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Voluntary muscular e ffort prediction for FES using EMG


Jeroen Buil

Semester Thesis, FS12 (10177)

Combining Functional Electrical Stimulation (FES) with an exoskeletal robotic device seem to prove good results in the rehabilitation of stroke patients. However a big limitation is that the amount of voluntary e ort that the patients are exerting is not maximised with the current rehabilita- tion strategy. However measuring the amount of voluntary e ort, a patient is exerting, is not an easy task as the electrical stimulation creates large artefacts in the EMG signal. In order to acquire an estimate of the amount of voluntary e ort a subject is exerting while receiving functional electri- cal stimulation, it is required to lter out both the stimulation and muscle artefacts evoked by FES. A system has been designed in LABVIEW which blanks the stimulation artefacts and eliminates the varying muscle responses by prediction the shape using an linear adaptive lter.


Type of Publication:

(13)Semester/Bachelor Thesis

R. Nguyen

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2012:IFA_4180
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