Optimal design of active-passive shoulder exoskeletons: a computational modeling of human-robot interaction

Exoskeleton robots, which range from fully passive to fully active-assisted movements, have become an essential instrument for assisting industrial employees and stroke rehabilitation therapy. Designing the exoskeleton actuation is challenging and time-consuming due to closed kinematic loops in the 3D human-exoskeleton multibody model, complicated interactions, and interdependent selection of power transmission features. This research proposes a process for dynamic syntheses of passive and active assistive shoulder exoskeletons. First, a multibody model was developed using six components: an upper-body musculoskeletal model, an optimal controller, the exoskeleton's rigid body, a passive mechanism, a powered actuator, and an assistance model. The desired motion was experimentally measured from six tasks: frontal reaching, left to right reaching, overhead reaching, sagittal-plane object handling, frontal-plane object handling, and over-head object handling. The system design was optimized by choosing features of the passive mechanism and exoskeleton motor such that the human joint active torque, power, muscle metabolic energy expenditure, and actuator electricity consumption were minimized. The dynamic synthesis processes were found to be successful, and the resultant optimized active-passive exoskeletons allow for the creation of lighter and smaller wearable robots that reduce the user's muscular activation torque for the tasks being studied.