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Fig. 3 | Journal of NeuroEngineering and Rehabilitation

Fig. 3

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

Fig. 3

The control diagram implemented in the active arm support. The upper section represents the physiological system (man with DMD), while the lower section represents the assistive system (active arm support). To perform a movement and reach the target position (\(p_{tar_{x,y}}\)) the man with DMD generates neural commands (C cnt ) with his central nervous system (CNS) that result in muscle activation (i.e. from where sEMG signals E sen are measured), and in muscle contraction that generates a voluntary wrench (W vol ). The intention of the user is detected in two ways: from sEMG signals (E sen ) or by measuring the interaction force and torque between the user’s arm and the active arm support (W int ). The interaction wrench (W int ), which is a combination of the voluntary wrench (W vol ) and the passive/intrinsic human arm wrench (W pas ) is measured by a force/torque sensor (W int ). In the force-based control method with stiffness compensation (FSC) an estimation of the voluntary force of the user (\(\hat {\mathbf {F}}_{vol_{x,y}}\)) is obtained by actively compensating the stiffness forces of the arm (\(\hat {F}_{stf}\)). The estimated stiffness forces for a given position of the arm (\(\mathbf {p}_{pnt_{x,y}}\)) are obtained from previously measured data. In the force-based control method without stiffness compensation (FNC) the estimated voluntary forces (\(\hat {\mathbf {F}}_{vol_{x,y}}\)) are equal to the measured interaction forces (\(\mathbf {F}_{int_{x},y}\)). In the sEMG-based control method the sEMG signals from two agonist/antagonist muscle pairs (biceps/triceps, and deltoid anterior/posterior) are measured and non-physiological voluntary forces are estimated from each muscle (F b ,F t ,F da ,F dp ). An estimated voluntary force in the x and y directions (\(\hat {\mathbf {F}}_{vol_{x,y}}\)) are obtained by subtracting the estimated voluntary forces of the antagonist muscles from the agonist muscles. In all control methods the estimated voluntary forces are used as input to an interface dynamic system (\(H_{adm_{e}},H_{adm_{f}}\)) that rendered the dynamics of a mass-damper system. The rotational velocity of the pointer around the vertical axis (\(\dot {\theta }_{ref_{z}}\)) is actively driven by the interaction torque between the subject’s arm and the robot (\(\tau _{int_{z}}\)) using the interface dynamics (\(H_{adm_{t}}\)). The resulting linear and angular velocity reference signals (\(\dot {\mathbf {p}}_{ref_{x,y}},\dot {\theta }_{ref_{z}}\)) are send to a low-level velocity controller of the UR5 Robotic Arm. The wrench (W res ) generated by the motors of the UR5 Robotic Arm (W mot ) together with the interaction wrench (W int ) moves the passive robot dynamics together with the pointer and the human arm dynamics to the position \(\mathbf {p}_{pnt_{x,y}}\) and the orientation \(\theta _{pnt_{z}}\). This motion is measured by the proprioceptive sensors of the man with DMD and is used to generate new neural commands to eventually reach the target position

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