Abstract
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).
Highlights
Internet of things (IoT) and ubiquitous sensing (US) are playing an important role in smart healthcare, and have entirely changed the landscape of the conventional traits and practices with self-organizing, distributed, low-power, and economical features
Experimental results reveal that our developed chip collects real-time ECG data efficiently, and the proposed efficient transmission power control (ETPC) algorithm achieves higher energy savings of 35.5% with a slightly larger packet loss ratio (PLR) as compared to conventional transmission power control (TPC)
We analyze the performance of single-chip-based wearable platform for measuring ECG signal by applying different filters for power line noise filtering
Summary
Internet of things (IoT) and ubiquitous sensing (US) are playing an important role in smart healthcare, and have entirely changed the landscape of the conventional traits and practices with self-organizing, distributed, low-power, and economical features. Sensors 2018, 18, 923 affecting the design and development of US is the energy drain and confined battery lifetime of sensor-enabled devices. A rapid technological revolution in miniaturized wearable devices and fast mathematical tools have motivated every corner of the medical domain, and has encouraged body sensor networks (BSNs) for examining the patients’ health over 24-h. A BSN is a group of tiny sensor nodes deployed on/in-body for getting up-to-date and accurate medical information by consulting with expert physicians for present and future health records. The data acquired from the multiple sensor nodes (e.g., electrocardiogram (ECG), blood pressure (BP), saturation oxygen level (SpO2 ), etc.) are further processed, and communicated by transmitter sensor nodes and base station (BS) to the end user. The continuous, dynamic, and long-term acquisition and monitoring of human physiological signals is carried out by wearable smart healthcare devices
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
