Population aging is a major hidden concern of society. The biggest impact of population aging on society is the increasing demand for medical care and long-term care, resulting in a heavy burden on social welfare. Therefore, in this study, we designed a wearable device for the rehabilitation of the foot muscles of the elderly, combined with the posture analysis system and integrated with timely data for display on the web. Through IoT, we can not only know the foot muscle strength data, but also know whether the walking posture is standard and whether the user’s walking posture is normal. The system can provide medical personnel with data to understand the foot strength health of the user during the process, to achieve the effects of prevention and rehabilitation. The rehabilitation of the elderly usually takes a lot of time. If someone needs to continue supervision, it will take a lot of time and personnel costs. In the long run, the cost of hospital services will increase. Therefore, we integrated wearable devices and IoT technology and present the muscle strength values collected by wearable devices on a web page. Through the analysis results of different methods, the data attribute and prediction prognosis system use the Extreme Gradient Boosting method with high accuracy, thus achieving the goal of cost research. The data analysis system classifies and presents the data on the web page. The nursing staff or medical personnel can view and understand the muscle strength of the rehabilitation personnel who are walking through the data analysis system on the web page.