Low-power wireless ECG acquisition and classification system for body sensor networks

Shuenn Yuh Lee, Jia Hua Hong, Cheng Han Hsieh, Ming Chun Liang, Shih Yu Chang Chien, Kuang Hao Lin

Research output: Contribution to journalArticlepeer-review

57 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number6762857
Pages (from-to)236-246
Number of pages11
JournalIEEE Journal of Biomedical and Health Informatics
Volume19
Issue number1
DOIs
Publication statusPublished - 2015 Jan 1

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

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