Signal processing for tele-healthcare
Emil Plesnik, University of Ljubljana, Faculty of Electrical Engineering
dr. Matej Zajc, University of Ljubljana, Faculty of Electrical Engineering
Duration 2009 - 2012
Emil Plesnik presented: Mobile Users ECG Signal Processing at ICT INNOVATIONS 2012 (link), 13.9.2012 Ohrid (presentation)
Emil Plesnik, Olga Malgina, Jurij F. Tasič and Matej Zajc. Detection of the electrocardiogram fiducial points in the phase space using the Euclidian distance measure. Medical engineering & physics, 1 May 2012, Vol. 34, No. 4, pp. 524-529, http://www.sciencedirect.com/science/article/pii/S1350453312000082, DOI: 10.1016/j.medengphy.2012.01.005
Abstract The paper proposes a phase-space based algorithm applying the Euclidian distance measure enabling detection of heartbeats and characteristic (fiducial) points from a single-lead electrocardiogram (ECG) signal. It extends the QRS detection in the phase space by detecting the P and T fiducial points. The algorithm is derived by reconstructing the ECG signals in a two-dimensional (2D) phase space according to the delay method and utilizes geometrical properties of the reconstructed phase portrait of the signal in the phase space for the heartbeat and fiducial-point detection. It uses adaptive thresholding and the Euclidian distance measure between the signal points in the phase portrait as an alternative to the phase-portrait area calculation (Lee et al., 2002 ). It was verified with the QT Database (2011; ) and its performance was assessed using sensitivity (Se) and the positive predictive value (PPV). Results for the proposed algorithm are 99.06%, 99.75% and 99.66% for Se and 94.87%, 99.75% and 99.66% for PPV for the P points, heartbeats and T points, respectively.
Emil Plesnik, Olga Malgina, Jurij F. Tasič and Matej Zajc. Detection of the electrocardiogram fiducial points in the phase space using area calculation. Electrotechnical review, english edition, 2011, Vol. 78, No. 5, pp. 257-262, http://ev.fe.uni-lj.si/5-2011/Plesnik.pdf.
Abstract The paper proposes an extension of a known method for heart-beat detection based on ECG reconstruction in a 2D phase space coherent to the delay method to detection of the P-Q-R-S-T characteristic (fiducial) points. The QT Database was used for evaluation and algorithm performance was assessed using sensitivity (Se) and positive predictive value (PPV). Results are 99.19 %, 99.67 % and 94.58 % for Se and 95.02 %, 99.67 % and 94.55 % for PPV for the P points, heartbeats and T points, respectively.
Emil Plesnik, Olga Malgina, Jurij F. Tasič and Matej Zajc. ECG baseline drift correction through phase space for simple R-point detection. The 25th IEEE International Symposium on Computer-Based Medical System, CBMS 2012, June 20-22, Rome, Italy. CBMS 2012.. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6266307
Abstract Baseline wandering interference causes inaccurate detection of electrocardiogram (ECG) characteristics such as the R point. In this paper an alternative approach for correction of the ECG baseline wandering for R-point detection is presented. The baseline wandering is corrected in the phase space where the ECG is reconstructed by using the first derivative of the signal. After correction in the phase space a simple thresholding can be used for the correct detection of R points. The method is evaluated on signals from the MIT-BIH Arrhythmia database. Results show that the method is effective in removing baseline wandering from the ECG and detecting the R points by a simple fixed threshold.
Recent research of the European statistical office Eurostat forecast increase in population in the age group over 65 years throughout the European Union. In addition, 86% of all deaths in the EU result from various chronic diseases such as cardiovascular disease, cancer, diabetes, muscular skeletal disorders, respiratory diseases, mental diseases, etc. Additionally, the higher costs of treatment and in recent years, the amount of resources allocated to health care continuing to grow. All these are serious motives to explore alternative services that would enhance the effectiveness of health care, facilitate the lives of patients and also decrease treatment-related costs.
Group for telemedicine services is dedicated to the realization of algorithms for digital processing of biosignals, such as compression algorithms or algorithms for detection of important biosignal features. Important area of research is also system architecture for biosignal acquisition.
Important scientific and application research topics are:
1. Algorithms for signal compression, feature detection and selection, signal classification for various applications, e.g. in medicine, sports, leisure, etc.
2. Data visualization and user interfaces: determining the feedback information of the system and methods of its presentation.
3. Architectures for acquisition of biosignals: sensors and electrodes for acquisition, amplifiers, isolating circuits, equalizers, A/D converters and microprocessors.
4. Wireless Sensor Networks (WSN): their use in telemedicine, especially in terms of Body Sensor Networks (BSN).
5. Communication technologies and protocols in wireless sensor networks.