Camera-Based Human Gait Speed Monitoring and Tracking for Performance Assessment of Elderly Patients with Cancer

This paper presents a camera-based device for monitoring walking gait speed. The walking gait speed data will be used for performance assessment of elderly patients with cancer and calibrating wearable walking gait speed monitoring devices. This standalone device has a Raspberry Pi computer, three cameras (two cameras for finding the trajectory and gait speed of the subject and one camera for tracking the subject), and two stepper motors. The stepper motors turn the camera platform left and right and tilt it up and down by using video footage from the center camera. The left and right cameras are used to record videos of the person walking. The algorithm for operating the proposed system is developed in Python. The measured data and calculated outputs of the system consist of times for frames, distances from the center camera, horizontal angles, distances moved, instantaneous gait speed (frame-by-frame), total distance walked, and average speed. This system covers a large Lab area of 134.3 m
²
and has achieved errors of less than 5% for gait speed calculation.Clinical Relevance— This project will help specialists to adjust the chemo dosage for elderly patients with cancer. The results will be used to analyze the human walking movements for estimating frailty and rehabilitation applications, too.