Applications of flexible materials in health management assisted by machine learning

Abstract

In recent years, the demand for improved health management has become increasingly higher; however, the existing medical resources have made it difficult to meet this demand. The field of health management is in urgent need for self-help monitoring equipment, intelligent identification technology and personalized medical services. This article reviews the application of flexible materials in health management, particularly the application of flexible wearable sensing devices combined with machine learning technology in various medical scenarios, and classifies them into several types of applications such as health monitoring and prevention, disease diagnosis and treatment, rehabilitation treatment and assistance. Flexible materials can be used to fabricate or integrate various types of high-sensitivity sensors with the characteristics of high flexibility and self-adhesion, resulting in a wealth of health monitoring equipment. These devices can self-monitor various physiological indicators in various parts of the human body. The integration of machine learning (ML) makes it possible to analyze and identify subtle, massive, multi-channel and multi-modal sensor data, accelerating the intelligent process of health management and personalized medicine. This paper not only elaborates on various flexible materials and ML algorithms commonly used in the field of health management, but also focuses on discussing the application of ML-assisted flexible materials in different stages of health management, and puts forward prospects for the future development direction, providing reference and inspiration for major changes in the field of health management.