Emerging memory devices for neuromorphic computing in the Internet of Medical Things

This review examines recent advances in emerging memory devices for neuromorphic computing within the Internet of Medical Things (IoMT). By integrating novel materials, brain-inspired computational architectures, and bioinspired algorithms, these technologies collectively enable efficient, adaptive, and secure biosignal processing at the edge. The review critically evaluates the strengths and limitations of devices such as resistive, ferroelectric, and photonic memories, highlighting their pivotal roles in overcoming the bottlenecks of conventional CPU/GPU-based systems. In addition, innovations in biocompatible packaging and seamless biointegration are discussed, emphasizing their potential for real-world clinical deployment. These advancements not only enhance energy efficiency, real-time processing, and miniaturization but also support the development of smarter biosensors, neural prosthetics, and wearable diagnostic platforms. The broader significance of this work lies in paving the way for next-generation, intelligent, secure, and patient-centric medical devices, thus accelerating the digital transformation of healthcare through advanced neuromorphic IoMT ecosystems.