aiqbench analysis
This research demonstrates a significant advancement in assistive robotics by enabling users with quadriplegia to control home mobile manipulators via bimanual high-density EMG signals from paralyzed limbs. By integrating these wearable sensors with vision and language modules, the system achieves up to 98% classification accuracy for performing daily living tasks without traditional input devices. This work bridges critical gaps in human-robot interaction, offering a practical solution for restoring independence through advanced neural interface technologies.
Bimanual High-Density EMG Control for In-Home Mobile Manipulation by Users with Quadriplegia
arXiv:2602.02773v2 Announce Type: replace Abstract: Mobile manipulators in the home can enable people with cervical spinal cord injury (cSCI) to perform daily physical household tasks that they could not otherwise do themselves. However, paralysis in these users often limits access to traditional robot control interfaces such as joysticks or keyboards. In this work, we introduce and deploy the first system that enables a user with quadriplegia to control a mobile manipulator using intent from paralyzed parts of their body, using bimanual high-density electromyography (HDEMG). We develop a pair of custom, fabric-integrated HDEMG forearm sleeves, worn on both arms, that capture residual neuromotor activity from clinically paralyzed degrees of freedom and support real-time gesture-based robot control. We achieve high classification accuracies based on motor intent across (n = 2) users with cSCI, achieving up to 98.0%. Second, by integrating vision, language, and motion planning modules, we introduce a shared autonomy framework that supports robust and user-driven teleoperation, with particular benefits for navigation-intensive tasks in home environments. Finally, to demonstrate the system in the wild, we present a twelve-day in-home user study evaluating real-time use of the wearable EMG interface for daily robot control. Together, these system components enable effective robot control for performing activities of daily living (ADLs) and other household tasks in a real home environment.
Abstract:Mobile manipulators in the home can enable people with cervical spinal cord injury (cSCI) to perform daily physical household tasks that they could not otherwise do themselves. However, paralysis in these users often limits access to traditional robot control interfaces such as joysticks or keyboards. In this work, we introduce and deploy the first system that enables a user with quadriplegia to control a mobile manipulator using intent from paralyzed parts of their body, using bimanual high-density electromyography (HDEMG). We develop a pair of custom, fabric-integrated HDEMG forearm sleeves, worn on both arms, that capture residual neuromotor activity from clinically paralyzed degrees of freedom and support real-time gesture-based robot control. We achieve high classification accuracies based on motor intent across (n = 2) users with cSCI, achieving up to 98.0%. Second, by integrating vision, language, and motion planning modules, we introduce a shared autonomy framework that supports robust and user-driven teleoperation, with particular benefits for navigation-intensive tasks in home environments. Finally, to demonstrate the system in the wild, we present a twelve-day in-home user study evaluating real-time use of the wearable EMG interface for daily robot control. Together, these system components enable effective robot control for performing activities of daily living (ADLs) and other household tasks in a real home environment.
Robotics (cs.RO)
arXiv:2602.02773 [cs.RO]
(or arXiv:2602.02773v2 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2602.02773 Focus to learn more arXiv-issued DOI via DataCite
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