Human motor augmentation with an extra robotic arm without functional interference

Area of Science:

• Robotics
• Neuroscience
• Human-Computer Interaction

Background:

• Extra robotic arms (XRAs) offer potential for daily activities but present sensorimotor control challenges.
• Existing human-machine interfaces (HMIs) may hinder users' natural functions when controlling XRAs.

Purpose of the Study:

• To propose a pipeline for identifying suitable HMIs for XRA control.
• To assess a multimodal motor HMI based on gaze and diaphragmatic respiration for controlling XRAs.

Main Methods:

• Developed a modular neurorobotic platform with virtual reality and an upper limb exoskeleton.
• Assessed a multimodal HMI using gaze detection and diaphragmatic respiration.
• Evaluated control of virtual and wearable XRAs with naïve and experienced users.

Main Results:

• The proposed HMI effectively controls XRAs independently or coordinated with biological limbs.
• Performance improved with training and showed learning retention.
• Haptic feedback did not enhance performance.
• Experienced users outperformed naïve users by 22.2%.

Conclusions:

• The developed pipeline and HMI are viable for controlling XRAs.
• Virtual reality-based training and testing are effective for XRAs.
• The HMI allows proficient XRA control without interfering with natural functions.