A Wireless IOT System Towards Gait Detection in Stroke Patients

Gait analysis using the Internet of Things (IoT) is an important medical diagnostic process and has many applications in rehabilitation, therapy and exercise training. We have designed and implemented an IoT model for gain detection in stroke or walking disability persons with a wireless communication module and the smartphone or personal computer to discreetly monitor insole pressure of the patient’s motion. The objective of this study is to present a multisensory system that explores walking patterns to predict a cautious gait in the stroke patient. This portable sensing system serves as a walking aid for rehabilitation training or permanent use in a wide range of gait disabilities. The proposed system can notify the user about their abnormal gait and possibly save the analyzed data of the gait variations in the cloud.