Senior-Safety-Strider: AI-Powered Walking Aid with Fall Detection for Seniors

This research presents the analysis and evaluation of an AI-powered walking aid system, which utilizes pitch and roll angle data from a cane to monitor and assess user walking behavior. The system is designed to distinguish between correct and incorrect walking behaviors by analyzing changes in these angles during user movement. The experimental results indicate that when the roll angle of the cane increases beyond 8 degrees while the pitch angle remains within the range of −20 to 20 degrees, the movement is identified as correct walking behavior, allowing the system to accurately count steps. However, if the pitch angle deviates beyond the specified range and the roll angle shows significant changes, the system identifies the walking behavior as incorrect and halts analysis to prevent inaccurate step counting. The findings of this study demonstrate that the AI-powered walking aid system effectively detects and analyzes walking behavior, thereby enhancing walking safety and preventing falls for users, particularly among the elderly who require appropriate and continuous care and support.