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Gait Recognition Using Joint Moments, Joint Angles, and Segment Angles
Author(s) -
Peter K. Larsen,
Niels Lynnerup,
Marius Henriksen,
Tine Alkjær,
Erik B. Simonsen
Publication year - 2010
Publication title -
journal of forensic biomechanics
Language(s) - English
Resource type - Journals
eISSN - 2090-2697
pISSN - 2090-2689
DOI - 10.4303/jfb/f100302
Subject(s) - sagittal plane , gait , joint (building) , gait analysis , angular displacement , offset (computer science) , computer science , displacement (psychology) , mathematics , physical medicine and rehabilitation , artificial intelligence , geometry , medicine , anatomy , engineering , psychology , structural engineering , programming language , psychotherapist
Recognition of gait patterns has been studied only moderately during the last decades. Different gait strategies have been described by applying different waveform anal- ysis techniques to biomechanical gait data and it has been shown that individuals can be identified using joint angles in the sagittal plane. However, little is known about addi- tional variables for gait recognition. We examined which biomechanical variables (joint moments, joint angles, and segment angles from the lower extremities) obtained in a gait lab could be used to distinguish between 21 subjects on two different days. A systematic "dc-offset" between days was often observed. This could be removed by taking the first derivative to the displacement data. Especially the joint angular and segment angular "velocities" (first derivative) in the sagittal and frontal planes provided high recognition rates and 100% subjects could be recognized by combining three of these variables.

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