การวเคราะหขอมลเครองพยงฝกกาวเดนของผปวยขาออนแรงผานระบบ IoT

This research aims to design and develop a database system for a weight-supporting gait training device intended for individuals with walking difficulties, such as stroke patients, individuals with muscular weakness, and the elderly.The research began with the development of a prototype device to support gait training through weight assistance. The project was initiated to address the challenges faced during the post-rehabilitation phase, where patients begin to regain their ability to walk or move their legs independently. At this stage, frequent gait training using assistive walking frames is essential to strengthen muscle groups. However, a significant issue encountered during training is the risk of falling, primarily due to the lack of an effective weight support system in existing assistive devices. As many patients continue to experience mobility impairments and residual disabilities, their walking patterns remain unstable, resulting in a fall risk two to three times higher than that of their age-matched peers. The most effective solution to prevent falls is consistent gait training, which has been scientifically proven to enhance muscle strength and significantly reduce the risk of falling. In light of current technological advancements, the Internet of Things (IoT) has played an increasingly important role in modern electronic devices such as smartphones and home appliances. Recognizing the potential of IoT, the research team proposes integrating this technology into the weight-supporting gait training device. The objective is to develop a system capable of storing and analyzing data related to patient gait and mobility through a cloud-based platform, thereby improving patient monitoring, rehabilitation planning, and individualized care.