Four undergraduate students of the University of Michigan – Shanghai Jiao Tong University Joint Institute (UM–SJTU JI, JI hereafter) have published a research article titled “Patchable Transparent Standalone Piezoelectric P(VDF-TrFE) Film for Radial Artery Pulse Detection” in International Journal of Energy Research, a journal with an impactor factor of 4.6 and journal citation report top 2%. The research project, under the supervision of JI Associate Professor Yuljae Cho, was initiated as an undergraduate research course ECE4900J in Spring 2023 and has outcomes of two SCI journal publications in RSC Advances and International Journal of Energy Research. Co-first authors of the published papers include two juniors, Yian Hu and Shunyao Huang, and one senior Yujia Gao, and one co-author Zhangsiyuan Jin. Yuljae Cho is the corresponding author of both papers.
The article published in International Journal of Energy Research presents a biosensor based on the piezoelectric effect which enables continuous real-time health monitoring for prompt detection of abnormalities caused by chronic or cardiovascular diseases. Despite continuous progress in passive sensors utilizing the piezoelectric effect, many of these sensors for bio applications faced several major challenges: containment of toxic substances that are not biocompatible, structural complexity of sensor devices involving complex manufacturing processes, and a lack of machine learning algorithm for medical data analysis.
The research work carried out by JI students aimed to achieve high piezoelectric output responses for accurate physiological signal acquisition with a biocompatible piezoelectric polymer material, or P(VDF-TrFE). The students solved the prevalent issue of the low piezoelectric output response of the P(VDF-TrFE) polymer by using a solvent based annealing method which induces the dipole-dipole interaction during the crystallization process. As a result, higher ferroelectric β-phase was formed in the polymer film, leading to the enhanced piezoelectric output response. A freestanding piezoelectric polymer was also produced by a facile and scalable method which can be directly attached to any curved surfaces such as on human skin. Thus, a patchable biosensor is achieved for continuous and real-time health monitoring (Figure below).
Population ageing has become one of prominent social issues in recent decades with challenges due to increased demand for medical care for aged people with chronic or cardiovascular diseases. Attributed to the recent development of various biomedical sensors and machine learning technology, it has been forecasted that a real-time health monitoring technique will fundamentally reform the current hospital-based medical care system into the personalized home-based one by utilizing wearable biosensors in the near future. In spite of its importance, a real-time, continuous monitoring capability in wearable medical devices is at its early stage of development for the time being. It has been a challenging issue to collect real-time, continuous physiological signals with personalized biomedical devices due to aforementioned issues—the materials toxicity, structural complexity of devices, and lack of machine learning algorithm for medical data analysis. The wearables biosensors developed are able to accurately convert physiological signals into electric signals, which can be analyzed by machine learning algorithms. The new method developed in the paper is expected to offer a promising route to tackle the current bottlenecks in real-time and continuous health monitoring.
Weblink of the research paper：
https://www.hindawi.com/journals/ijer/2023/2213988/
https://pubs.rsc.org/en/content/articlehtml/2023/ra/d3ra05932d
Author Profiles
Yian Hu is a JI junior undergraduate student majoring in Electronic and Computer Engineering. Her research interests include wearable devices and integrated circuits.
Shunyao Huang is a JI junior undergraduate student majoring in Electronic and Computer Engineering. Her research interest covers wearable sensing technology and machine learning.
Yujia Gao is a JI senior undergraduate student majoring in Electronic and Computer Engineering. She will pursue her graduate degree in the School of Information at the University of Michigan. Her research interest lies in flexible sensing technology.
Zhangsiyuan Jin is a JI senior undergraduate student majoring in Electronic and Computer Engineering. She will continue to pursue her master’s degree at JI. Her research interest includes wearable energy harvesting technology.
Yuljae Cho is an associate professor at JI. He received his Ph.D. degree at University of Oxford and was a research associate at University of Cambridge. His research focuses on emerging energy materials and their applications to energy harvesting and optoelectronic devices.
