Abstract
A SmartInsoles Cyber-Physical System (CPS) is designed and implemented for the purpose of measuring gait parameters of multiple users in a restriction-free environment. This CPS comprises a master software installed on a computer and numerous multi-sensory health devices in the form of smart insoles. Each of these insoles contains 12 Force-Sensitive Resistor (FSR) sensors, an Inertial Measurement Unit (IMU), a WiFi-enabled microcontroller and a battery to power all components. A validation pilot study was completed in collaboration with the Interdisciplinary School of Health Sciences at the University of Ottawa by performing 150 trials on 15 healthy subjects. Each subject performed 10 walks on the Tekscan Strideway gait mat system, while simultaneously wearing the designed SmartInsoles CPS. Spatiotemporal data for over 450 unique steps were collected by both systems. These data were analyzed carefully, and a thorough comparison was performed between the results from the two systems. Seven parameters were analyzed in this study: stride time, stance time, swing time, double support time, step time, cadence and gait time. Detailed results in the form of tables, scatterplots, histograms and Bland–Altman graphs were generated. Analysis of the results shows high agreement between the values of the two systems and suggests high accuracy of the implemented CPS as a multi-device, multi-sensory system for gait measurement and analysis.
Highlights
Recording detailed foot kinetics and pressure point data can be beneficial in performance enhancement applications such as in sports and physiotherapy
We present the results of this experiment, where SW represents the results acquired by the Strideway system, and IN represents the results acquired by the implemented Insoles’ Cyber-Physical System (CPS)
Many studies in healthcare technologies and mHealth are moving towards facilitating remote patient monitoring [45,46,47], which can reduce costs and improve quality of care [48]
Summary
Recording detailed foot kinetics and pressure point data can be beneficial in performance enhancement applications such as in sports and physiotherapy. Research in post-routine analysis for medical and rehabilitation applications is still lacking an optimal solution that can record gait data to be used for fall prediction, detection and avoidance [1] Solutions to this problem are especially imperative for people who have a high risk of serious injuries as a result of falling or tripping [2]. Novel technological advances in IoT, including wireless technology and sensors, allow for the possibility of building low-cost, wearable insoles that can collect continuous measurements These measurements can be acquired while a given participant is performing an everyday activity in naturalistic conditions (e.g., going up and down stairs, crossing a road, etc.). The main advantages of the wireless shoe insole format are that they can be used in naturalistic settings, can monitor changes in gait overtime in these settings and can be used in conjunction with other wireless technologies to track an individual in real time
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