A Wireless and Battery-Free Wearable Pressure Sensing System for Human-Machine Interaction and Health Monitoring

• Published in: IEEE journal on flexible electronics Vol. 2; no. 6; p. 1
• Main Authors: Lee, Sang Won, Pei, Xiaochang, Rajendran, Jerome, Esfandyarpour, Rahim
• Format: Journal Article
• Language: English
• Published: IEEE 01.11.2023
• Subjects: Biomedical monitoring; Flexible electronics; Human-machine interaction; Monitoring; MXene; PEDOT:PSS; Pressure sensors; Real-time systems; Sensors; Wearable healthcare devices; Wireless communication; Wireless sensor networks
• ISSN: 2768-167X; 2768-167X
• DOI: 10.1109/JFLEX.2023.3300997

Wearable devices have received tremendous interest in healthcare monitoring due to their significant advantages in terms of flexibility, non-invasiveness, wireless capability, and portability. However, they still face challenges including the need for external power sources, bulky measuring instruments, and a lack of a wireless data transport system. Herein, we propose a PEDOT:PSS/MXene pressure sensing platform based on 2D e-textile and screen-printed interdigitated electrodes. Both materials improve the electrical conductivity, sensitivity, stability, flexibility, and mechanical durability of the pressure sensor. A near-field communication (NFC) readout system provides real-time wireless monitoring by transmitting signals from the sensor to a smartphone app, without external batteries. The pressure sensor has sensitivity, a wide detection range, excellent repeatability and stability, fast response/recovery time, and long-term durability. Long-term usability was verified through the bending test up to 21,400 cycles. The flexible pressure sensor successfully monitored wrist pulse, physical movements, and various muscle movements in the body. Repeatable, stable, reliable, and regular signals were obtained wirelessly through the NFC readout system. Our sensing platform could be a promising solution for healthcare monitoring, rehabilitation therapy, and early medical diagnosis. Additionally, it suggests a new platform for helping people with disabilities to communicate with others through human-machine interaction.