a material of ten patients and then tested in another ten patients treated in an intensive care unit. By studying the differences in the variation of the spectral content between the different phases of respiration, the described method can distinguish between inspiration and expiration and can extract respiration frequency, and respiration pause periods. The system detected 98% of the inspirations and 99% of the expirations. This method for respiration monitoring has the advantage of being simple, robust and the sensor does not need to be placed closed to the face. A commercial heart microphone was used and we anticipate that further improvement in performance can be achieved trough optimization of sensor design.

  • 39.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Lindén, Maria
    Mälardalens högskola.
    Distribuerad vård – Möjligheter, behov och svårigheter - En diskussion om den framtida vården.2007Conference paper (Other academic)
  • 40.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Lindén, Maria
    Institutionen för datavetenskap och elektronik, Mälardalens högskola, Västerås, Sverige.
    Rattfält, Linda
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Distribuerad vård - Möjligheter, Behov och svårigheter.2006Conference paper (Other academic)
  • 41.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Oscarsson, Marcus
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Rattfält, Linda
    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.
    A platform for patient monitoring in home health care including an interpretation tool for heart failure patients2009In: WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, VOL 25, PT 5, ISSN 1680-0737, Vol. 25, no 5, p. 157-160Article in journal (Refereed)
    Abstract [en]

    About 2% of the population suffer from heart failure, which is a disease associated with high mortality. We have developed a measurement platform including an interpretation tool for heart failure patients where physiological signals can be acquired and on which 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. In this platform, we have implemented a tool for interpretation support of the data measured from the patient. This tool are intended for use in home health care as an aid for monitoring and follow up heart failure patients.

  • 42.
    Hult, Peter
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Arts and Sciences.
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    A bioacoustic method for timing of the different phases of the breathing cycle and monitoring of breathing frequency.2000In: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 22, no 6, p. 425-433Article in journal (Refereed)
    Abstract [en]

    It is well known that the flow of air through the trachea during respiration causes vibrations in the tissue near the trachea, which propagate to the surface of the body and can be picked up by a microphone placed on the throat over the trachea. Since the vibrations are a direct result of the airflow, accurate timing of inspiration and expiration is possible. This paper presents a signal analysis solution for automated monitoring of breathing and calculation of the breathing frequency. The signal analysis approach uses tracheal sound variables in the time and frequency domains, as well as the characteristics of the disturbances that can be used to discriminate tracheal sound from noise. One problem associated with the bioacoustic method is its sensitivity for acoustic disturbances, because the microphone tends to pick up all vibrations, independent of their origin. A signal processing method was developed that makes the bioacoustic method clinically useful in a broad variety of situations, for example in intensive care and during certain heart examinations, where information about both the precise timing and the phases of breathing is crucial.

  • 43.
    Ljungvall, Ingrid
    et al.
    Swedish University of Agriculture Science.
    Ahlström, Christer
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Hoglund, Katja
    Swedish University of Agriculture Science.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Kvart, Clarence
    Swedish University of Agriculture Science.
    Borgarelli, Michele
    Kansas State University.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Haggstrom , Jens
    Swedish University of Agriculture Science.
    Use of signal analysis of heart sounds and murmurs to assess severity of mitral valve regurgitation attributable to myxomatous mitral valve disease in dogs2009In: AMERICAN JOURNAL OF VETERINARY RESEARCH, ISSN 0002-9645 , Vol. 70, no 5, p. 604-613Article in journal (Refereed)
    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.

  • 44.
    Olsson, Linda
    et al.
    Linköping University, Department of Biomedical Engineering.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering.
    Kan bedömningen av hjärtsviktspatienter underlättas genom införandet av avancerade tekniska system för analys och tolkningsstöd?2007Conference paper (Other academic)
    Abstract [sv]

    Sensorsystemet har många fördelar. Det är användarvänligt då det inte krävs att användaren utför kalibreringar och all mätning går att automatisera. Då blodprover inte behövs minimeras smittorisk och utövaren behöver inte stanna för att ta blodprover. Då systemet går att bygga bärbart och förhållandevis kostnadseffektivt har det fördelen att det går att använda i den aktuella idrotten så ofta idrottaren själv behöver.

  • 45.
    Pettersson, Nils-Erik
    et al.
    Örebro läns landsting.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Ekstrand, Kristina
    Katrineholms kommun.
    Hult, peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Lindén, Maria
    Mälardalen University Sweden.
    NovaMedTech – En satsning på att ny medicinsk teknik i Östra Mellansverige2010Conference paper (Other academic)
  • 46.
    Rattfält, Linda
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Ahlström, Christer
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Berglin, Lena
    The Swedish School of Textiles, University College of Borås, Borås, Sweden.
    Lindén, Maria
    Dept. of Computer Science and Electronics, Mälardalen University, Västerås, Sweden.
    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.
    Wiklund, Urban
    Dept. of Biomedical Engineering & Informatics, Umeå University Hospital, Umeå, Sweden.
    A Canonical correlation approach to heart beat detection in textile ECG measurements2006In: IET 3rd International Conference On Advances in Medical, Signal and Information Processing, 2006. MEDSIP 2006, IEEE , 2006, p. 1-4Conference paper (Refereed)
    Abstract [en]

    Research in textile sensors has lead to new ways to measure electrocardiograms (ECG). However, additional disturbances from e.g. muscular noise and high skin-electrode impedances often result in poor signal quality. The paper contains a simple application of canonical correlation analysis (CCA) on multi channel ECG signals recorded with textile electrodes. Using CCA to solve the blind source separation (BSS) problem, we intend to separate the ECG signal from the various noise sources. The method (CCABSS) was compared to simple averaging of the ECG channels and to the independent component analysis method (ICA). A heart beat detector was used to evaluate the signal quality. Results show that the signal was completely lost while simulating various noise in 33%, 17% and 7% of the cases for averaging, ICA and CCA, respectively.

  • 47.
    Rattfält, Linda
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology. Biomedical Engineering, Örebro County Council, Örebro, Sweden.
    Ahlström, Christer
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology. Biomedical Engineering, Örebro County Council, Örebro, Sweden.
    Eneling, Martin
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Ragnemalm, Bengt
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements. Biomedical Engineering, Örebro County Council, Örebro, Sweden.
    Lindén, M.
    Intelligent Sensor Systems, Mälardalen University, Västerås, Sweden.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology. Biomedical Engineering, Örebro County Council, Örebro, Sweden.
    A platform for physiological signals including an intelligent stethoscope2009In: 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.

  • 48.
    Rattfält, Linda
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Alod, Tanja
    Hult, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Den textila elektrodens utformning - En studie i hur designparametrar inverkar på signalkvaliteten i EKG-mätningar2006In: Medicinteknikdagarna 06,2006, 2006Conference paper (Other academic)
  • 49.
    Rattfält, Linda
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    Alod, Tanja
    Linköping University, Department of Biomedical Engineering.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, Faculty of Science & Engineering.
    The Textile Electrode Configuration - How signal quality in ECG-measurements is affected by design parameters. (Poster)2006Conference paper (Other academic)
  • 50.
    Rattfält, Linda
    et al.
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Chedid, Michel
    Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.
    Hult, Peter
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Lindén, Maria
    Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation. Linköping University, The Institute of Technology.
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Electrical Properties of Textile Electrodes2007In: Engineering in Medicine and Biology Society, 2007. EMBS 2007, IEEE , 2007, p. 5735-5738Conference paper (Refereed)
    Abstract [en]

    In this study we aim to explain the behavior of textile electrodes due to their construction techniques. Three textile electrodes were tested for electrode impedance and polarization potentials. The multifilament yarn (A) is favorable for its low thread resistance. Although, when knitted into electrodes, the staple fiber yarn (B) showed a comparable and satisfiable electrode impedance. The multifilament yarn had however a lower polarization potential drift then the other specimens. The monofilament yarn (C) had high electrode impedance and varying mean polarization potentials due to its conductive material and small contact area with the skin.

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