title: A patient-controlled functional electrical stimulation system for arm weight relief.
abstract: A patient-driven control strategy for Functional Electrical Stimulation (FES), which amplifies volitionally-initiated shoulder abductions, is proposed to improve stroke patients' rehabilitation. Based on the measured abduction angle, a FES-induced muscle recruitment is generated that yields a pre-specified percentage of this angle - yielding arm weight relief. To guarantee the correct recruitment also under fatigue and uncertain muscle activation we employ feedback control of the recruitment level determined by filtering the FES-evoked electromyogram. Filter parameters are user-optimized to obtain a linear relation between filter output and angle with a good signal-to-noise ratio. The auto-tuned recruitment controller (RC) was tested on five healthy subjects and compared to direct stimulation (DS) while muscle fatigue progressively occurred. Results showed a more linear relation between recruitment level and angle than between non-controlled stimulation intensity and angle (R2=0.93 vs. R2=0.79, angular range of 54°). After 6 min of stimulation, abduction decreased by 42% ± 14 for DS and by 0% ± 12 for RC, showing an effective compensation of fatigue. RC yielded significant smaller errors than DS in generating desired angles (0.23% ± 5.9 vs. 14.6% ± 9.7). When FES-induced arm weight support was provided, a mean reduction of the volitional effort (determined by Electromyography) of 78% was achieved compared to angular tracking without FES. First experiments with one acute stroke patient are also reported.
authors.affiliation: Control Systems Group, Technische Universität Berlin, Berlin, Germany. Electronic address: klauer@control.tu-berlin.de.
authors.forename: C
authors.initials: C
authors.lastname: Klauer
authors.affiliation: NeuroEngineering and Medical Robotics Laboratory, NearLab, Politecnico di Milano, Milan, Italy.
authors.forename: S
authors.initials: S
authors.lastname: Ferrante
authors.affiliation: NeuroEngineering and Medical Robotics Laboratory, NearLab, Politecnico di Milano, Milan, Italy.
authors.forename: E
authors.initials: E
authors.lastname: Ambrosini
authors.affiliation: Klinik für Neurologie mit Stroke Unit und Frührehabilitation, Unfallkrankenhaus, Berlin, Germany.
authors.forename: U
authors.initials: U
authors.lastname: Shiri
authors.affiliation: Klinik für Neurologie mit Stroke Unit und Frührehabilitation, Unfallkrankenhaus, Berlin, Germany.
authors.forename: F
authors.initials: F
authors.lastname: Dähne
authors.affiliation: Klinik für Neurologie mit Stroke Unit und Frührehabilitation, Unfallkrankenhaus, Berlin, Germany.
authors.forename: I
authors.initials: I
authors.lastname: Schmehl
authors.affiliation: NeuroEngineering and Medical Robotics Laboratory, NearLab, Politecnico di Milano, Milan, Italy.
authors.forename: A
authors.initials: A
authors.lastname: Pedrocchi
authors.affiliation: Control Systems Group, Technische Universität Berlin, Berlin, Germany.
authors.forename: T
authors.initials: T
authors.lastname: Schauer
mesh_terms: D000328:Adult; D000369:Aged, 80 and over; D001132:Arm / Q000502:physiology* / Q000503:physiopathology; D004599:Electric Stimulation Therapy / Q000379:methods*; D005240:Feasibility Studies; D006801:Humans; D008297:Male; D020521:Stroke / Q000503:physiopathology / Q000628:therapy; D016474:Weight-Bearing
keywords: Biomedical control; Electromyography; Functional electrical stimulation; Medical systems; Rehabilitation; Signal processing