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Although several reports have described advances in intelligent robotic systems and brain-machine interfaces (BMI) that have helped restore functionality and independence to individuals living with sensorimotor challenges and deficits; fewer studies have focused on tasks requiring bimanual coordination and fine manipulation given the technical complexity of controlling multiple degrees of freedom (DOF) across multiple limbs in a coordinated way through a user input.
To address this challenge, a recent study published in Frontiers in Neurorobotics describes a collaborative shared control strategy to manipulate and coordinate two Modular Prosthetic Limbs (MPL) for performing a bimanual self-feeding task.
The study was conducted by a multidisciplinary team of researchers led by Dr. D. Handelman of the Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD. USA.
A human participant with microelectrode arrays in sensorimotor brain regions provided commands to both MPLs to perform the self-feeding task, which included bimanual cutting.
Motor commands were decoded from bilateral neural signals to control up to two DOFs on each MPL at a time.
The shared control strategy enabled the participant to map his four-DOF control inputs, two per hand, to as many as 12 DOFs for specifying robot end effector position and orientation.
Using neurally-driven shared control, the participant successfully and simultaneously controlled movements of both robotic limbs to cut and eat food in a complex bimanual self-feeding task.
The authors conclude that their demonstration of bimanual robotic system control via a brain-machine interface (BMI) in collaboration with intelligent robot behavior has major implications for restoring complex movement behaviors and re-enabling activities of daily living (ADL) for those living with sensorimotor deficits like spinal cord injured patients.
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