Low-Power Wireless ECG Acquisition and Classification System for Body Sensor Networks

TLDR

The study proposes a low‑power biosignal acquisition and classification system for body sensor networks. The system comprises a high‑pass sigma‑delta biosignal processor, a low‑power super‑regenerative on‑off‑keying transceiver, and a DSP for ECG classification, all fabricated in TSMC 0.18‑μm CMOS and operating with less than 1 mW power, enabling over 80 days of battery life on two 605 mAh zinc‑air cells. Beat detection and ECG classification achieved accuracies of 99.44 % and 97.25 %, respectively.

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.