Synthesis of optimal electrical stimulation patterns for functional motion restoration: applied to spinal cord-injured patients.

We investigated the synthesis of electrical stimulation patterns for functional movement restoration in human paralyzed limbs. We considered the knee joint system, co-activated by the stimulated quadriceps and hamstring muscles. This synthesis is based on optimized functional electrical stimulation...

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Detalles Bibliográficos
Publicado en:Medical & Biological Engineering & Computing Vol. 53; no. 3; pp. 227 - 241
Autores principales: Benoussaad, Mourad, Poignet, Philippe, Hayashibe, Mitsuhiro, Azevedo-Coste, Christine, Fattal, Charles, Guiraud, David
Formato: Journal Article
Publicado: Springer Nature Mar2015
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:We investigated the synthesis of electrical stimulation patterns for functional movement restoration in human paralyzed limbs. We considered the knee joint system, co-activated by the stimulated quadriceps and hamstring muscles. This synthesis is based on optimized functional electrical stimulation (FES) patterns to minimize muscular energy consumption and movement efficiency criteria. This two-part work includes a multi-scale physiological muscle model, based on Huxley's formulation. In the simulation, three synthesis strategies were investigated and compared in terms of muscular energy consumption and co-contraction levels. In the experimental validation, the synthesized FES patterns were carried out on the quadriceps-knee joint system of four complete spinal cord injured subjects. Surface stimulation was applied to all subjects, except for one FES-implanted subject who received neural stimulation. In each experimental validation, the model was adapted to the subject through a parameter identification procedure. Simulation results were successful and showed high co-contraction levels when reference trajectories were tracked. Experimental validation results were encouraging, as the desired and measured trajectories showed good agreement, with an 8.4 % rms error in a subject without substantial time-varying behavior. We updated the maximal isometric force in the model to account for time-varying behavior, which improved the average rms errors from 31.4 to 13.9 % for all subjects.