12984_2023_1301_MOESM1_ESM.docx (4.73 MB)
Additional file 1 of Decoding hand and wrist movement intention from chronic stroke survivors with hemiparesis using a user-friendly, wearable EMG-based neural interface
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posted on 2024-01-14, 04:21 authored by Eric C. Meyers, David Gabrieli, Nick Tacca, Lauren Wengerd, Michael Darrow, Bryan R. Schlink, Ian Baumgart, David A. FriedenbergAdditional file 1. Supplementary Data.
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session data producedhealth care professionals34 ± 1150 embedded electrodes1 ± 5two fundamental movementsacross three movementsacross 12 movementsdecoding algorithm trained12 functional handwrist movement intentionmeet user needsincluding multiple typesform factor designedneurolife emg systemchronic stroke survivorssevere hand impairmentdemonstrate accurate decodingwearable forearm sleeve4 ± 6decode surface emgdecoding handforearm movementsform factorwearable emgstroke survivorssystem indicatessurface electromyographyresolution emgemg ).stroke populationvarying levelsupper extremitytime controlspecifically callingsleeve ’research settingspromising methodplatform technologyonline scenariosoften limitedmain resultsinvestigational useinvestigational devicehome withouthemiparesis usingfive percentfederal lawexpert technicianexisting technologiesdecode highcurrently limitedcontrol mechanismassociated hardwareassistive technologiesassistive devices
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