Evoked EMG-based torque prediction under muscle fatigue in implanted neural stimulation

Mitsuhiro Hayashibe 1, * Qin Zhang 2, 1 David Guiraud 1 Charles Fattal 3
* Auteur correspondant
1 DEMAR - Artificial movement and gait restoration
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : In patients with complete spinal cord injury, fatigue occurs rapidly and there is no proprioceptive feedback regarding the current muscle condition. Therefore, it is essential to monitor the muscle state and assess the expected muscle response to improve the current FES system toward adaptive force/torque control in the presence of muscle fatigue. Our team implanted neural and epimysial electrodes in a complete paraplegic patient in 1999. We carried out a case study, in the specific case of implanted stimulation, in order to verify the corresponding torque prediction based on stimulus evoked EMG (eEMG) when muscle fatigue is occurring during electrical stimulation. Indeed, in implanted stimulation, the relationship between stimulation parameters and output torques is more stable than external stimulation in which the electrode location strongly affects the quality of the recruitment. Thus, the assumption that changes in the stimulation-torque relationship would be mainly due to muscle fatigue can be made reasonably. The eEMG was proved to be correlated to the generated torque during the continuous stimulation while the frequency of eEMG also decreased during fatigue. The median frequency showed a similar variation trend to the mean absolute value of eEMG. Torque prediction during fatigue-inducing tests was performed based on eEMG in model cross-validation where the model was identified using recruitment test data. The torque prediction, apart from the potentiation period, showed acceptable tracking performances that would enable us to perform adaptive closed-loop control through implanted neural stimulation in the future.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00630237
Contributeur : David Guiraud <>
Soumis le : vendredi 7 octobre 2011 - 17:08:27
Dernière modification le : jeudi 24 mai 2018 - 15:59:23

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Mitsuhiro Hayashibe, Qin Zhang, David Guiraud, Charles Fattal. Evoked EMG-based torque prediction under muscle fatigue in implanted neural stimulation. Journal of Neural Engineering, IOP Publishing, 2011, 8 (6), pp.7. 〈http://iopscience.iop.org/1741-2552/8/6/064001〉. 〈10.1088/1741-2560/8/6/064001〉. 〈lirmm-00630237〉

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