A Gamified Electromyographic Computer Interface to Study the Emergence of Motor Control Abnormalities after Stroke
Adarsh Mavathaveedu1, Ania Busza2
1University of Rochester, 2Neurology, University of Rochester
Objective:
To characterize the evolution of motor control impairments in wrist flexor and extensor muscle groups over the first 3 months post-stroke.
Background:
Upper extremity (UE) disability is common after stroke. Prior studies in individuals with hemiparesis due to stroke have identified four distinct impairments of motor control: (1) decreased maximal muscle activation, (2) delayed muscle activation, (3) motor fatiguability, and (4) abnormal co-activation of antagonistic muscle groups. However, the factors predicting emergence of specific motor control abnormalities are unclear.
Design/Methods:
We have developed an electromyographic (EMG) computer interface to collect EMG signals from subjects performing repetitive muscle activations. Our EMG computer interface uses surface EMG signals from the wrist flexor and extensor muscle groups to control a computer game. Successful gameplay requires multiple isometric muscle contractions at precise time points. EMG data are analyzed to identify maximum EMG values, activation delay, and co-activation of antagonist muscle groups during gameplay. We are conducting a longitudinal study over the first 3 months post-stroke to study evolution of each impairment and identify factors that may predict specific motor control abnormalities in the chronic phase after stroke.
Results:
Preliminary results suggests that our system is well-tolerated and that subjects early (<10 days) after stroke exhibit decreased EMG amplitude and increased variability in activation onset of wrist flexor and extensors in their affected UE as compared to their unaffected arm. Some participants also show increased co-activation and increased motor fatigue in their paretic arm.
Conclusions:
Our EMG-controlled computer interface can be used to collect EMG data across multiple time points. With our current longitudinal study, we will assess the prevalence and individual trajectory of each motor impairment over the first 3 months post-stroke. Ultimately, we hope to use the information gained in this longitudinal study to develop personalized, impairment-specific interventions for motor recovery.