Detection of Running Asymmetry Using a Wearable Sensor System. (2015)

• Record Type: Journal Article
• Authors: Moran, Kieran; Richter, Chris; Farrell, Evan; Mitchell, Edmond; Ahmadi, Amin; O'Connor, Noel E.
• Is Part Of: Procedia engineering. Volume 112(2015)
• Page Start: 180
• Page End: 183
• Publication Date: 2015
• Subjects: Sensor fusion -- Activity classification -- Biomechanics -- Curve shift registration -- Analysis of Characterising Phases; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2015.07.196
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: We demonstrate a wearable ambulatory analysis framework that could be used to evaluate running asymmetry, day-to-day during unconstrained training. The system can automatically differentiate running from other training movement tasks, and extract all of the runner's associated step-cycles (heel-strike to heel-strike). We evaluate the system's ability in 21 participants who have artificially induced asymmetry. Impact accelerations differentiate asymmetry more effectively than angular velocities (gyroscope), and tibial inertial sensors differentiate more effectively than sensors attached to the thigh.