Institute of Electrical and Electronics Engineers (IEEE)
2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC)
Scientific gait analysis through the Internet of Things (IoT) is able to provide an overall assessment of "observations of daily living". All existing biomechanical models for predicting injuries in the elderly mainly consider the gait related parameters. Their accuracy is limited because injuries due to falls are significantly affected by different gait events in the gait cycle. The objective of this study is to develop a biomechanical model for improving subject-specific prediction of when different gait cycle events will induce falls. For this research, we designed and implemented a smart-shoe with a Wi-Fi communication module to discreetly collect insole pressure data in common environment. To the best of our knowledge, we are the first to use the gait biomechanical model implemented in smartphones to identify abnormal gait patterns for risk prediction. The proposed system, Your Walk is My Command, can warn the user about their abnormal gait and possibly save them from a forthcoming injuries.
Majumder, AKM Jahangir Alam; Saxena, Piyush; and Ahamed, Sheikh Iqbal, "Your Walk is My Command: Gait Detection on Unconstrained Smartphone Using IoT System" (2016). Mathematics, Statistics and Computer Science Faculty Research and Publications. 532.