경량화된 심전도 측정 임베디드 장비에서 템플릿 기반 직선근사화를 이용한 통신오버헤드 감소 기법
Communication-Power Overhead Reduction Method Using Template-Based Linear Approximation in Lightweight ECG Measurement Embedded Device
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초록
With the recent development of hardware and software technology, interest in the development of wearable devices is increasing. In particular, wearable devices require algorithms suitable for low-power and low-capacity embedded devices. Among them, there is an increasing demand for a signal compression algorithm that reduces communication overhead, in order to increase the efficiency of storage and transmission of electrocardiogram (ECG) signals requiring long-time measurement. Because normal beats occupy most of the signal with similar shapes, a high rate of signal compression is possible if normal beats are represented by a template. In this paper, we propose an algorithm for determining the normal beat template using the template cluster and Pearson similarity. Also, the template is expressed effectively as a few vertices through linear approximation algorithm. In experiment of Datum 234 of MIT-BIH arrhythmia database (MIT-BIH ADB) provided by Physionet, a compression ratio was 33.44:1, and an average distribution of root mean square error (RMSE) was 1.55%.
Abstract
With the recent development of hardware and software technology, interest in the development of wearable devices is increasing. In particular, wearable devices require algorithms suitable for low-power and low-capacity embedded devices. Among them, there is an increasing demand for a signal compression algorithm that reduces communication overhead, in order to increase the efficiency of storage and transmission of electrocardiogram (ECG) signals requiring long-time measurement. Because normal beats occupy most of the signal with similar shapes, a high rate of signal compression is possible if normal beats are represented by a template. In this paper, we propose an algorithm for determining the normal beat template using the template cluster and Pearson similarity. Also, the template is expressed effectively as a few vertices through linear approximation algorithm. In experiment of Datum 234 of MIT-BIH arrhythmia database (MIT-BIH ADB) provided by Physionet, a compression ratio was 33.44:1, and an average distribution of root mean square error (RMSE) was 1.55%.
참고문헌 (14)
- S. L. Rohit, "Iot Based Health Monitoring System Using Raspberry PI –Review", Second International Conference on Inventive Communication and Computational Technologies, pp.997~1002 (2018)
- Sid Ahmed Elhannachi, "Adaptive Medical Image Compression Based on Lossy and Lossless Embedded Zerotree Methods", JIPS(Journal of Information Processing Systems), 13(1), pp.40~56 (2017), 한국정보처리학회[DOI]
- 박용주, "생체 환경 정보 센싱 모듈 및 농장 제어 게이트웨이를 이용한 스마트 낙농 관리 시스템 개발", 대한임베디드공학회논문지, 11(1), pp.15~20 (2016), 대한임베디드공학회[DOI]
- 이형봉, "SpO2 기반 휴대형 생체 신호 모니터링 시스템 개발", 대한임베디드공학회논문지, 8(5), pp.273~283 (2013), 대한임베디드공학회[DOI]
- 이아라, "욕창 방지를 위한 체압 모니터링 시스템 개발", 대한임베디드공학회논문지, 6(4), pp.209~214 (2011), 대한임베디드공학회
- W. Smith, "Comparison of Diagnostic Value Using a Small, Single Channel, P-wave Centric Sternal ECG Monitoring Patch with a Standard 3-lead Holter System over 24 Hours", American Heart Journal, 185, pp.67~73 (2016)
- S. Lee, "Efficient Fiducial Point Detection of ECG QRS Complex Based on Polygonal Approximation", Sensors, 18(12), pp.1~16 (2018)
- S. Lee, "Advanced Real-Time Dynamic Programming in the Polygonal Approximation of ECG Signals for a Lightweight Embedded Device", IEEE Access, 7, pp.1628501~1162861 (2019)
- R. Bellman, "Applied Dynamic Programming" (2015), Princeton Legacy Library, Princeton University Press
- J. Ma, "A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications", IEEE Journal of Biomedical and Health Informatics, 19(3), pp.986~994 (2015)
- X. Wang, "ECG Cmpression Based on Combining of EMD and Wavelet Transform", Electronics Letters, 52(19), pp.1588~1590 (2016)
- G. Bansal, "Template Based Classification of Cardiac Arrhythmia in ECG Data", 2015 IEEE 2nd International Conference on Recent Trends in Information Systems, pp.337~341 (2015)
- S. M. Lee, "Self-Organized Real-Time Authentication Mechanism Using ECG Signal", 2014 The International Industrial Information Systems Conference, pp.231~233 (2014)
- G. B. Moody, "The MIT-BIH Arrhythmia Database on CD-ROM and Software for Use with it", Proceedings Computers in Cardiology, pp.185~188 (1990)