The ability to estimate knee angle and detect heel-strike and toe-off events in real-time will greatly benefit current research being performed in training and rehabilitation devices for stroke and neurological disorder patients. This work set out to accomplish this by developing algorithms to detect heel-strike and toe-off in various stroke patients, and estimate knee angle on an able bodied individual using inertial measurement units (IMUs).
The algorithms developed were able to detect every heel-strike and toe-off point in real-time from all six trials of six different stroke patients, yielding a correlation of 0.97 and above compared to commercial software. The knee angle was also successfully estimated in real-time with a RMSE of 8° compared to motion capture software.
|Commitee:||Khoo, I-Hung, Krishnan, Vennila|
|School:||California State University, Long Beach|
|Department:||Mechanical and Aerospace Engineering|
|School Location:||United States -- California|
|Source:||MAI 56/06M(E), Masters Abstracts International|
|Subjects:||Engineering, Biomedical engineering, Mechanical engineering|
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