Wireless, Flexible, Ionic, Perspiration‐Rate Sensor System with Long‐Time and High Sweat Volume Functions Toward Early‐Stage, Real‐Time Detection of Dehydration

• Published in: Advanced functional materials Vol. 33; no. 44
• Main Authors: Honda, Satoko, Tanaka, Ryuki, Matsumura, Guren, Seimiya, Naruhito, Takei, Kuniharu
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 25.10.2023
• Subjects: Dehydration; Diagnosis; Electrolytes; Flexible components; Ingestion; Machine learning; Materials science; Metabolites; Monitoring; Parameters; Perspiration; Physiological responses; Physiology; Sensors; Sweat; Sweating; Water drops; Wearable technology
• ISSN: 1616-301X; 1616-3028
• DOI: 10.1002/adfm.202306516

Flexible sensors that can be attached to the body to collect vital data wirelessly enable real‐time, early‐stage diagnosis for human health management. Wearable sweat sensors have received considerable attention for real‐time physiological monitoring. Unlike conventional methods that require blood‐drawing in a clinic, sweat analyses may enable noninvasive tracking of health conditions for early‐stage diagnosis. Even though a variety of studies to monitor metabolites and other substances have been conducted, automatic, continuous, long‐term, simultaneous monitoring of perspiration rate and electrolytes, which are important parameters in dehydration, has yet to be achieved because of challenges related to sensor design. Here a wireless, wearable, integrated, microfluidic sensor system that can continuously measure these parameters in real‐time for prolonged periods are presented. The proposed sensors are systematically characterized, and machine learning is used to predict device tilt angle to calibrate sensor output signals. Using the sensor design to form a water droplet in a fluidic channel, high‐volume perspiration rate is continuously monitored for more than 7000 s (total sweat volume >170 µL). By testing 10 subjects, physiological responses to ingestion of a sports drink are confirmed by measuring perspiration rhythm changes extracted from real‐time, continuous sweat impedance and rate.