2.R R R R Pan-Tompkins(PT) [8] R 2 SQRS[9] PT Q R WQRS[10] Quad Level Vector(QLV)[11] QRS R Continuous Wavelet Transform(CWT)[12] Mexican hat 4

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1 G-002 R Database and R-Wave Detecting System for Utilizing ECG Data Takeshi Nagatomo Ikuko Shimizu Takeshi Ikeda Akio Sashima Koichi Kurumatani R R MIT-BIH R 90% 1. R R [1] Tokyo University of Agri. and Tech Naka cho, Koganei shi, Tokyo , Japan Advanced Industrial Science and Technology(AIST) , Aomi, Koto-ku, Tokyo , Japan [2]-[4] R Medical waveform Format Encoding Rules(MFER)[5] MIT-BIH[6] ABS1[7] R R MIT-BIH 90 R 2 R 3 4 R

2 2.R R R R Pan-Tompkins(PT) [8] R 2 SQRS[9] PT Q R WQRS[10] Quad Level Vector(QLV)[11] QRS R Continuous Wavelet Transform(CWT)[12] Mexican hat 4 ψ(t) = (1 2t 2 )e t2 (1) t[s] R R 10s 0.67 Instantaneous HeartRate(IHR)[13] Short-Term AutoCorrelation(STAC)[14] IHR STAC 1 R : R R 3.2. Relational Database PostgreSQL 4 R ID

3 1) 2) )MFER[5] 2)MIT-BIH[6] 3) ABS1[7] MFER MFER MFER MFER R R R 1) 2)R 3) 3 R 1) [15] P QRS T 225 ms 225 ms 450 ms 3 3: ( mv 1 40 ms 0 mv ( ) ) 2)R R 2: R 1. (R ) R 0.03 R

4 A B 5.2. QLV CWT 5 8 4: R ( ) R 0.03 R R ) R R R 10 10s 0.66 R 10 R R R R 1 = [/min] (2) 1 [s] R 5.1. R MIT-BIH 48 MIT-BIH R (ground truth) R 5: 1( A 0.7 ( ) 48 QLV 39 CWT 36 ) 6: 2( A 40 ) 7: 3(QLV A 39 ) 368

5 11: CWT 8: 4(CWT A 36 ) : ( MIT- BIH 48 ( ) ) R R 2 A R P T Q S R R : QLV 12: 1( R ( ) ) 369

6 B : 2 16: 1 14: 3 R 10 R 10 R 15 17: 2 18: 3 15: 5( ) CWT R Q S T 15 R Q T R R R T R R Q S 1 R Q S 18 Q R R 1 R : 4 370

7 20: R R ( ) R R 21: R MIT-BIH R R [1] DscyOffice ( office/law/ htm) [2] (http: // portable-ecg/software_pag_index.php) [3] ( fukuda.co.jp/medical/products/ecg/) [4] ( nihonkohden.co.jp/iryo/products/physio/ 01_ecg/) [5] ( jp/whatismfer.htm) [6] Ary L. Goldberger, et al. Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals. Circulation 101,23, e215 e220 (2000) 22: 7 22 R R 10 R R 6. [7],,,.. IT 7, Vol.8, No.1, (2013) [8] Jiapu Pan and Willis J. Tompkins. A realtime QRS detection algorithm. IEEE Transactions on Biomedical Engineering, Vol.3, (1985) [9] PhysioNet WFDB Applications, sqrs ( wag/sqrs-1.htm) [10] PhysioNet WFDB Applications, wqrs ( wag/wqrs-1.htm) 371

8 [11] Hyejung Kim et al. ECG signal compression and classification algorithm with quad level vector for ECG holter system. IEEE Trans. on Information Technology in Biomedicine, Vol.14, No (2010) [12] Inaki Romero, et al. Low-power robust beat detection in ambulatory cardiac monitoring. Proc. IEEE Biomedical Circuits and Systems Conference (2009) [13] Masanao Nakano, et al. Instantaneous Heart Rate detection using short-time autocorrelation for wearable healthcare systems. Proc. Engineering in Medicine and Biology Society (2012) [14] Shintaro Izumi, et al. Low-power hardware implementation of noise tolerant heart rate extractor for a wearable monitoring system. Proc. IEEE International Conference on Bioinformatics and Bioengineering (2013) [15] Wenli Chen, et al. Detection of QRS complexes using wavelet transforms and golden section search. Proc. International Conference on Intelligent Systems and Knowledge Engineering (2007) 372

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