Gait analysis that is used to measure human activity level, is an important aspect for the health professionals. It helps in understanding the limitations caused in the locomotion due to some orthopedic conditions or some neurological disorders. Health analysis though of key importance is yet, limited to the routine pathological monitoring and dietitian consultation. A possible Extension of it could be pre--habilitation (Pre-hab) process for wellness. Pre-hab process helps to prepare your body for high level of activities, reduces the possible risk of injury and ensures quick recovery. The work proposed in the paper emphasize on aspect of Recognition of Gait Pattern for pre-hab through the body worn sensors comprising of accelerometer, gyroscope & electromyography. Continuous remote monitoring is done using sensor connectivity to internet of things (IoT). The analysis of normal or abnormal gait is done using the Data Analytics Module.
{"title":"Pre-Habilitation and Wellness through Gait Analysis using Body Worn Sensors","authors":"Neha Sathe, A. Hiwale, R. Phalnikar","doi":"10.1145/3194244.3194258","DOIUrl":"https://doi.org/10.1145/3194244.3194258","url":null,"abstract":"Gait analysis that is used to measure human activity level, is an important aspect for the health professionals. It helps in understanding the limitations caused in the locomotion due to some orthopedic conditions or some neurological disorders. Health analysis though of key importance is yet, limited to the routine pathological monitoring and dietitian consultation. A possible Extension of it could be pre--habilitation (Pre-hab) process for wellness. Pre-hab process helps to prepare your body for high level of activities, reduces the possible risk of injury and ensures quick recovery. The work proposed in the paper emphasize on aspect of Recognition of Gait Pattern for pre-hab through the body worn sensors comprising of accelerometer, gyroscope & electromyography. Continuous remote monitoring is done using sensor connectivity to internet of things (IoT). The analysis of normal or abnormal gait is done using the Data Analytics Module.","PeriodicalId":117372,"journal":{"name":"ICCET '18","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134001381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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