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Content Provider | IEEE Xplore Digital Library |
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Author | Rosen, S. Tucker, C.A. Lee, S.C.K. |
Copyright Year | 2006 |
Description | Author affiliation: Biomed. Eng. Program, Drexel Univ., Philadelphia, PA (Rosen, S.) |
Abstract | Children with cerebral palsy (CP) expend up to three times the energy required for ambulation as compared to typically developed children of the same age. Measuring the metabolic energy required to execute a task is an intuitively appealing way to quantify task efficiency. Task energy demand is often quantified through pulmonary tests that measure oxygen consumption. Although providing an accepted measure of energy demand, these tests are technically demanding and staff intensive. For this reason, we sought a measure of gait efficiency based on spatiotemporal and kinematic parameters that would be reflective of the energy cost during ambulation in children with cerebral palsy. Gait data from 18 subjects with CP over 30 separate data collection sessions was used. Statistical analysis showed oxygen cost highly correlates to several kinematic variables, most notably, pelvic tilt, walking speed, landing angle and the biomechanical efficiency quotient (BEQ). The results of the work support the development of a computational model that would capture gait energy efficiency |
Sponsorship | IEEE EMB |
Starting Page | 1220 |
Ending Page | 1223 |
File Size | 167390 |
Page Count | 4 |
File Format | |
ISBN | 1424400325 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2006.260744 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2006-08-30 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Energy efficiency Birth disorders Energy measurement Testing Kinematics Costs Spatiotemporal phenomena Statistical analysis Legged locomotion Computational modeling |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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