Tailored robotic training improves hand function and proprioceptive processing in stroke survivors with proprioceptive deficits: A randomized controlled trial
Andria J. Farrens, Luis Garcia-Fernandez, Raymond Diaz Rojas, Jillian Obeso Estrada, Dylan Reinsdorf, Vicky Chan, Disha Gupta, Joel Perry, Eric Wolbrecht, An Do, Steven C. Cramer, David J. Reinkensmeyer

TL;DR
This study demonstrates that proprioceptively-tailored robotic training significantly improves hand function and neural proprioceptive processing in stroke survivors with deficits, supporting personalized neurorehabilitation approaches.
Contribution
It introduces two novel proprioceptive training methods using robotic exoskeletons and shows their effectiveness in enhancing hand function and neural processing in stroke rehabilitation.
Findings
Propriopixel training improved hand function in stroke survivors with proprioceptive deficits.
Proprioceptive gains were correlated with functional improvements.
Neural sensitivity to proprioception increased, evidenced by a new EEG biomarker.
Abstract
Precision rehabilitation aims to tailor movement training to improve outcomes. We tested whether proprioceptively-tailored robotic training improves hand function and neural processing in stroke survivors. Using a robotic finger exoskeleton, we tested two proprioceptively-tailored approaches: Propriopixel Training, which uses robot-facilitated, gamified movements to enhance proprioceptive processing, and Virtual Assistance Training, which reduces robotic aid to increase reliance on self-generated feedback. In a randomized controlled trial, forty-six chronic stroke survivors completed nine 2-hour sessions of Standard, Propriopixel or Virtual training. Among participants with proprioceptive deficits, Propriopixel ((Box and Block Test: 7 +/- 4.2, p=0.002) and Virtual Assistance (4.5 +/- 4.4 , p=0.068) yielded greater gains in hand function (Standard: 0.8 +/- 2.3 blocks). Proprioceptive…
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Taxonomy
TopicsStroke Rehabilitation and Recovery · Virtual Reality Applications and Impacts · EEG and Brain-Computer Interfaces
