Monitoring gait events by image processing

This paper presents a novel methodology in measuring Foot Progression Angle (FPA) and other gait parameters, using digital image processing, based on body and foot speeds. Measurements of body parts' movement speeds allow identification of gait events such as initial contact, mid stance and Flat Foot Phase (FFP). Algorithms were developed to segment FFP based on the motion patterns and their relationships. Digital data and graphic presentation results are generated synchronously from the same optic device. This could allow clinicians to confirm results of the both data sets. New methodology requires participant to walk along a 10-meter flat walkway, at self-selected speed, wearing comfortable shoes. Measurement set-up involves a mobile-phone camera, attached to a torso-mounted strap, pointing downwards, a walkway with parallel straight lines outlining progression direction, and printed strips placed along the long axis of the foot. Several methods were evaluated to find the best way to detect initial contact, flat foot and mid stance phases. Our new methodology may present a solution for mobile gait analysis, which could be used at home, or community / outdoor environment, basically outside of the sophisticated well equipped and expensive labs.