Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review

Area of Science:

• Robotics
• Neuroscience
• Human-Machine Interaction

Background:

• Human nervous system interaction with robotic lower limb exoskeletons is key.
• Current exoskeleton control often treats controllers as external agents.
• Embodiment principles suggest controllers should integrate with the human nervous system's dynamics.

Purpose of the Study:

• To emphasize the necessity of measuring exoskeleton embodiment.
• To advocate for high-fidelity quantitative embodiment measures over qualitative surveys.
• To explore advanced techniques for understanding embodiment in human-machine interactions.

Main Methods:

• Review of existing research on embodiment and exoskeletons.
• Discussion of the limitations of current qualitative measures.
• Proposal for the integration of quantitative measures and mobile brain imaging techniques.

Main Results:

• Current qualitative measures of embodiment are insufficient.
• Quantitative measures are crucial for exoskeleton development and prototyping.
• Mobile brain imaging, like high-density electroencephalography, can offer deeper insights.

Conclusions:

• Future exoskeleton research must incorporate quantitative embodiment metrics.
• Improved embodiment measurement will advance human-machine interaction.
• This approach will enhance the success and development of robotic exoskeletons.