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Human-exoskeleton interaction portrait.

Mohammad Shushtari¹, Julia Foellmer², Arash Arami^3,4

¹Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.

Journal of Neuroengineering and Rehabilitation

|September 5, 2024

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This study introduces the interaction portrait (IP) to analyze human-robot co-adaptation in lower limb exoskeletons. IP reveals distinct strategies for hybrid torque controllers (HTC) and adaptive model-based torque controllers (AMTC), improving user-exoskeleton coordination.

Area of Science:

Robotics
Biomechanics
Human-Computer Interaction

Background:

Optimizing user experience and robot performance in human-robot physical interaction is critical.
Assessing user adaptation and co-adaptation in wearable robots, like lower limb exoskeletons, requires advanced analytical methods.
Traditional analyses of muscle activity and interaction torque alone may not fully capture complex human-robot co-adaptation dynamics.

Purpose of the Study:

To introduce a novel method, the interaction portrait (IP), for evaluating human-robot interaction and co-adaptation in lower limb exoskeletons.
To compare the co-adaptation strategies elicited by a hybrid torque controller (HTC) and a novel adaptive model-based torque controller (AMTC) against a time-based controller (TBC).
To demonstrate the potential of IP analysis in comparing and designing controllers for optimized human-robot interaction in wearable robots.

Keywords:

Control Exoskeleton Physical Interaction

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Main Methods:

Muscle activity and interaction torque were analyzed as a two-dimensional random variable.
The interaction portrait (IP) was introduced, visualizing this variable's distribution in polar coordinates.
IP was applied to compare HTC, AMTC, and TBC during treadmill walking at varying speeds, assessing normalized oxygen uptake.

Main Results:

Both HTC and AMTC significantly reduced users' normalized oxygen uptake compared to TBC, indicating improved user-exoskeleton coordination.
IP analysis identified two distinct co-adaptation strategies: HTC promoted yielding control to the exoskeleton, while AMTC encouraged user engagement with reduced interaction torque.
IP phase evolution provided insights into individual user interaction strategy formation.

Conclusions:

The interaction portrait (IP) offers a novel approach to understanding and quantifying human-robot co-adaptation in lower limb exoskeletons.
Different controllers elicit distinct co-adaptation strategies, with AMTC showing promise for rehabilitation and gait training applications due to enhanced user engagement.
IP analysis has the potential to significantly advance the design and optimization of controllers for wearable robots.