Electrical Engineering Department, Sukkur IBA University, Sukkur 65200, Pakistan.
Decision Information Systems and Production LAB, University Lumiere Lyon2, Bron-69500, France.
Sensors (Basel). 2018 Mar 20;18(3):923. doi: 10.3390/s18030923.
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).
微型医疗设备的快速发展和新兴趋势使得人们能够以引人注目的方式，普遍而深入地监测每个人生活中的生理信号和日常活动。由于传统可穿戴传感器设备在普遍感知 (US) 期间的能量受限性质，节能已成为医疗保健中高度需求和有争议的问题之一。本文采用德州仪器 (Texas Instruments) 的模拟前端 (AFE) 芯片模型 ADS1292R 开发了一种基于单芯片的可穿戴无线心电图 (ECG) 监测系统。该开发的芯片采用两个采用的通道收集实时 ECG 数据，用于连续监测人体心脏活动。然后，这两个通道和 AFE 被构建到右腿驱动右腿驱动 (RLD) 驱动电路中，具有导联脱落检测和医疗级测试信号。在整个实验设置中，以 60 次/分钟 (BPM) 至 120 BPM 的速度采集 60 Hz 噪声的人类 ECG 数据。此外，设计了截止频率为 60 Hz、0.67 Hz 和 100 Hz 的带通滤波器 (截止频率 60 Hz)、高通滤波器 (截止频率 0.67 Hz) 和低通滤波器 (截止频率 100 Hz)，分别采用双线性变换对实时 ECG 信号进行整流，同时提取电源噪声和伪迹。最后，提出了一种基于传输功率控制的节能 (ETPC) 算法，并在硬件上实现，然后与几种传统 TPC 方法进行比较。实验结果表明，我们开发的芯片能够有效地采集实时 ECG 数据，与传统 TPC（例如，恒定 TPC、Gao 的方法和 Xiao 的方法）相比，所提出的 ETPC 算法在略微增加分组丢失率 (PLR) 的情况下可实现高达 35.5%的节能效果。
