Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics

Abstract

Medical robotics has revolutionized healthcare by enhancing precision, adaptability, and clinical outcomes. This field has further evolved with the advent of human–machine interfaces (HMIs), which facilitate seamless interactions between users and robotic systems. However, traditional HMIs rely on rigid sensing components and bulky wiring, causing mechanical mismatches that limit user comfort, accuracy, and wearability. Flexible sensors offer a transformative solution by enabling the integration of adaptable sensing technology into HMIs, enhancing overall system functionality. Further integrating artificial intelligence (AI) into these systems addresses key limitations of conventional HMI, including challenges in complex data interpretations and multimodal sensing integration. In this review, we systematically explore the convergence of flexible sensor‐based HMIs and AI for medical robotics. Specifically, we analyze core flexible sensing mechanisms, AI‐driven advancements in healthcare, and applications in prosthetics, exoskeletons, and surgical robotics. By bridging the gap between flexible sensing technologies and AI‐driven intelligence, this review presents a roadmap for developing next‐generation smart medical robotic systems, advancing personalized healthcare and adaptive human–robot interactions.