Bionic Skins and Biosensors: Machine Learning Applications of Soft Robotics

Abstract

Abstract - The integration of soft robotics with bio technology and electronics are able to brought transformation with engineered bionic skins and smart bio sensors. Bionic skin provides self-healing, flexibility as well as bio-compatibility to monitor physiological signals as it is engineered to replicate the sensory as well as functional status of human dermis. Complementing these, bio-sensors are able to convert bio logical inputs into quantifiable output signals. These allows health monitoring as real time diagnostics. The intersection of machine learning with number of other sectors has further brought enhancement in these systems that simplify adaptive controls, precise signal processing along with predictive modelling for personalization of health care. These ML techniques (SVM, CNN, RL) are innovative as these progressively found applications for pattern recognition, anomaly detection and feature extraction in bio chemical as well as bio mechanical signals. Its implications have role across rehabilitation, prosthetics, human machine interfaces and chronic disease management. Although their progress is rapid, these met with number of challenges namely data security, bio compatibility, energy efficiency, and regulatory acceptations. This review highlights the evolution of bionic skins and bio sensors, explores their integration with soft robotics and machine learning models and outlines future directions towards multi modal. Intelligent and patient-centered health cared technologies.