Analysis of the Human Interaction with a Wearable Lower‐Limb Exoskeleton

Abstract

The design of a wearable robotic exoskeleton needs to consider the interaction, either physical or cognitive, between the human user and the robotic device. This paper presents a method to analyse the interaction between the human user and a unilateral, wearable lower‐limb exoskeleton. The lower‐limb exoskeleton function was to compensate for muscle weakness around the knee joint. It is shown that the cognitive interaction is bidirectional; on the one hand, the robot gathered information from the sensors in order to detect human actions, such as the gait phases, but the subjects also modified their gait patterns to obtain the desired responses from the exoskeleton. The results of the two‐phase evaluation of learning with healthy subjects and experiments with a patient case are presented, regarding the analysis of the interaction, assessed in terms of kinematics, kinetics and/or muscle recruitment. Human‐driven response of the exoskeleton after training revealed the improvements in the use of the device, while particular modifications of motion patterns were observed in healthy subjects. Also, endurance (mechanical) tests provided criteria to perform experiments with one post‐polio patient. The results with the post‐polio patient demonstrate the feasibility of providing gait compensation by means of the presented wearable exoskeleton, designed with a testing procedure that involves the human users to assess the human‐robot interaction.

Quasi-passive lower limbs exosuit: an in-depth assessment of fatigue, kinematic and muscular patterns while comparing assistive strategies on an expert subject’s gait analysis

“…Moreover, a generalization of the effectiveness over a small number of subjects in a single testing run is always difficult to be reliable (Van Dijk et al, 2011). This aspect is essential, particularly when considering the effects of the learning curve on the user's motion style and neuro-motor coordination, particularly when considering changes in the walking pattern and due to the mutual adaptation in which robot and human effectively cooperate and exchange forces (Moreno et al, 2009;Afzal et al, 2020).…”

Mobile Sensors for Robotics Research

“…Integrating rehabilitation robots with human motion and force sensors for effective training and positive therapeutic effects is attracting more and more attentions in research and clinic fields (Bonato, 2010;Moreno et al, 2009). In order to control robots at the level of human motor control, the muscular activity of the lower limbs which has been estimated from measurements of joint moments and segment orientations may be useful information for biomedical applications (Wu et al, 2009;Lin et al, 2010).…”