# Optimizing Hand Rehabilitation Post-Stroke Using Interactive Virtual Environments

> **NIH NIH R01** · NEW JERSEY INSTITUTE OF TECHNOLOGY · 2020 · $689,747

## Abstract

Project Abstract
This application seeks funding to continue our on-going investigation into the effects of intensive, high dosage
task and impairment based training of the hemiparetic hand, using haptic robots integrated with complex
gaming and virtual reality simulations. A growing body of work suggests that there is a time-limited period of
post-ischemic heightened neuronal plasticity during which intensive training may optimally affect the recovery
of gross motor skills, indicating that the timing of rehabilitation is as important as the dosing. However, recent
literature indicates a controversy regarding both the value of intensive, high dosage as well as the optimal
timing for therapy in the first two months after stroke. Our study is designed to empirically investigate this
controversy. Furthermore, current service delivery models in the United States limit treatment time and length
of hospital stay during this period. In order to facilitate timely discharge from the acute care hospital or the
acute rehabilitation setting, the initial priority for rehabilitation is independence in transfers and ambulation.
This has negatively impacted the provision of intensive hand and upper extremity therapy during this period of
heightened neuroplasticity. It is evident that providing additional, intensive therapy during the acute
rehabilitation stay is more complicated to implement and difficult for patients to tolerate, than initiating it in the
outpatient setting, immediately after discharge. Our pilot data show that we are able to integrate intensive,
targeted hand therapy into the routine of an acute rehabilitation setting. Our system has been specifically
designed to deliver hand training when motion and strength are limited. The system uses adaptive algorithms
to drive individual finger movement, gain adaptation and workspace modification to increase finger range of
motion, and haptic and visual feedback from mirrored movements to reinforce motor networks in the lesioned
hemisphere. We will translate the extensive experience gained in our previous studies on patients in the
chronic phase, to investigate the effects of this type of intervention on recovery and function of the hand, when
the training is initiated within early period of heightened plasticity. We will integrate the behavioral, the
kinematic/kinetic and neurophysiological aspects of recovery to determine: 1) whether early intensive training
focusing on the hand will result in a more functional hemiparetic arm; (2) whether it is necessary to initiate
intensive hand therapy during the very early inpatient rehabilitation phase or will comparable outcomes be
achieved if the therapy is initiated right after discharge, in the outpatient period; and 3) whether the effect of the
early intervention observed at 6 months post stroke can be predicted by the cortical reorganization evaluated
immediately after the therapy. This proposal will fill a critical gap in the literature and make a significa...

## Key facts

- **NIH application ID:** 9951071
- **Project number:** 5R01HD058301-08
- **Recipient organization:** NEW JERSEY INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** SERGEI V ADAMOVICH
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $689,747
- **Award type:** 5
- **Project period:** 2009-03-05 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9951071

## Citation

> US National Institutes of Health, RePORTER application 9951071, Optimizing Hand Rehabilitation Post-Stroke Using Interactive Virtual Environments (5R01HD058301-08). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9951071. Licensed CC0.

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