Impact of shoulder abduction loading on brain-machine interface in predicting hand opening and closing in individuals with chronic stroke

Background. Many individuals with moderate and severe stroke are unable to use their paretic hand. Currently, the effect of conventional therapy on regaining meaningful hand function in this population is limited. Efforts have been made to use brain-machine interfaces (BMIs) to control hand function. To date, almost all BMI classification algorithms are designed for detecting hand movements with a resting arm. However, many functional movements require simultaneous movements of the arm and hand. Arm movement will possibly affect the detection of intended hand movements, specifically for individuals with chronic stroke who have muscle synergies. The most prevalent upper-extremity synergy - flexor synergy - is expressed as an abnormal coupling between shoulder abductors and elbow/wrist/finger flexors. Objective. We hypothesized that because of flexor synergy, shoulder abductor activity would affect the detection of the hand-opening (a movement inhibited by flexion synergy) but not the hand-closing task (a movement facilitated by the flexion synergy). Methods. We evaluated the accuracy of a BMI classification algorithm in detecting hand-opening versus closing after reaching a target with 2 different shoulder-abduction loads in 6 individuals with stroke. Results. We found a decreased accuracy in detecting hand opening when an individual with stroke intends to open the hand while activating shoulder abductors. However, such decreased accuracy with increased shoulder loading was not shown while detecting a hand-closing task. Conclusions. This study supports the idea that one should consider the effect of shoulder abduction activity when designing BMI classification algorithms for the purpose of restoring hand function in individuals with moderate to severe stroke.