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Knee Angle Analysis Using a Wearable Motion Analysis System for Detection and Rehabilitation of Mild Traumatic Brain Injury

[+] Author Affiliations
Amanda L. Martori, Stephanie L. Carey, Derek J. Lura, Rajiv V. Dubey

University of South Florida, Tampa, FL

Paper No. SBC2013-14802, pp. V01AT20A032; 2 pages
doi:10.1115/SBC2013-14802
From:
  • ASME 2013 Summer Bioengineering Conference
  • Volume 1A: Abdominal Aortic Aneurysms; Active and Reactive Soft Matter; Atherosclerosis; BioFluid Mechanics; Education; Biotransport Phenomena; Bone, Joint and Spine Mechanics; Brain Injury; Cardiac Mechanics; Cardiovascular Devices, Fluids and Imaging; Cartilage and Disc Mechanics; Cell and Tissue Engineering; Cerebral Aneurysms; Computational Biofluid Dynamics; Device Design, Human Dynamics, and Rehabilitation; Drug Delivery and Disease Treatment; Engineered Cellular Environments
  • Sunriver, Oregon, USA, June 26–29, 2013
  • Conference Sponsors: Bioengineering Division
  • ISBN: 978-0-7918-5560-7
  • Copyright © 2013 by ASME

abstract

Mild traumatic brain injuries (mTBI) are common in soldiers and athletes, and can affect many areas of a person’s daily life including gait [1]. Current methods of measuring gait parameters involve expensive optical motion capture systems, time intensive setup, wires, complicated filtering techniques, and a laboratory setting. A wearable and wireless motion analysis system would allow gait analysis to be performed outside of a laboratory setting during activities of daily living, in a clinical setting or on a football field. The purpose of this study was to develop and verify an algorithm to calculate knee flexion during slow gait, particularly during terminal stance and pre-swing phases, using wireless wearable sensors.

Copyright © 2013 by ASME

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