Edge-Cloud-Based Wearable Computing for Automation Empowered Virtual Rehabilitation

This work intends to enhance the standard of rehabilitative care provided to patients by optimizing the medical automation monitoring system enabled by wearable computing by edge cloud and Internet of Things technology. First, the recent research literature on edge cloud and wearable computing devices is analyzed. Recent studies in virtual reality and automated medical rehabilitation are used to analyze and contrast various data fusion techniques in wearable sensors. Subsequently, an edge cloud model is constructed to enable real-time tracking of patients’ vital signs, allowing for timely assessment of their health status and rehabilitation progress. Then, a wearable device information monitoring rehabilitation system is established to provide effective rehabilitation treatment for stroke patients. The monitoring module of the rehabilitation system incorporates an edge computing terminal device, which models the virtual circuit for enhanced functionality. Based on the findings, when the number of output codes from the network structure is set to 1000, the average conversion energy of the dynamic conversion system is 140, the first conversion energy of the proposed model is 160, and the second conversion energy is 220. Regarding the rehabilitation treatment effectiveness, the system developed here demonstrates superior operational efficiency and delivers improved outcomes in rehabilitation treatment. This work serves as a practical reference for advancing the intelligent transformation of the medical service system. Note to Practitioners—The goal of this work is to examine the viability of an automated virtual rehabilitation system for use in medical rehabilitation training for stroke, auto accident, and post-operative stroke rehabilitation. Combining the current research status of edge cloud and wearable devices reveals that the majority of existing rehabilitation training approaches are primarily reflected at the theoretical level, with only a few instances of practical applications highlighted. Therefore, this work presents a novel method for designing a wearable medical information monitoring system that operates on the edge cloud with the wearable device computing automation service as its foundation. It can track the patient’s vitals in real time to gauge the rehabilitation’s success. When compared to other cutting-edge rehabilitation options, the validated established edge cloud model clearly stands out as superior and can aid patients in achieving better outcomes from their rehabilitation treatment. The result demonstrates that the method is effective. In the future, it is planned to apply this rehabilitation system to more treatment cases and improve the overall design of the system.