Tags:Human-machine interaction, Machine learning, Mobility and Rehabilitation
Abstract:
Human mobility involves the nervous and muscular systems, essential for the planning and execution of movements such as walking. According to the WHO, approximately 3.8% of the global population faces challenges in walking. This article presents the development of a human-machine interface with the goal of testing the system and validating user perception to make it more accessible, efficient, and enjoyable for patients. The integration of serious games into the system was chosen to establish an interactive environment that blends gait training, driving physical rehabilitation. This approach focuses on integrating technology into conventional therapy to offer a safer and more motivating environment. The system was validated with twelve volunteers in a series of tasks that offered different degrees of autonomy when interacting with the treadmill. The evaluation of the control strategy in the tasks used the SUS questionnaire, indicating an acceptability score above 70. The results demonstrate the adaptability of the treadmill to individuals’ speed due to the developed control model, promoting its use in applications combined with serious games, thus enhancing the user experience without increasing complexity.
Automated Treadmill Control Strategy for Gait Rehabilitation Based on Human-Machine Interaction