An Energy-Efficient Algorithm for Wearable Electrocardiogram Signal Processing in Ubiquitous Healthcare Applications.
An Energy-Efficient Algorithm for Wearable Electrocardiogram Signal Processing in Ubiquitous Healthcare Applications.
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DOI：
10.3390/s18030923
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发表时间：
2018-03-20
期刊：
影响因子：
--
通讯作者：
Pirbhulal S
中科院分区：
文献类型：
--
作者：
Sodhro AH;Sangaiah AK;Sodhro GH;Lohano S;Pirbhulal S
小型化医疗设备的快速发展和新兴趋势使得能够以突出和普遍的方式对每个人的生理信号和日常活动进行非侵入式监测。由于传统可穿戴传感器设备在无处不在的感测（US）期间的功率受限性质，能量效率已经成为医疗保健中的高度要求和有争议的问题之一。采用德州仪器公司的模拟前端芯片ADS 1292 R，研制了一种基于单片机的可穿戴式无线心电监护系统。所开发的芯片采集实时心电数据，采用两个通道连续监测人体心脏活动。然后，这两个通道和AFE被构建到具有导联脱落检测和医学分级测试信号的右腿驱动右腿驱动（RLD）驱动器电路中。在60 Hz噪声下以60次/分钟（BPM）至120 BPM收集人ECG数据，并在整个实验设置中进行考虑。采用双线性变换设计了截止频率分别为60 Hz、0.67 Hz和100 Hz的陷波滤波器（截止频率为60 Hz）、高通滤波器（截止频率为0.67 Hz）和低通滤波器（截止频率为100 Hz），用于在提取实时心电信号的同时对电源线噪声和伪影进行校正。最后，本文提出了一种基于发射功率控制的能量有效（ETPC）算法，并在硬件上实现了该算法，并与几种传统的TPC方法进行了比较。实验结果表明，我们开发的芯片有效地收集实时ECG数据，并且所提出的ETPC算法与传统TPC（例如，恒定TPC，Gao和Xiao的方法）。
Rapid progress and emerging trends in miniaturized medical devices have enabled the un-obtrusive monitoring of physiological signals and daily activities of everyone’s life in a prominent and pervasive manner. Due to the power-constrained nature of conventional wearable sensor devices during ubiquitous sensing (US), energy-efficiency has become one of the highly demanding and debatable issues in healthcare. This paper develops a single chip-based wearable wireless electrocardiogram (ECG) monitoring system by adopting analog front end (AFE) chip model ADS1292R from Texas Instruments. The developed chip collects real-time ECG data with two adopted channels for continuous monitoring of human heart activity. Then, these two channels and the AFE are built into a right leg drive right leg drive (RLD) driver circuit with lead-off detection and medical graded test signal. Human ECG data was collected at 60 beats per minute (BPM) to 120 BPM with 60 Hz noise and considered throughout the experimental set-up. Moreover, notch filter (cutoff frequency 60 Hz), high-pass filter (cutoff frequency 0.67 Hz), and low-pass filter (cutoff frequency 100 Hz) with cut-off frequencies of 60 Hz, 0.67 Hz, and 100 Hz, respectively, were designed with bilinear transformation for rectifying the power-line noise and artifacts while extracting real-time ECG signals. Finally, a transmission power control-based energy-efficient (ETPC) algorithm is proposed, implemented on the hardware and then compared with the several conventional TPC methods. Experimental results reveal that our developed chip collects real-time ECG data efficiently, and the proposed ETPC algorithm achieves higher energy savings of 35.5% with a slightly larger packet loss ratio (PLR) as compared to conventional TPC (e.g., constant TPC, Gao’s, and Xiao’s methods).
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