Subjective Assessment of Individualized Gait Patterns on Enjoyment, Comfort, and Naturalness in Robot-Assisted Walking

Abstract

Lower-limb exoskeletons often use trajectory-tracking control to define the device's motion and assistance level. One challenge lies in ensuring a smooth and comfortable interaction between the user and the robotic device by defining a reference trajectory. While recent research has focused on generating individualized gait patterns based on user-specific body characteristics and walking speed, limited research has explored the subjective perception of these patterns and their impact on user experience and rehabilitation outcomes.

This study investigates user perceptions of individualized versus standard and random gait patterns, focusing on enjoyment, comfort, and naturalness. A predictive gait pattern model, incorporating individual data and walking speed, was developed and tested with human participants using a grounded robotic lower limb device. Participants compared the three gait pattern types and provided subjective feedback through a questionnaire.

Findings indicate no significant preference for any gait pattern in terms of enjoyment, comfort, and naturalness, except for physical strain where the predicted pattern caused significantly more strain than the standard. The analysis also revealed that longer engagement with the device led to increased comfort and naturalness, suggesting an adaptation effect. A general tendency towards preferring the standard pattern was noted, though further research is necessary to determine whether a larger sample size reveals significant differences. Additionally, the perception of different gait patterns and their effect on the rehabilitation outcome should be explored with stroke patients.