(Invited) Intelligent Wearable Biosensors—Progress and Problem

Abstract

Artificial intelligence (AI) and wearable sensors are two fields that are instrumental in realizing the goal of precision medicine—tailoring the best treatment for individual patients. Recent development between these two fields is enabling better patient data acquisition and improved design of wearable sensors for monitoring the wearers’ health, fitness, and their surroundings. The growing field of wearable sensors aims to tackle the limitations of centralized, reactive healthcare by giving individuals insight into the metrics of their own physiology. However, assessing the effectiveness of a therapeutic platforms on disease is extremely complex, due to the massive quantities of data generated by biomedical devices. Integration of AI approaches can bridge this gap, using pattern analysis and classification algorithms for improvement of diagnostic and therapeutic accuracy. The future AI-biosensors (AI wearable sweat biosensor, AI- eatable biosensor, AI-glass biosensor, AI-implantable biosensor et al.) mainly have the function of AI-diagnosis (Diagnostic algorithms in the microprocessor can verify the output of the sensor and present the diagnostic information), Big data processing (Use of self-contained space for historical data and various necessary parameters of data storage to greatly improve the performance of the controller.) and Self-learning/adaptive (Embedded microprocessor with advanced programming function. In the working process, the AI-biosensor can reconstruct the structure and parameters according to certain behavioral criteria, and has adaptive functions)