Ye Sun, Assistant Professor, Mechanical Engineering—Engineering Mechanics
Shiyan Hu, Adjunct Professor, Electrical and Computer Engineering
Sponsor: National Science Foundation
Amount of Support: $330,504
Duration of Support: 3 years
Abstract: Electrophysiological measurement is a well-accepted tool and standard for health monitoring and well-being management. A great number of electrophysiological measurement devices have been developed including clinical equipment, research products, and consumer electronics. However, until now, it is still challenging to secure long-term stable and accurate signal acquisition, especially in wearable condition, not only for medical application in hospital settings, but also for daily well-being management. Motion-induced artifacts widely exist in electrophysiological recording regardless of electrodes (wet, dry, or noncontact). These artifacts are one of the major impediments against the acceptance of wearable devices and capacitive electrodes in clinical diagnosis. This project is to provide new strategies to mitigate motion-induced artifacts in wearable electronics and design accurate wearable electronics for daily monitoring and disease diagnosis. The PIs will disseminate the research products to both students and the research community. New course materials will be developed for undergraduate and graduate education. Undergraduate and graduate students involved in the research program will obtain diverse knowledge in hardware design and data analytics. For K-12 students, the PIs will provide an integrated research and educational experience through the programs of Engineering Exploration Day for Girls and the Summer Youth Program at Michigan Technological University. A research demo and hands-on experience for triboelectric generation in textile materials will be developed and provided to K-12 students.
The research goal of this proposal is to understand the fundamental mechanism of triboelectric artifacts in wearable devices and provide synergistic solutions to mitigating the artifacts. Three approaches are proposed to achieve the goal: 1) understanding the mechanism of triboelectric charge generation in wearable condition by physical modeling and experimental validation; 2) guided by the understanding, developing tribomaterial-based sensors to manipulate triboelectric charges for artifact removal; 3) leveraging the proposed new tribomaterial-based sensors and statistical data analytics for true electrophysiological signal estimation. If successful, the synergic knowledge produced by the project will not only help improve the traditional bioinstrumentation in the medical society, but also benefit industrial community of consumer wearable electronics.
Li, Xian and Sun, Ye. “WearETE: A Scalable Wearable E-Textile Triboelectric Energy Harvesting System for Human Motion Scavenging,” Sensors, v.17, 2017. doi:10.3390/s17112649
Huang, Hui and Hu, Shiyan and Sun, Ye. “Energy-efficient ECG compression in wearable body sensor network by leveraging empirical mode decomposition,” 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2018. doi:10.1109/bhi.2018.8333391