Human-in-the-Loop Optimization of Exoskeleton Assistance Via Online Simulation of Metabolic Cost

Abstract

Many assistive robotic devices have been developed to augment or assist human locomotion. Despite advancements in design and control algorithms, this task remains challenging. Human walking strategies are unique and complex, and assistance strategies based on the dynamics of unassisted locomotion typically offer only modest reductions to the metabolic cost of walking. Recently, human-in-the-loop (HIL) methodologies have been used to identify subject-specific assistive strategies, which offer significant improvements to energy savings. However, current implementations suffer from long measurement times, necessitating the use of low-dimensional control parameterizations, and possibly requiring multiday collection protocols to avoid subject fatigue. We present a HIL methodology, which optimizes the assistive torques provided by a powered hip exoskeleton. Using musculoskeletal modeling, we are able to evaluate simulated metabolic rate online. We applied our methodology to identify assistive torque profiles for seven subjects walking on a treadmill, and found greater reductions to metabolic cost when compared to generic or off-the-shelf controllers. In a secondary investigation, we directly compare simulated and measured metabolic rate for three subjects experiencing a range of assistance levels. The time investment required to identify assistance strategies via our protocol is significantly lower when compared to existing protocols relying on calorimetry. In the future, frameworks such as these could be used to enable shorter HIL protocols or exploit more complex control parameterizations for greater energy savings.

Modelling the interaction between wearable assistive devices and digital human models—A systematic review

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Patient-Specific Exercises with the Development of an End-Effector Type Upper Limb Rehabilitation Robot

“…Future works will mainly start from the following aspects. One is to study the human-in-the-loop optimization control-based rehabilitation to perform more scientific rehabilitation training strategy [ 38 ]. The second is to study the intelligent prescription; the ULRR system should be able to adaptively and intelligently give the optimal training prescription based on the assessment of the patient's rehabilitation status.…”

Improving Muscle Force Distribution Model Using Reflex Excitation: Toward a Model-Based Exoskeleton Torque Optimization Approach

“…In addition, hand tuning of exoskeletons is very cumbersome in practice. Hence, to expedite and facilitate development of effective exoskeletons having a general, reliable, and realistic model-based design approach is a must [15][16][17][18].…”