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Web application for motor rehabilitation after stroke based on neuroeconomic approaches
Background and Aims:Learned non-use is a substantial problem for neurorehabilitation and it represents the difference between the functional capacity of an affected limb (e.g. based on the Fugl-Mayer scale) and the actual use of this limb in a daily life (e.g. using AAUT scale). Although the Constraint-Induced Therapy has proved its effectiveness, this approach has some methodological limitations, and it does not always guarantee active use of the affected limb after discharge from clinical premises. Regardless of an introduction of the International Classification of Functioning (ICF), which aims to integrate biological, psychological, and social factors for effective individualized rehabilitation protocols, rehabilitation is still on its way to becoming an ecological intervention. Nowadays, researchers are actively investigating possible directions towards making rehabilitation more patient-oriented, hence stimulating active participation in the treatment procedures. Methods: We developed a web application for stroke patients to investigate their motor decision making. The software is developed using the Blazor web framework. It allows to trace hand movements using the touch screen. Results: Web application is available by https://risk-n-reach. azurewebsites.net/. Two aims, sure and risky, are available for reaching by subject’s hand during each trial. Baseline stage consists of determining the probabilities of reaching a ‘risky’ aim at its different positions on a screen. After baseline stage it’s possible to suggest scores dependent on a ‘risky’ aim position. Conclusions: We expect that investigation of neuroeconomic parameters of motor decision making will be a step forward, which will help to overcome the learned non-use problem in stroke patients.