title: Computer-aided generation of stimulation data and model identification for functional electrical stimulation (FES) control of lower extremities.
abstract: Standard stimulation data for unassisted standing up of paraplegic patients was generated by dynamic optimization linked with model simulation, to overcome the difficulties in the present electromyogram (EMG)-based method. The generated stimulation data were roughly in agreement with the normal subjects' EMG. From these, it is suggested that the 'model-based' method is useful as an alternative of the 'EMG-based method'. The same technique can be applied to generation of patient-specific stimulation data once the musculoskeletal system of a patient is properly identified. The musculoskeletal system must be identified from data taken from simple and noninvasive experiments for the identification method to be practically acceptable. We developed a musculoskeletal model and systematic identification protocols for this purpose. They were validated for the vastus lateralis muscle at the knee joint. The identification was successful and the predicted joint angle trajectories closely matched the experimental data. This implies that the model-based generation of patient-specific stimulation data is possible.
authors.affiliation: Graduate School of Engineering, Tohoku University, Sendai, Japan.
authors.forename: G M
authors.initials: GM
authors.lastname: Eom
authors.forename: T
authors.initials: T
authors.lastname: Watanabe
authors.forename: R
authors.initials: R
authors.lastname: Futami
authors.forename: N
authors.initials: N
authors.lastname: Hoshimiy
authors.forename: Y
authors.initials: Y
authors.lastname: Handa
mesh_terms: D003198:Computer Simulation; D004599:Electric Stimulation Therapy; D004576:Electromyography; D006801:Humans; D007866:Leg; D008954:Models, Biological; D009043:Motor Activity; D010264:Paraplegia / Q000503:physiopathology* / Q000628:therapy*; D011187:Posture; D013813:Therapy, Computer-Assisted