OBJECTIVE: Brain-computer interface (BCI) technology is attracting increasing interest as a tool for enhancing recovery of motor function after stroke, yet the optimal way to apply this technology is unknown. Here, we studied the immediate and therapeutic effects of BCI-based training to control pre-movement sensorimotor rhythm (SMR) amplitude on robot-assisted finger extension in people with stroke. APPROACH: Eight people with moderate to severe hand impairment due to chronic stroke completed a four-week three-phase protocol during which they practiced finger extension with assistance from the FINGER robotic exoskeleton. In Phase 1, we identified spatiospectral SMR features for each person that correlated with the intent to extend the index and/or middle finger(s). In Phase 2, the participants learned to increase or decrease SMR features given visual feedback, without movement. In Phase 3, the participants were cued to increase or decrease their SMR features, and when successful, were then cued to immediately attempt to extend the finger(s) with robot assistance. MAIN RESULTS: Of the four participants that achieved SMR control in Phase 2, three initiated finger extensions with a reduced reaction time after decreasing (versus increasing) pre-movement SMR amplitude during Phase 3. Two also extended at least one of their fingers more forcefully after decreasing pre-movement SMR amplitude. Hand function, measured by the box and block test (BBT), improved by 7.3 ± 7.5 blocks versus 3.5 ± 3.1 blocks in those with and without SMR control, respectively. Higher BBT scores at baseline correlated with a larger change in BBT score. SIGNIFICANCE: These results suggest that learning to control person-specific pre-movement SMR features associated with finger extension can improve finger extension ability after stroke for some individuals. These results merit further investigation in a rehabilitation context.
OBJECTIVE: Brain-computer interface (BCI) technology is attracting increasing interest as a tool for enhancing recovery of motor function after stroke, yet the optimal way to apply this technology is unknown. Here, we studied the immediate and therapeutic effects of BCI-based training to control pre-movement sensorimotor rhythm (SMR) amplitude on robot-assisted finger extension in people with stroke. APPROACH: Eight people with moderate to severe hand impairment due to chronic stroke completed a four-week three-phase protocol during which they practiced finger extension with assistance from the FINGER robotic exoskeleton. In Phase 1, we identified spatiospectral SMR features for each person that correlated with the intent to extend the index and/or middle finger(s). In Phase 2, the participants learned to increase or decrease SMR features given visual feedback, without movement. In Phase 3, the participants were cued to increase or decrease their SMR features, and when successful, were then cued to immediately attempt to extend the finger(s) with robot assistance. MAIN RESULTS: Of the four participants that achieved SMR control in Phase 2, three initiated finger extensions with a reduced reaction time after decreasing (versus increasing) pre-movement SMR amplitude during Phase 3. Two also extended at least one of their fingers more forcefully after decreasing pre-movement SMR amplitude. Hand function, measured by the box and block test (BBT), improved by 7.3 ± 7.5 blocks versus 3.5 ± 3.1 blocks in those with and without SMR control, respectively. Higher BBT scores at baseline correlated with a larger change in BBT score. SIGNIFICANCE: These results suggest that learning to control person-specific pre-movement SMR features associated with finger extension can improve finger extension ability after stroke for some individuals. These results merit further investigation in a rehabilitation context.
Authors: Sumner Norman; Mark Dennison; Eric Wolbrecht; Steven Cramer; Ramesh Srinivasan; David Reinkensmeyer Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2016-02-11 Impact factor: 3.802
Authors: S C Cramer; G Nelles; R R Benson; J D Kaplan; R A Parker; K K Kwong; D N Kennedy; S P Finklestein; B R Rosen Journal: Stroke Date: 1997-12 Impact factor: 7.914
Authors: Eric T Wolbrecht; Justin B Rowe; Vicky Chan; Morgan L Ingemanson; Steven C Cramer; David J Reinkensmeyer Journal: Clin Neurophysiol Date: 2018-02-03 Impact factor: 3.708
Authors: Sumner L Norman; David Maresca; Vassilios N Christopoulos; Whitney S Griggs; Charlie Demene; Mickael Tanter; Mikhail G Shapiro; Richard A Andersen Journal: Neuron Date: 2021-03-22 Impact factor: 17.173
Authors: Paul Dominick E Baniqued; Emily C Stanyer; Muhammad Awais; Ali Alazmani; Andrew E Jackson; Mark A Mon-Williams; Faisal Mushtaq; Raymond J Holt Journal: J Neuroeng Rehabil Date: 2021-01-23 Impact factor: 4.262
Authors: Quentin Sanders; Vicky Chan; Renee Augsburger; Steven C Cramer; David J Reinkensmeyer; An H Do Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2020-04-15 Impact factor: 4.528