Memristor-based intelligent systems for sensing, computing, and therapeutic integration applications

Memristor technology is heralding a paradigm shift for implantable/wearable medical devices. By synergistically integrating their intrinsic nonvolatile memory and brain-inspired computing capabilities with biocompatible materials, memristor-based devices address the fundamental bottlenecks of conventional medical electronics—namely, high power consumption, poor biocompatibility, and low signal processing efficiency. This review comprehensively explores the innovative applications of memristors in medical devices and highlights their core advantages, such as tunable resistance, nonvolatility, and excellent biocompatibility. Key advancements include: neuromorphic computing for predicting epilepsy and monitoring Parkinson's disease; flexible sensors for ultrasensitive detection of physiological signals like pressure and temperature; and implantable systems for continuous health tracking. We provide a focused analysis of how material innovations—including metal oxides, organic compounds, and two-dimensional materials—increase device performance in terms of sensitivity, stability, and environmental adaptability while addressing challenges such as device variability, biocompatibility in complex biological milieus, and large-scale integration. Future trajectories emphasize deep interdisciplinary convergence, brain-like adaptive learning, biodegradable materials, and standardized industrial implementation. Memristors are poised to revolutionize intelligent medicine by delivering efficient, precise, and ultralow-power medical solutions. • It is discussed the applications of memristors in medical devices, focusing on their unique properties such as tunable resistance states, non-volatile memory, and biocompatibility. • Key advancements include their use in neuromorphic computing for epilepsy prediction and Parkinson's disease monitoring are reviewed. • A focused analysis is provided on how metal oxides, organic materials, two-dimensional materials, and other materials enhance device performance. • The review also addresses challenges such as device consistency, biocompatibility in complex biological environments, and large-scale integration. • Future trends emphasize interdisciplinary integration, brain-like adaptive learning, degradable materials, and standardized industrial applications.