Adam T. Barth, Benjamin Boudaoud, Jeff S. Brantley, Shanshan Chen, Christopher L. Cunningham, Taeyoung Kim, H. Powell, Samuel A. Ridenour, J. Lach, B. Bennett
{"title":"Longitudinal high-fidelity gait analysis with wireless inertial body sensors","authors":"Adam T. Barth, Benjamin Boudaoud, Jeff S. Brantley, Shanshan Chen, Christopher L. Cunningham, Taeyoung Kim, H. Powell, Samuel A. Ridenour, J. Lach, B. Bennett","doi":"10.1145/1921081.1921107","DOIUrl":null,"url":null,"abstract":"Gait analysis has long been used for various medical and healthcare assessments [1]. In orthopedics and prosthetics, gait analysis is essential for identifying the pathology and assessing the efficacy of the orthopedic assistants or prosthetics prescribed. For example, the efficacy of ankle-foot orthoses (AFOs), usually prescribed to patients with muscle disorders, (e.g., cerebral palsy, spinal cord injury, muscular dystrophy, etc.) to prevent contractures [2], remains unclear. Studies on recovery and rehabilitation from knee surgery have shown that gait analysis focusing on knee joint angles is the key to evaluating the efficacy of treatment. In elderly healthcare, gait analysis has also played an important role in studies of fall risks and fall prevention [3]. Even in cognitive and neuropsychology studies, gait analysis becomes an important parameter because of the close relationship between human cognitive skills and motor function. For example, [4] and [5] have shown the research value of gait analysis in Parkinson's disease and early childhood autism diagnosis, respectively.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"47 1","pages":"192-193"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1921081.1921107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Gait analysis has long been used for various medical and healthcare assessments [1]. In orthopedics and prosthetics, gait analysis is essential for identifying the pathology and assessing the efficacy of the orthopedic assistants or prosthetics prescribed. For example, the efficacy of ankle-foot orthoses (AFOs), usually prescribed to patients with muscle disorders, (e.g., cerebral palsy, spinal cord injury, muscular dystrophy, etc.) to prevent contractures [2], remains unclear. Studies on recovery and rehabilitation from knee surgery have shown that gait analysis focusing on knee joint angles is the key to evaluating the efficacy of treatment. In elderly healthcare, gait analysis has also played an important role in studies of fall risks and fall prevention [3]. Even in cognitive and neuropsychology studies, gait analysis becomes an important parameter because of the close relationship between human cognitive skills and motor function. For example, [4] and [5] have shown the research value of gait analysis in Parkinson's disease and early childhood autism diagnosis, respectively.