Enhancing Hand Rehabilitation Through Interactive Design - Xiaotian Sun; Sitong Lu; Jiaqi Fan (CAAI Artificial Intelligence Research)
The demand for hand rehabilitation services is increasing currently, and there are many choices of hand rehabilitation products available on the market. Here, we report a flexible curvature sensor-based data glove, equipped with a built-in light trigger system, which is expected to provide active signal feedback for better human machine interface experience. By analyzing user needs and leveraging advancements in human-computer interaction, this new design not only facilitates physical recovery but also fosters a sense of ownership and motivation among patients. The incorporation of real-time feedback mechanisms further amplifies the efficacy of the rehabilitation process, propelling patients toward greater independence and self-assurance. Specially from an emotional point of view, the elements, such as functionality, design, color, material, and human-computer interaction, based on user needs, would be analyzed to summarize some core requirements. Then the performance of hand movements is integrated into the rehabilitation process through visual feedback to address the problem of monotony during training. This design can leverage the feedback mechanism between visual cues and hand movements, enhancing the sensory interaction experience between individuals and the product. Finally, it is proved by experiment this proposed design is very potential to help improve patients’ motivation and self-efficacy in training, thereby enhancing the effectiveness of rehabilitation. By combining these elements, we believed that the design is expected to make up some emotional support for better human machine interface experience.