Development of a Flexible Armalcolite/PDMS Sensing Device With Machine Learning for Physiological Temperature Monitoring

Abstract

The ceramic material based skin-attachable wearable sensing device, integrated with artificial intelligence technology, plays a crucial role in real-time temperature monitoring for health-care and disease diagnosis. However, a few unavoidable drawbacks of ceramic materials such as congenital brittleness, toxicity, low biocompatibility, long response and recovery times, poor sensitivity, and hysteresis prevent them from being used in various advanced applications. Therefore, in this research work, a highly sensitive skin-attachable Armalcolite/PDMS-based flexible temperature sensor is fabricated by using a facile spin coating technique. The microstructures of the Armalcolite/PDMS sensor are investigated by using XRD, SEM and FTIR techniques. The developed sensor exhibits various desirable properties like high relative percentage sensitivity (−1.50% $^{\circ }$ C $^{-1}$ ), excellent linearity (R $^{2} =$ 0.999), good sensing accuracy (0.1 $^{\circ }$ C), and better stability (30 days) for the tracking of temperature from (25-45) $^{\circ }$ C. These outstanding characteristics of the developed sensor show its potential to fulfill the demands of biomedical applications and enduring skin temperature monitoring. Additionally, the real-time application of the sensor in the surveillance of the human skin temperature, rate of breathing, touch sensitivity of fingers, and blow air temperature measurement are anatomized. Furthermore, its efficacy is assessed using an artificial intelligence (AI)-based machine learning classifier, highlighting its potential in e-skin and healthcare application. The sensor also wirelessly transmits temperature data to a mobile device for real-time body temperature monitoring, underscoring its versatility and utility in healthcare applications.