Smartphone-based Gait Analysis: A Boon for Disease Diagnosis
Kai Leong
Killarney Secondary
Floor Location : S 047 N

With only three gait analysis centers in Western Canada, gait analysis is currently not an accessible, feasible, or cost-effective method of disease diagnosis and screening. An often overlooked marker of health, gait has been validated as an early marker for Alzheimer’s disease, multiple sclerosis, Parkinson’s disease, sports-related injuries, and chronic pulmonary disease. With the rise of smartphone use in Canada and across the world amongst children and seniors alike, smartphones are at the forefront of health research tools.

The aim of this study was to develop and investigate an automated smartphone based gait analysis system capable of detecting and monitoring gait parameters similar to the golden standard GaitRite system. Smartphone-based gait analysis offers numerous benefits: in terms of cost savings, portability, customizability, patient tolerance, and deployment scalability. In addition, this gait analysis tool is feasible in both the developing and developed world.

An algorithm was developed to identify gait cycles and parameters using accelerometers embedded in all commercial smartphones without the need for sensors external to the phone. Measures of stride length and time variability, gait asymmetry, and cadence were successfully gleaned using this gait analysis algorithm. After comparison with the golden standard, small error values for step length, step time, and distance were calculated.

This system has the potential to transform smartphones into health monitors designed to monitor health markers while the smartphone is carried during normal activities, namely, free-living walking. The present study’s results suggest that gait analysis may soon be a feasible and accessible method of disease diagnosis in virtually any environment.