TY - JOUR
T1 - Low-power wireless ECG acquisition and classification system for body sensor networks
AU - Lee, Shuenn Yuh
AU - Hong, Jia Hua
AU - Hsieh, Cheng Han
AU - Liang, Ming Chun
AU - Chien, Shih Yu Chang
AU - Lin, Kuang Hao
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - A low-power biosignal acquisition and classification system for body sensor networks is proposed. The proposed system consists of three main parts: 1) a high-pass sigma delta modulator-based biosignal processor (BSP) for signal acquisition and digitization, 2) a low-power, super-regenerative on-off keying transceiver for short-range wireless transmission, and 3) a digital signal processor (DSP) for electrocardiogram (ECG) classification. The BSP and transmitter circuits, which are the body-end circuits, can be operated for over 80 days using two 605 mAH zinc-air batteries as the power supply; the power consumption is 586.5 μW. As for the radio frequency receiver and DSP, which are the receiving-end circuits that can be integrated in smartphones or personal computers, power consumption is less than 1 mW. With a wavelet transform-based digital signal processing circuit and a diagnosis control by cardiologists, the accuracy of beat detection and ECG classification are close to 99.44% and 97.25%, respectively. All chips are fabricated in TSMC 0.18-μm standard CMOS process.
AB - A low-power biosignal acquisition and classification system for body sensor networks is proposed. The proposed system consists of three main parts: 1) a high-pass sigma delta modulator-based biosignal processor (BSP) for signal acquisition and digitization, 2) a low-power, super-regenerative on-off keying transceiver for short-range wireless transmission, and 3) a digital signal processor (DSP) for electrocardiogram (ECG) classification. The BSP and transmitter circuits, which are the body-end circuits, can be operated for over 80 days using two 605 mAH zinc-air batteries as the power supply; the power consumption is 586.5 μW. As for the radio frequency receiver and DSP, which are the receiving-end circuits that can be integrated in smartphones or personal computers, power consumption is less than 1 mW. With a wavelet transform-based digital signal processing circuit and a diagnosis control by cardiologists, the accuracy of beat detection and ECG classification are close to 99.44% and 97.25%, respectively. All chips are fabricated in TSMC 0.18-μm standard CMOS process.
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U2 - 10.1109/JBHI.2014.2310354
DO - 10.1109/JBHI.2014.2310354
M3 - Article
C2 - 25561446
AN - SCOPUS:84920871937
SN - 2168-2194
VL - 19
SP - 236
EP - 246
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 1
M1 - 6762857
ER -