Recent Advances in Flexible Sensing and Edge Intelligence for Embedded Medical Devices: Challenges in Clinical Translation
Abstract
Enabled by chronic disease management, aging trends, and digital health, medical monitoring is evolving from intermittent testing to continuous personalized monitoring. In this context, embedded medical devices integrate physiological data acquisition with edge computing technologies. This review examines the development of flexible sensing and edge intelligence approaches in embedded medical devices, with a focus on their progression from physiological signal acquisition to intelligent analysis and clinical translation. By analyzing recent advances in related technologies, this review summarizes key developments in sensing materials, device architectures, on-device computing, and system-level integration, while also identifying challenges associated with long-term stability, power efficiency, data security, and clinical validation. The analysis highlights that future progress will rely on the synergistic optimization of device design, intelligent algorithms, and clinical evaluation frameworks, with low-power intelligence, multifunctional integration, and standardized evaluation as key directions for future development.
