Assessment of upper limb muscle tone level based on estimated impedance parameters
Many strategies have been developed by occupational and physical therapists for the assessment of poststroke patients’ upper limb muscle tone and physical recovery progress. Despite, having the appropriate skills, they face serious challenges in quantifying continuously, the patients’ recovery p...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IEEE
2017
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/53828/ http://irep.iium.edu.my/53828/ http://irep.iium.edu.my/53828/ http://irep.iium.edu.my/53828/19/53828-Assessment%20of%20Upper%20Limb%20Muscle%20Tone%20Level%20based.pdf http://irep.iium.edu.my/53828/13/Assessment%20of%20upper%20limb%20muscle%20tone%20level%20based%20on%20estimated%20impedance%20parameters.pdf |
| Summary: | Many strategies have been developed by
occupational and physical therapists for the assessment of poststroke patients’ upper limb muscle tone and physical recovery
progress. Despite, having the appropriate skills, they face serious
challenges in quantifying continuously, the patients’ recovery
progress. Moreover, the therapy has become more costly and time
consuming since the patients are required to have a face-to-face
contact with the therapist over a long period of time. By deploying
robot-assisted rehabilitation therapy, some of these problems have
been addressed, however, serious challenges still exist in the aspect
of proper estimation and assessment of patients muscle tone level
and recovery progress during rehabilitation therapy. This paper
proposes an appropriate strategy for prediction and assessment of
subjects’ muscle tone level and recovery based on the estimation
of upper-limb mechanical impedance parameters. The subjects’
mechanical impedance parameters are estimated using a recursive
least square estimator method and the muscle tone level are
predicted by Artificial Neural Network (ANN) which has been
trained using the estimated impedance parameters. Preliminary
experimental result shows that the upper-limb impedance
parameters can be estimated to an accuracy level of 90%, while
simulation studies have revealed that the muscle tone level can be
reliably predicted at 95.01% accuracy level. |
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