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Ask, Per
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Gharehbaghi, A., Borga, M., Janerot Sjöberg, B. & Per, A. (2015). A novel method for discrimination between innocent and pathological heart murmurs. Medical Engineering and Physics, 37(7), 674-682.
Open this publication in new window or tab >>A novel method for discrimination between innocent and pathological heart murmurs
2015 (English)In: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 37, no 7, 674-682 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel method for discrimination between innocent and pathological murmurs using the growing time support vector machine (GTSVM). The proposed method is tailored for characterizing innocent murmurs (IM) by putting more emphasis on the early parts of the signal as IMs are often heard in early systolic phase. Individuals with mild to severe aortic stenosis (AS) and IM are the two groups subjected to analysis, taking the normal individuals with no murmur (NM) as the control group. The AS is selected due to the similarity of its murmur to IM, particularly in mild cases. To investigate the effect of the growing time windows, the performance of the GTSVM is compared to that of a conventional support vector machine (SVM), using repeated random sub-sampling method. The mean value of the classification rate/sensitivity is found to be 88%/86% for the GTSVM and 84%/83% for the SVM. The statistical evaluations show that the GTSVM significantly improves performance of the classification as compared to the SVM.

Place, publisher, year, edition, pages
Elsevier, 2015
Keyword
Growing-time support vector machine, support vector machine, phonocardiogram signal, heart murmurs, innocent murmurs.
National Category
Medical Engineering
Identifiers
urn:nbn:se:liu:diva-117825 (URN)10.1016/j.medengphy.2015.04.013 (DOI)000357354400007 ()26003286 (PubMedID)
Note

At the time for thesis presentation publication was in status: Manuscript

Available from: 2015-05-08 Created: 2015-05-08 Last updated: 2017-12-04Bibliographically approved
Gharehbaghi, A., Ask, P., Lindèn, M. & Babic, A. (2015). A Novel Model for Screening Aortic Stenosis Using Phonocardiogram. In: Henrik Mindedal and Mikael Persson (Ed.), 16th Nordic-Baltic Conference on Biomedical Engineering: . Paper presented at 16th Nordic-Baltic Conference on Biomedical Engineering, 16. NBC & 10. MTD 2014 joint conferences. October 14-16, 2014, Gothenburg, Sweden (pp. 48-51). Springer Science Business Media.
Open this publication in new window or tab >>A Novel Model for Screening Aortic Stenosis Using Phonocardiogram
2015 (English)In: 16th Nordic-Baltic Conference on Biomedical Engineering / [ed] Henrik Mindedal and Mikael Persson, Springer Science Business Media , 2015, 48-51 p.Conference paper (Refereed)
Abstract [en]

This study presents an algorithm for screening aortic stenosis, based on heart sound signal processing. It benefits from an artificial intelligent-based (AI-based) model using a multi-layer perceptron neural network. The AI-based model learns disease related murmurs using non-stationary features of the murmurs. Performance of the model is statistically evaluated using two different databases, one of children and the other of elderly volunteers with normal heart condition and aortic stenosis. Results showed a 95% confidence interval of the high accuracy/sensitivity (84.1%-86.0%)/(86.0%-88.4%) thus exhibiting a superior performance to a cardiologist who relies on the conventional auscultation. The study suggests including the heart sound signal in the clinical decision making due to its potential to improve the screening accuracy.

Place, publisher, year, edition, pages
Springer Science Business Media, 2015
Series
IFMBE Proceedings, ISSN 1680-0737 ; 48
Keyword
Aortic stenosis, phonocardiography, heart sound, heart murmurs
National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:liu:diva-112774 (URN)10.1007/978-3-319-12967-9_13 (DOI)000347893000013 ()978-3-319-12966-2 (ISBN)978-3-319-12967-9 (ISBN)
Conference
16th Nordic-Baltic Conference on Biomedical Engineering, 16. NBC & 10. MTD 2014 joint conferences. October 14-16, 2014, Gothenburg, Sweden
Available from: 2014-12-15 Created: 2014-12-15 Last updated: 2017-07-13Bibliographically approved
Gharehbaghi, A., Ask, P. & Babic, A. (2015). A pattern recognition framework for detecting dynamic changes on cyclic time series. Pattern Recognition, 48(3), 696-708.
Open this publication in new window or tab >>A pattern recognition framework for detecting dynamic changes on cyclic time series
2015 (English)In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 48, no 3, 696-708 p.Article in journal (Refereed) Published
Abstract [en]

This paper proposes a framework for binary classification of the time series with cyclic characteristics. The framework presents an iterative algorithm for learning the cyclic characteristics by introducing the discriminative frequency bands (DFBs) using the discriminant analysis along with k-means clustering method. The DFBs are employed by a hybrid model for learning dynamic characteristics of the time series within the cycles, using statistical and structural machine learning techniques. The framework offers a systematic procedure for finding the optimal design parameters associated with the hybrid model. The proposed  model is optimized to detect the changes of the heart sound recordings (HSRs) related to aortic stenosis. Experimental results show that the proposed framework provides efficient tools for classification of the HSRs based on the heart murmurs. It is also evidenced that the hybrid model, proposed by the framework, substantially improves the classification performance when it comes to detection of the heart disease.

Place, publisher, year, edition, pages
Elsevier, 2015
Keyword
Hybrid model, cyclic time series, time series, phonocardiogram, systolic murmurs
National Category
Biomedical Laboratory Science/Technology Medical Biotechnology
Identifiers
urn:nbn:se:liu:diva-110177 (URN)10.1016/j.patcog.2014.08.017 (DOI)000347747000008 ()
Available from: 2014-09-04 Created: 2014-09-04 Last updated: 2017-12-05Bibliographically approved
Wandel, B., Pettersson, N.-E. & Ask, P. (2015). Certification of Clinical Engineers in Sweden. In: : . Paper presented at 6th European Conference of the International Federation for Medical and Biological Engineering (MBEC) (pp. 961-963). , 45.
Open this publication in new window or tab >>Certification of Clinical Engineers in Sweden
2015 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The Swedish Society for Biomedical Engineering and Physics has certified clinical engineers since 1994. The certification is performed at two levels: Master of Science and Bachelor of Science. We have in total received had 695 applications and certified 391 engineers. We have also developed a system to certify Specialists in Clinical engineering.

Series
IFMBE Proceedings, ISSN 1680-0737
Keyword
Clinical engineer; certification; patient safety
National Category
Social Sciences Interdisciplinary
Identifiers
urn:nbn:se:liu:diva-116919 (URN)10.1007/978-3-319-11128-5_239 (DOI)000349454200239 ()978-3-319-11127-8 (ISBN)
Conference
6th European Conference of the International Federation for Medical and Biological Engineering (MBEC)
Note

6th European Conference of the International-Federation-for-Medical-and-Biological-Engineering (MBEC), Dubrovnik, CROATIA, SEP 07-11, 2014

Available from: 2015-04-09 Created: 2015-04-09 Last updated: 2018-01-11
Gharehbaghi, A., Ekman, I., Ask, P., Nylander, E. & Janerot-Sjoberg, B. (2015). Letter: Assessment of aortic valve stenosis severity using intelligent phonocardiography [Letter to the editor]. International Journal of Cardiology, 198, 58-60.
Open this publication in new window or tab >>Letter: Assessment of aortic valve stenosis severity using intelligent phonocardiography
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2015 (English)In: International Journal of Cardiology, ISSN 0167-5273, E-ISSN 1874-1754, Vol. 198, 58-60 p.Article in journal, Letter (Other academic) Published
Abstract [en]

n/a

Place, publisher, year, edition, pages
ELSEVIER IRELAND LTD, 2015
Keyword
Intelligent phonocardiography; Heart sound; Phonocardiography; Aortic stenosis; Decision support system; Primary healthcare centers
National Category
Clinical Medicine Medical Biotechnology
Identifiers
urn:nbn:se:liu:diva-121420 (URN)10.1016/j.ijcard.2015.06.126 (DOI)000360319900020 ()26151715 (PubMedID)
Available from: 2015-09-18 Created: 2015-09-18 Last updated: 2017-12-04
Gharehbaghi, A., Dutoit, T., Ask, P. & Sornmo, L. (2014). Detection of systolic ejection click using time growing neural network. Medical Engineering and Physics, 36(4), 477-483.
Open this publication in new window or tab >>Detection of systolic ejection click using time growing neural network
2014 (English)In: Medical Engineering and Physics, ISSN 1350-4533, E-ISSN 1873-4030, Vol. 36, no 4, 477-483 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we present a novel neural network for classification of short-duration heart sounds: the time growing neural network (TGNN). The input to the network is the spectral power in adjacent frequency bands as computed in time windows of growing length. Children with heart systolic ejection click (SEC) and normal children are the two groups subjected to analysis. The performance of the TGNN is compared to that of a time delay neural network (TDNN) and a multi-layer perceptron (MLP), using training and test datasets of similar sizes with a total of 614 normal and abnormal cardiac cycles. From the test dataset, the classification rate/sensitivity is found to be 97.0%/98.1% for the TGNN, 85.1%/76.4% for the TDNN, and 92.7%/85.7% for the MLP. The results show that the TGNN performs better than do TDNN and MLP when frequency band power is used as classifier input. The performance of TGNN is also found to exhibit better immunity to noise.

Place, publisher, year, edition, pages
Elsevier, 2014
Keyword
Systolic ejection click; Time growing neural network; Time delay neural network; Heart sound
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-106865 (URN)10.1016/j.medengphy.2014.02.011 (DOI)000334976800008 ()
Available from: 2014-05-28 Created: 2014-05-23 Last updated: 2017-12-05
Rattfält, L., Bjorefors, F., Nilsson, D., Wang, X., Norberg, P. & Ask, P. (2013). Properties of screen printed electrocardiography smartware electrodes investigated in an electro-chemical cell. Biomedical engineering online, 12.
Open this publication in new window or tab >>Properties of screen printed electrocardiography smartware electrodes investigated in an electro-chemical cell
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2013 (English)In: Biomedical engineering online, ISSN 1475-925X, E-ISSN 1475-925X, Vol. 12Article in journal (Refereed) Published
Abstract [en]

Background

ECG (Electrocardiogram) measurements in home health care demands new sensor solutions. In this study, six different configurations of screen printed conductive ink electrodes have been evaluated with respect to electrode potential variations and electrode impedance.

Methods

The electrode surfaces consisted of a Ag/AgCl-based ink with a conduction line of carbon or Ag-based ink underneath. On top, a lacquer layer was used to define the electrode area and to cover the conduction lines. Measurements were performed under well-defined electro-chemical conditions in a physiologic saline solution.

Results

The results showed that all printed electrodes were stable and have a very small potential drift (less than 3 mV/30 min). The contribution to the total impedance was 2% of the set maximal allowed impedance (maximally 1 kΩ at 50 Hz), assuming common values of input impedance and common mode rejection ratio of a regular amplifier.

Conclusion

Our conclusions are that the tested electrodes show satisfying properties to be used as elements in a skin electrode design that could be suitable for further investigations by applying the electrodes on the skin.

Keyword
Screen printed electrodes, ECG, Electrode impedance, Electrode potential, Smartware electrodes
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-96422 (URN)10.1186/1475-925X-12-64 (DOI)000321916300001 ()
Note

Funding Agencies|VINNOVA - Swedens Innovation Agency||NovaMedTech||Linkoping Initiative for Life Science Technologies (LIST)||

Available from: 2013-08-20 Created: 2013-08-19 Last updated: 2017-12-06
Rattfält, L., Lindén, M., Hult, P., Ask, P. & Borga, M. (2013). Robust Heart Beat Detector Based on Weighted Correlation and Multichannel Input: Implementation on the ECG recorded with textile electrodes. Paper presented at 8th International Conference on Wearable Micro and Nano Technologies for Personalized Health. International Journal of E-Health and Medical Communications, 4(1), 61-71.
Open this publication in new window or tab >>Robust Heart Beat Detector Based on Weighted Correlation and Multichannel Input: Implementation on the ECG recorded with textile electrodes
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2013 (English)In: International Journal of E-Health and Medical Communications, ISSN 1947-315X, Vol. 4, no 1, 61-71 p.Article in journal, Meeting abstract (Refereed) Published
Abstract [en]

The aim of this study was to develop and evaluate a robust heartbeat detector for noisy electrocardiograms (ECGs) recorded with textile electrodes. We suggest a method based on weighted correlation in a multi-channel ECG to obtain a heartbeat detector. Signals were acquired during rest and at movements which simulate every day activities. From each recording a segment corresponding to a heartbeat was extracted and correlated with the whole signal. From the correlation data, heartbeat candidates were derived and weighted based on their variance similarity with the heartbeat model and previous heartbeats. Finally, the outputs of each channel were added to create the global output. The output was compared to the Pan Tompkins heartbeat detector. Results are promising for recordings at rest (sensitivity = 0.97, positive predictive value (PPV) = 0.97). For static muscle tension in the torso the results were much higher than the reference method (sensitivity = 0.77, PPV = 0.85). Corresponding values for the reference method were sensitivity = 0.96 and PPV = 0.95 at rest and sensitivity = 0.52 and PPV = 0.75 during muscle tension.

Place, publisher, year, edition, pages
IGI Global, 2013
Keyword
textile electrodes, multichannel ecg, noise suppression, heartbeat detector
National Category
Other Medical Engineering
Identifiers
urn:nbn:se:liu:diva-79772 (URN)10.4018/jehmc.2013010106 (DOI)
Conference
8th International Conference on Wearable Micro and Nano Technologies for Personalized Health
Available from: 2012-08-14 Created: 2012-08-14 Last updated: 2015-03-20
Ask, P., Ekstrand, K., Hult, P., Lindén, M. & Pettersson, N.-E. (2012). NovaMedTech - a regional program for supporting new medical technologies in personalized health care. Studies in Health Technology and Informatics, 177, 71-5.
Open this publication in new window or tab >>NovaMedTech - a regional program for supporting new medical technologies in personalized health care
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2012 (English)In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 177, 71-5 p.Article in journal (Refereed) Published
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.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-87681 (URN)10.3233/978-1-61499-069-7-71 (DOI)22942033 (PubMedID)
Available from: 2013-01-22 Created: 2013-01-21 Last updated: 2017-12-06
Rattfält, L., Bjorefors, F., Wang, X., Nilsson, D., Norberg, P. & Ask, P. (2011). Electrical Characterization of Screen Printed Electrodes for ECG Measurements. In: Roa Romero, Laura M. (Ed.), Mediterranean conference on medical and biological engineering and computing 2013: . Paper presented at 15th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC 2011) (pp. 219-221). Paper presented at 15th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC 2011). Springer Berlin/Heidelberg, 34(2011).
Open this publication in new window or tab >>Electrical Characterization of Screen Printed Electrodes for ECG Measurements
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2011 (English)In: Mediterranean conference on medical and biological engineering and computing 2013 / [ed] Roa Romero, Laura M., Springer Berlin/Heidelberg, 2011, Vol. 34, no 2011, 219-221 p.Chapter in book (Refereed)
Abstract [en]

Screen printed electrodes with conductive ink made of Carbon and Ag/AgCl were tested for polarization potentials and electrode impedances. In 30 minutes the mean decrease of polarization potential was 2 mV. The electrode impedances at 10 Hz were between 670 and 250 Ohms. These characteristics seem adequate for personalized health care applications.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2011
Series
IFMBE Proceedings, ISSN 1680-0737 ; 34
Keyword
Screen printed electrodes; ECG; impedance spectroscopy; polarization potentials
National Category
Analytical Chemistry
Identifiers
urn:nbn:se:liu:diva-116920 (URN)10.1007/978-3-642-21683-1_55 (DOI)978-3-642-21682-4 (ISBN)
Conference
15th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC 2011)
Note

15th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC 2011), Aalborg, DENMARK, JUN 14-17, 2011

Available from: 2015-04-09 Created: 2015-04-09 Last updated: 2016-08-30
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