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Fig. 1 | Journal of NeuroEngineering and Rehabilitation

Fig. 1

From: Comparison between sEMG and force as control interfaces to support planar arm movements in adults with Duchenne: a feasibility study

Fig. 1

General Framework for sEMG- and Force-based Admittance Control. Simplified control diagram of the physiological system and the assistive system. To perform a movement the man with DMD generates neural commands (C cnt ) with his central nervous system (CNS), which result in muscle activation (i.e. from where sEMG signals E sen are measured) and muscle contraction that generates voluntary muscle force (F vol ). Either force (F int ) or sEMG signals (E sen ) are used to derive the motion intention of the user and control the assistive system. a The interaction force (F int ), which is a combination of the voluntary muscle force (F vol ) and the passive/intrinsic human arm force (F pas ) is measured by a force sensor (F int ). An estimation of the voluntary force of the user is obtained by actively compensating the intrinsic arm force (\(\hat {F}_{com}\)). b sEMG signals from the arm muscles of the user are measured and a voluntary force is estimated from them. In both control methods the estimated voluntary force is used as input for an admittance model. The resulting velocity reference signal (v ref ) is send to a low-level velocity feedback controller that operates the actuator. The resulting force (F res ) generated by the actuator (F act ) together with the interaction force (F int ) moves the passive robot and human arm dynamics with a support velocity (v sup )

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