Predicting Gains With Visuospatial Training After Stroke Using an EEG Measure of Frontoparietal Circuit Function.

The heterogeneity of stroke prompts the need for predictors of individual treatment response to rehabilitation therapies. We previously studied healthy subjects with EEG and identified a frontoparietal circuit in which activity predicted training-related gains in visuomotor tracking. Here we asked whether activity in this same frontoparietal circuit also predicts training-related gains in visuomotor tracking in patients with chronic hemiparetic stroke. Subjects (n = 12) underwent dense-array EEG recording at rest, then received 8 sessions of visuomotor tracking training delivered via home-based telehealth methods. Subjects showed significant training-related gains in the primary behavioral endpoint, Success Rate score on a standardized test of visuomotor tracking, increasing an average of 24.2 ± 21.9% (p = 0.003). Activity in the circuit of interest, measured as coherence (20-30 Hz) between leads overlying ipsilesional frontal (motor cortex) and parietal lobe, significantly predicted training-related gains in visuomotor tracking change, measured as change in Success Rate score (r = 0.61, p = 0.037), supporting the main study hypothesis. Results were specific to the hypothesized ipsilesional motor-parietal circuit, as coherence within other circuits did not predict training-related gains. Analyses were repeated after removing the four subjects with injury to motor or parietal areas; this increased the strength of the association between activity in the circuit of interest and training-related gains. The current study found that (1) Eight sessions of training can significantly improve performance on a visuomotor task in patients with chronic stroke, (2) this improvement can be realized using home-based telehealth methods, (3) an EEG-based measure of frontoparietal circuit function predicts training-related behavioral gains arising from that circuit, as hypothesized and with specificity, and (4) incorporating measures of both neural function and neural injury improves prediction of stroke rehabilitation therapy effects.

Choice of Human-Computer Interaction Mode in Stroke Rehabilitation.

BACKGROUND AND OBJECTIVE: Advances in technology are providing new forms of human-computer interaction. The current study examined one form of human-computer interaction, augmented reality (AR), whereby subjects train in the real-world workspace with virtual objects projected by the computer. Motor performances were compared with those obtained while subjects used a traditional human-computer interaction, that is, a personal computer (PC) with a mouse. METHODS: Patients used goal-directed arm movements to play AR and PC versions of the Fruit Ninja video game. The 2 versions required the same arm movements to control the game but had different cognitive demands. With AR, the game was projected onto the desktop, where subjects viewed the game plus their arm movements simultaneously, in the same visual coordinate space. In the PC version, subjects used the same arm movements but viewed the game by looking up at a computer monitor. RESULTS: Among 18 patients with chronic hemiparesis after stroke, the AR game was associated with 21% higher game scores (P = .0001), 19% faster reaching times (P = .0001), and 15% less movement variability (P = .0068), as compared to the PC game. Correlations between game score and arm motor status were stronger with the AR version. CONCLUSIONS: Motor performances during the AR game were superior to those during the PC game. This result is due in part to the greater cognitive demands imposed by the PC game, a feature problematic for some patients but clinically useful for others. Mode of human-computer interface influences rehabilitation therapy demands and can be individualized for patients.

Comparing "pick and place" task in spatial Augmented Reality versus non-immersive Virtual Reality for rehabilitation setting.

Introducing computer games to the rehabilitation market led to development of numerous Virtual Reality (VR) training applications. Although VR has provided tremendous benefit to the patients and caregivers, it has inherent limitations, some of which might be solved by replacing it with Augmented Reality (AR). The task of pick-and-place, which is part of many activities of daily living (ADL's), is one of the major affected functions stroke patients mainly expect to recover. We developed an exercise consisting of moving an object between various points, following a flash light that indicates the next target. The results show superior performance of subjects in spatial AR versus non-immersive VR setting. This could be due to the extraneous hand-eye coordination which exists in VR whereas it is eliminated in spatial AR.