Na Jin Seo1, Alex Barry, Mohammad Ghassemi, Kristen M Triandafilou, Mary Ellen Stoykov, Lynn Vidakovic, Elliot Roth, Derek G Kamper. 1. Departments of Rehabilitation Sciences and Health Science and Research, Medical University of South Carolina, Charleston, and Ralph H. Johnson VA Medical Center, Charleston, South Carolina (N.J.S.); Shirley Ryan AbilityLab, Chicago, Illinois (A.B., K.M.T., M.E.S., L.V. E.R.); Joint Department of Biomedical Engineering, North Carolina State University/University of North Carolina at Chapel Hill, Raleigh, Chapel Hill (M.G., D.G.K); and Department of Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.E.S., L.V., E.R.).
Abstract
BACKGROUND/ PURPOSE: To determine the feasibility of training with electromyographically (EMG) controlled games to improve control of muscle activation patterns in stroke survivors. METHODS: Twenty chronic stroke survivors (>6 months) with moderate hand impairment were randomized to train either unilaterally (paretic only) or bilaterally over 9 one-hour training sessions. EMG signals from the unilateral or bilateral limbs controlled a cursor location on a computer screen for gameplay. The EMG muscle activation vector was projected onto the plane defined by the first 2 principal components of the activation workspace for the nonparetic hand. These principal components formed the x- and y-axes of the computer screen. RESULTS: The recruitment goal (n = 20) was met over 9 months, with no screen failure, no attrition, and 97.8% adherence rate. After training, both groups significantly decreased the time to move the cursor to a novel sequence of targets (P = 0.006) by reducing normalized path length of the cursor movement (P = 0.005), and improved the Wolf Motor Function Test (WMFT) quality score (P = 0.01). No significant group difference was observed. No significant change was seen in the WMFT time or Box and Block Test. DISCUSSION/ CONCLUSIONS: Stroke survivors could successfully use the EMG-controlled games to train control of muscle activation patterns. While the nonparetic limb EMG was used in this study to create target EMG patterns, the system supports various means for creating target patterns per user desires. Future studies will employ training with the EMG-controlled games in conjunction with functional task practice for a longer intervention duration to improve overall hand function.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A379).
BACKGROUND/ PURPOSE: To determine the feasibility of training with electromyographically (EMG) controlled games to improve control of muscle activation patterns in stroke survivors. METHODS: Twenty chronic stroke survivors (>6 months) with moderate hand impairment were randomized to train either unilaterally (paretic only) or bilaterally over 9 one-hour training sessions. EMG signals from the unilateral or bilateral limbs controlled a cursor location on a computer screen for gameplay. The EMG muscle activation vector was projected onto the plane defined by the first 2 principal components of the activation workspace for the nonparetic hand. These principal components formed the x- and y-axes of the computer screen. RESULTS: The recruitment goal (n = 20) was met over 9 months, with no screen failure, no attrition, and 97.8% adherence rate. After training, both groups significantly decreased the time to move the cursor to a novel sequence of targets (P = 0.006) by reducing normalized path length of the cursor movement (P = 0.005), and improved the Wolf Motor Function Test (WMFT) quality score (P = 0.01). No significant group difference was observed. No significant change was seen in the WMFT time or Box and Block Test. DISCUSSION/ CONCLUSIONS: Stroke survivors could successfully use the EMG-controlled games to train control of muscle activation patterns. While the nonparetic limb EMG was used in this study to create target EMG patterns, the system supports various means for creating target patterns per user desires. Future studies will employ training with the EMG-controlled games in conjunction with functional task practice for a longer intervention duration to improve overall hand function.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A379).
Authors: Emelia J Benjamin; Salim S Virani; Clifton W Callaway; Alanna M Chamberlain; Alexander R Chang; Susan Cheng; Stephanie E Chiuve; Mary Cushman; Francesca N Delling; Rajat Deo; Sarah D de Ferranti; Jane F Ferguson; Myriam Fornage; Cathleen Gillespie; Carmen R Isasi; Monik C Jiménez; Lori Chaffin Jordan; Suzanne E Judd; Daniel Lackland; Judith H Lichtman; Lynda Lisabeth; Simin Liu; Chris T Longenecker; Pamela L Lutsey; Jason S Mackey; David B Matchar; Kunihiro Matsushita; Michael E Mussolino; Khurram Nasir; Martin O'Flaherty; Latha P Palaniappan; Ambarish Pandey; Dilip K Pandey; Mathew J Reeves; Matthew D Ritchey; Carlos J Rodriguez; Gregory A Roth; Wayne D Rosamond; Uchechukwu K A Sampson; Gary M Satou; Svati H Shah; Nicole L Spartano; David L Tirschwell; Connie W Tsao; Jenifer H Voeks; Joshua Z Willey; John T Wilkins; Jason Hy Wu; Heather M Alger; Sally S Wong; Paul Muntner Journal: Circulation Date: 2018-01-31 Impact factor: 29.690
Authors: Na Jin Seo; Derek G Kamper; Viswanathan Ramakrishnan; Jillian B Harvey; Christian Finetto; Christian Schranz; Gabrielle Scronce; Kristen Coupland; Keith Howard; Jenna Blaschke; Adam Baker; Caitlyn Meinzer; Craig A Velozo; Robert J Adams Journal: Trials Date: 2022-04-12 Impact factor: 2.279