TY - GEN
T1 - EEG and Motor Effects of Multimodal Feedback to Train Functional Grasp after Traumatic Brain Injury
AU - Liu, Mingxiao
AU - Wilder, Samuel
AU - Sanford, Sean
AU - Dewil, Sophie
AU - Saleh, Soha
AU - Nataraj, Raviraj
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Physical therapy is crucial to rehabilitating hand function needed for activities of daily living after neurological traumas such as traumatic brain injury (TBI). Virtual reality (VR) can motivate participation in motor rehabilitation therapies. Computerized interfaces like VR could be further leveraged to provide augmented feedback during training that accelerates motor learning. In prior work, our lab demonstrated improved performance of a functional grasp task after training with augmented feedback from a 'smart' glove. The glove has modules and computational intelligence to detect and cue users about secure grasp. In this study, we incorporated VR with the glove to enhance the augmented feedback. We then examined how multimodal (audio and visual cues) feedback impacted performance and neurological responses compared to unimodal feedback (audio cues only) after TBI (n=5) versus neurotypicals (n=10). After training with multimodal feedback for a grasp-and-place task, electroencephalography (EEG) alpha power significantly increased for TBI and neurotypical groups. However, only the TBI group significantly improved performance (i.e., reduced motion pathlength). These results suggest a neurological basis for the benefits of training with multimodal feedback. Adding sensory cues may better consolidate early motor learning in the presence of neurological dysfunction, as indicated by higher alpha activity with improved performance. Computerized interfaces such as virtual reality offer a powerful platform to customize rehabilitative training and improve functional outcomes according to specific neurological states.
AB - Physical therapy is crucial to rehabilitating hand function needed for activities of daily living after neurological traumas such as traumatic brain injury (TBI). Virtual reality (VR) can motivate participation in motor rehabilitation therapies. Computerized interfaces like VR could be further leveraged to provide augmented feedback during training that accelerates motor learning. In prior work, our lab demonstrated improved performance of a functional grasp task after training with augmented feedback from a 'smart' glove. The glove has modules and computational intelligence to detect and cue users about secure grasp. In this study, we incorporated VR with the glove to enhance the augmented feedback. We then examined how multimodal (audio and visual cues) feedback impacted performance and neurological responses compared to unimodal feedback (audio cues only) after TBI (n=5) versus neurotypicals (n=10). After training with multimodal feedback for a grasp-and-place task, electroencephalography (EEG) alpha power significantly increased for TBI and neurotypical groups. However, only the TBI group significantly improved performance (i.e., reduced motion pathlength). These results suggest a neurological basis for the benefits of training with multimodal feedback. Adding sensory cues may better consolidate early motor learning in the presence of neurological dysfunction, as indicated by higher alpha activity with improved performance. Computerized interfaces such as virtual reality offer a powerful platform to customize rehabilitative training and improve functional outcomes according to specific neurological states.
KW - grasp
KW - rehabilitation
KW - traumatic brain injury
KW - virtual reality
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U2 - 10.1109/CBMS58004.2023.00246
DO - 10.1109/CBMS58004.2023.00246
M3 - Conference contribution
AN - SCOPUS:85166485412
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
SP - 374
EP - 377
BT - Proceedings - 2023 IEEE 36th International Symposium on Computer-Based Medical Systems, CBMS 2023
A2 - Sicilia, Rosa
A2 - Kane, Bridget
A2 - Almeida, Joao Rafael
A2 - Spiliopoulou, Myra
A2 - Andrades, Jose Alberto Benitez
A2 - Placidi, Giuseppe
A2 - Gonzalez, Alejandro Rodriguez
T2 - 36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023
Y2 - 22 June 2023 through 24 June 2023
ER -