Optimizing Hand Rehabilitation Post-Stroke Using Interactive Virtual Environments

NCT01072461 | Completed Phase 1

• 1 other identifier: 5R01HD058301-02
• Study Type: interventional
• Target: 55
• Locations: 1 country
• Sites: 1

Brief Summary

The complexity of sensorimotor control required for hand function as well as the wide range of recovery of manipulative abilities makes rehabilitation of the hand most challenging. The investigators past work has shown that training in a virtual environment (VE) using repetitive, adaptive algorithms has the potential to be an effective rehabilitation medium to facilitate motor recovery of hand function. These findings are in accordance with current neuroscience literature in animals and motor control literature in humans. The investigators are now in a position to refine and optimize elements of the training paradigms to enhance neuroplasticity. The investigators first aim tests if and how competition among body parts for neural representations stifles functional gains from different types of training regimens. The second aim tests the functional benefits of unilateral versus bilateral training regimens.The third aim tests whether functional improvements gained from training in a virtual environment transfer to other (untrained) skills in the real world.

Conditions

Cerebrovascular Accident; Hemiparesis; Hemiplegia

Keywords

Cerebrovascular Accident; Robotics; Virtual Reality; Rehabilitation; Neuroplasticity

Outcome Measures

Primary Outcomes (1)

• Change in Jebsen Test of Hand Function

  Two Weeks Prior to Training, Immediately Prior to Training, Immediately After Training, 3 Months After Training

Secondary Outcomes (5)

• Change in Wolf Motor Function Test

  Two Weeks Prior to Training, Immediately Prior to Training, Immediately After Training, 3 Months After Training

• Change in 9 Hole Peg Test

  Two Weeks Prior to Training, Immediately Prior to Training, Immediately After Training, 3 Months After Training

• Change in Box and Blocks Test

  Two Weeks Prior to Training, Immediately Prior to Training, Immediately After Training, 3 Months After Training

• Change in Robotically Collected Kinematics

  1 day before training and 1 day after training

• Change in Reach to Grasp Test

  1 day before training and 1 day after training

Study Arms (3)

Train Paretic Hand and Arm Separate

ACTIVE COMPARATOR

Eight three hour training sessions of robotically facilitated hand and arm training in complex virtual environments, using activities that train the fingers in isolation and other activities that train the arm in isolation.

Behavioral: HAS Training

Train Paretic Hand and Arm Together

EXPERIMENTAL

Behavioral: HAT training

Train Both Hands Together in VE

EXPERIMENTAL

Behavioral: Bimanual Training

Interventions

HAS Training BEHAVIORAL

Robotically measured and facilitated training of the hemiparetic hand and arm in isolation, in a three dimensional haptically rendered virtual environment.

Also known as: Isolated UE training

Train Paretic Hand and Arm Separate

HAT training BEHAVIORAL

Robotically measured and facilitated training of the hemiparetic hand and arm as an integrated functional unit, in a three dimensional haptically rendered virtual environment

Also known as: Integrated UE training

Train Paretic Hand and Arm Together

Bimanual Training BEHAVIORAL

Robotically measured and facilitated training of the hemiparetic hand and non-hemiparetic hand together, in a three dimensional haptically rendered virtual environment

Also known as: Bilateral UE training

Train Both Hands Together in VE

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Six months post cerebrovascular accident
• Residual upper extremity impairment that affects participation
• At least ten degrees of active finger extension
• Tolerate passive shoulder flexion to chest level

You may not qualify if:

• Severe neglect
• Severe aphasia

Sponsors & Collaborators

• New Jersey Institute of Technology: lead
• Rutgers, The State University of New Jersey: collaborator

Study Sites (1)

New Jersey Institute of Technology

Newark, New Jersey, 07102, United States

Location

Related Publications (21)

• Adamovich SV, Fluet GG, Tunik E, Merians AS. Sensorimotor training in virtual reality: a review. NeuroRehabilitation. 2009;25(1):29-44. doi: 10.3233/NRE-2009-0497.

  PMID: 19713617 BACKGROUND

• Tunik E, Adamovich SV. Remapping in the ipsilesional motor cortex after VR-based training: a pilot fMRI study. Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:1139-42. doi: 10.1109/IEMBS.2009.5335392.

  PMID: 19965144 BACKGROUND

• Fluet GG, Merians AS, Qiu Q, Lafond I, Saleh S, Ruano V, Delmonico AR, Adamovich SV. Robots integrated with virtual reality simulations for customized motor training in a person with upper extremity hemiparesis: a case study. J Neurol Phys Ther. 2012 Jun;36(2):79-86. doi: 10.1097/NPT.0b013e3182566f3f.

  PMID: 22592063 BACKGROUND

• Tunik E, Saleh S, Adamovich SV. Visuomotor discordance during visually-guided hand movement in virtual reality modulates sensorimotor cortical activity in healthy and hemiparetic subjects. IEEE Trans Neural Syst Rehabil Eng. 2013 Mar;21(2):198-207. doi: 10.1109/TNSRE.2013.2238250. Epub 2013 Jan 9.

  PMID: 23314780 BACKGROUND

• Bagce HF, Saleh S, Adamovich SV, Krakauer JW, Tunik E. Corticospinal excitability is enhanced after visuomotor adaptation and depends on learning rather than performance or error. J Neurophysiol. 2013 Feb;109(4):1097-106. doi: 10.1152/jn.00304.2012. Epub 2012 Nov 28.

  PMID: 23197454 BACKGROUND

• Bagce HF, Saleh S, Adamovich SV, Tunik E. Visuomotor gain distortion alters online motor performance and enhances primary motor cortex excitability in patients with stroke. Neuromodulation. 2012 Jul;15(4):361-6. doi: 10.1111/j.1525-1403.2012.00467.x. Epub 2012 Jun 1.

  PMID: 22672345 BACKGROUND

• Saleh S, Adamovich SV, Tunik E. Resting state functional connectivity and task-related effective connectivity changes after upper extremity rehabilitation: a pilot study. Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:4559-62. doi: 10.1109/EMBC.2012.6346981.

  PMID: 23366942 BACKGROUND

• Saleh S, Adamovich SV, Tunik E. Mirrored feedback in chronic stroke: recruitment and effective connectivity of ipsilesional sensorimotor networks. Neurorehabil Neural Repair. 2014 May;28(4):344-54. doi: 10.1177/1545968313513074. Epub 2013 Dec 26.

  PMID: 24370569 BACKGROUND

• Yarossi M, Adamovich S, Tunik E. Sensorimotor cortex reorganization in subacute and chronic stroke: A neuronavigated TMS study. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:5788-91. doi: 10.1109/EMBC.2014.6944943.

  PMID: 25571311 BACKGROUND

• Schettino LF, Adamovich SV, Bagce H, Yarossi M, Tunik E. Disruption of activity in the ventral premotor but not the anterior intraparietal area interferes with on-line correction to a haptic perturbation during grasping. J Neurosci. 2015 Feb 4;35(5):2112-7. doi: 10.1523/JNEUROSCI.3000-14.2015.

  PMID: 25653367 BACKGROUND

• Qiu Q, Fluet GG, Lafond I, Merians AS, Adamovich SV. Coordination changes demonstrated by subjects with hemiparesis performing hand-arm training using the NJIT-RAVR robotically assisted virtual rehabilitation system. Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:1143-6. doi: 10.1109/IEMBS.2009.5335384.

  PMID: 19965145 RESULT

• Adamovich SV, Fluet GG, Merians AS, Mathai A, Qiu Q. Incorporating haptic effects into three-dimensional virtual environments to train the hemiparetic upper extremity. IEEE Trans Neural Syst Rehabil Eng. 2009 Oct;17(5):512-20. doi: 10.1109/TNSRE.2009.2028830. Epub 2009 Aug 7.

  PMID: 19666345 RESULT

• Adamovich SV, Fluet GG, Mathai A, Qiu Q, Lewis J, Merians AS. Design of a complex virtual reality simulation to train finger motion for persons with hemiparesis: a proof of concept study. J Neuroeng Rehabil. 2009 Jul 17;6:28. doi: 10.1186/1743-0003-6-28.

  PMID: 19615045 RESULT

• Merians AS, Fluet GG, Qiu Q, Saleh S, Lafond I, Davidow A, Adamovich SV. Robotically facilitated virtual rehabilitation of arm transport integrated with finger movement in persons with hemiparesis. J Neuroeng Rehabil. 2011 May 16;8:27. doi: 10.1186/1743-0003-8-27.

  PMID: 21575185 RESULT

• Fluet GG, Merians AS, Qiu Q, Davidow A, Adamovich SV. Comparing integrated training of the hand and arm with isolated training of the same effectors in persons with stroke using haptically rendered virtual environments, a randomized clinical trial. J Neuroeng Rehabil. 2014 Aug 23;11:126. doi: 10.1186/1743-0003-11-126.

  PMID: 25148846 RESULT

• Fluet GG, Merians AS, Qiu Q, Rohafaza M, VanWingerden AM, Adamovich SV. Does training with traditionally presented and virtually simulated tasks elicit differing changes in object interaction kinematics in persons with upper extremity hemiparesis? Top Stroke Rehabil. 2015 Jun;22(3):176-84. doi: 10.1179/1074935714Z.0000000008. Epub 2015 Jan 22.

  PMID: 26084322 RESULT

• Puthenveettil S, Fluet G, Qiu Q, Adamovich S. Classification of hand preshaping in persons with stroke using Linear Discriminant Analysis. Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:4563-6. doi: 10.1109/EMBC.2012.6346982.

  PMID: 23366943 RESULT

• Boos A, Qiu Q, Fluet GG, Adamovich SV. Haptically facilitated bimanual training combined with augmented visual feedback in moderate to severe hemiplegia. Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:3111-4. doi: 10.1109/IEMBS.2011.6090849.

  PMID: 22254998 RESULT

• Qiu Q, Adamovich S, Saleh S, Lafond I, Merians AS, Fluet GG. A comparison of motor adaptations to robotically facilitated upper extremity task practice demonstrated by children with cerebral palsy and adults with stroke. IEEE Int Conf Rehabil Robot. 2011;2011:5975431. doi: 10.1109/ICORR.2011.5975431.

  PMID: 22275632 RESULT

• Rohafza M, Fluet GG, Qiu Q, Adamovich S. Correlations between statistical models of robotically collected kinematics and clinical measures of upper extremity function. Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:4120-3. doi: 10.1109/EMBC.2012.6346873.

  PMID: 23366834 RESULT

• Rohafza M, Fluet GG, Qiu Q, Adamovich S. Correlation of reaching and grasping kinematics and clinical measures of upper extremity function in persons with stroke related hemiplegia. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:3610-3. doi: 10.1109/EMBC.2014.6944404.

  PMID: 25570772 RESULT

MeSH Terms

Conditions

Stroke; Paresis; Hemiplegia

Condition Hierarchy (Ancestors)

Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Paralysis

Study Officials

• Sergei V. Adamovich, PhD

  New Jersey Institute of Technology

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: phase 1
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, OUTCOMES ASSESSOR
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: February 16, 2010
• First Posted: February 22, 2010
• Study Start: March 1, 2009
• Primary Completion: March 1, 2013
• Study Completion: March 1, 2015
• Last Updated: October 7, 2015

Record last verified: 2015-10

Locations

US (1)