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

Abstract

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-byframe), 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.

Automated Camera-Based Assessment of Short Physical Performance Battery (SPPB) for Older Adults with Cancer

“…A marker symbol, located in the view area of the cameras, helps calculate the subject's overall angle, regardless of the platform rotation angle (see Figure 4 inset). The CBMT system employs template matching to detect the marker and adjust the platform angle left/right or up/down [21]. For experiments requiring a 180°rotation of the platform, multiple markers can be used.…”

“…In previous work [21], the triangulation technique was employed to obtain polar coordinate positions from subject pixel position pairs (see Figure 5(a)). To reduce depth inaccuracies in the gait speed calculation, the system was calibrated using Eqs.…”

“…This current chapter is based on and is a continuation of the previously published work, "Camera-Based Short Physical Performance Battery and Timed Up and Go Assessment for Older Adults with Cancer," and one other paper, "Camera-Based Human Gait Speed Monitoring and Tracking for Performance Assessment of Elderly Patients with Cancer [20,21]. "…”

“…In this work we propose a self-standing Camera-based Body Motion Tracking (CBMT) system, inspired by earlier studies [20,21], and designed for use in clinics and hospitals to enable easier fitness evaluation of patients using the SPPB tests. The CBMT system performs object recognition and tracking of people, accurately processes all SPPB statistics, can be monitored via a cell phone, and allows for report generation and cloud storage for medical professionals' access.…”