Functional electrical stimulation and brain-machine interfaces for simultaneous control of wrist and finger flexion

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Abstract Background Restoring dexterous hand movements in individuals with cervical spinal cord injury requires continuous control of multiple biomechanically linked degrees-of-freedom (DOF). Brain-machine interface (BMI) controlled functional electrical stimulation (FES) is a promising method to restore hand movements. We explored the suitability of restoring movement to two biomechanically linked DOF simultaneously, finger flexion and wrist flexion, using previously introduced FES methods, namely stimulation targeting individual DOFs independently. We then demonstrate a finger and wrist movement BMI that, when combined with the FES system, could restore simultaneous control of wrist and finger flexion. Methods Two monkeys were implanted with intramuscular electrodes in muscles of the hand. Stimulation on these electrodes was used to evoke finger and wrist movements in both monkeys. Additionally, one of these monkeys was implanted with intracortical electrode arrays in the primary motor cortex and used a BMI to control wrist and finger flexion in a virtual hand without FES. Results First we demonstrate a monkey using an intracortical BMI to control the wrist and finger flexion in a virtual hand, both before and after the hand is temporarily paralyzed, achieving success rates and acquisition times equivalent to able-bodied control with BMI control after temporary paralysis in two sessions. We then show that intramuscular FES with two predetermined stimulation patterns, one targeting finger flexion and one targeting wrist flexion, can move the monkeys’ fingers and wrist across a functional range of motion. Due to the biomechanical coupling of the wrist and fingers, stimulation targeting finger or wrist flexion individually ultimately evokes movements in both DOF. However, we demonstrate that a simple control strategy treating each DOF independently was able to control both DOF simultaneously in a closed-loop task, achieving greater than 80% success rates. Conclusions We outline a method using an artificial brain-to-body interface that could restore continuous wrist and finger movements after spinal cord injury.