EMG-controlled Virtual Reality to Improve Upper Extremity Function in Chronic Stroke Patients

NCT04154371 | Unknown

• 1 other identifier: BNL2019-1
• Study Type: interventional
• Target: 6
• Locations: 1 country
• Sites: 1

Brief Summary

This is a single subject design study to investigate the effectiveness of electromyography-controlled virtual reality and serious gaming treatment on upper extremity functionality in patients in the chronic recovery stage after stroke. The treatment consists of 18 sessions, 3 times per week, 2 hours each session. The investigator's hypothesis is that this treatment will improve upper limb functionality in our study population, this outcome will be measured with Fugl-Meyer Upper-Extremity (FMA-UE) and Action Research Arm Test (ARAT) tests and Kinematic analysis. In addition, we expect to see an increase in the strength of the affected limb and an increase in the embodiment of the upper limb trained.

Conditions

Stroke; Upper Extremity Dysfunction

Keywords

Electromyography; Virtual Reality

Outcome Measures

Primary Outcomes (2)

• Upper Extremity Scale of Fugl-Meyer Assessment

  The upper extremity portion of the Fugl-Meyer is a 33-item observational measure of upper limb function (Fugl-Meyer, et al., 1975). Each item is measured on an ordinal scale of 0-2 with 2 indicating normal functionality. The total score ranges from 0-66.

  3 times over 3 weeks immediately prior to intervention, once per week at the beginning of the session during intervention (6 weeks), 3 times over 3 weeks immediately after the end intervention, and once more 3 months after the end of intervention

• Action Research Arm Test

  The Action Research Arm Test is a 19-item observational measure of upper limb function (Lyle, 1981). Each item is measured on an ordinal scale of 0-3, with 3 indicating normal functionality. The total score ranges from 0-57.

  3 times over 3 weeks immediately prior to intervention, once per week at the beginning of the session during intervention (6 weeks), 3 times over 3 weeks immediately after the end intervention, and once more 3 months after the end of intervention

Secondary Outcomes (4)

• Kinematic Analysis

  Once in the 3 weeks immediately prior to intervention, once every other week during intervention at the beginning of the session, once in the 3 weeks immediately after the end of intervention, and once more 3 months after the end of intervention

• Embodiment Questionnaire

  Once in the 3 weeks immediately prior to intervention, once per week during the intervention at the end of the session, once in the 3 weeks immediately after the end of intervention, and once more 3 months after the end of intervention

• Thermography

  Once in the 3 weeks immediately prior to intervention, once in the 3 weeks immediately after the end of intervention, and once more 3 months after the end of intervention

• Grip Strength

  3 times over 3 weeks immediately prior to intervention, once per week at the beginning of the session during intervention (6 weeks), 3 times over 3 weeks immediately after the end intervention, and once more 3 months after the end of intervention

Other Outcomes (5)

• ABILHAND

  Once in the 3 weeks immediately prior to intervention, once in the 3 weeks immediately after the end of intervention, and once more 3 months after the end of intervention

• Stroke Impact Scale

  Once in the 3 weeks immediately prior to intervention, once in the 3 weeks immediately after the end of intervention, and once more 3 months after the end of intervention

• Barthel Index

  Once in the 3 weeks immediately prior to intervention, once in the 3 weeks immediately after the end of intervention, and once more 3 months after the end of intervention

Study Arms (1)

Single-arm or non-randomized trial

EXPERIMENTAL

Six post-stroke patients, in the chronic recovery stage, will receive a treatment in which motor execution is promoted by virtual and augmented reality using serious gaming controlled by myoelectric pattern recognition. The aim of this treatment is to improve upper limb functionality.

Device: Electromyography-controlled virtual and augmented reality using serious gaming

Interventions

Electromyography-controlled virtual and augmented reality using serious gaming DEVICE

Surface electrodes and a tracking marker are placed on the subject's affected upper extremity. Electrodes are placed on active muscle sites along the affected extremity determined by palpation. Electrodes are connected to an electromyography recording device, and signal acquisition and processing software are used to record EMG signals and display feedback. Myoelectric signals are used to control a virtual limb on the screen. The intervention consists of different steps: virtual reality, augmented reality, and serious gaming, which the participant must control with their muscle activity, record by EMG, in their affected limb.

Single-arm or non-randomized trial

Eligibility Criteria

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

You may qualify if:

• Able to sign an informed consent document
• Detectable muscle signals in the affected upper limb.
• Age between 18 and 80 years of age
• Montreal Cognitive Assessment test score of at least 22
• At least 6 months after stroke
• Experiencing upper-limb weakness, paralysis, or other loss of functionality
• Having a score below 50 on the Fugl-Meyer Assessment - Upper Extremity score
• Modified Ashworth score (0-5) of less than 3 pts
• Able to communicate and follow instructions needed for assessment and intervention adherence

You may not qualify if:

• Patients who are blind
• Presence of a condition or abnormality that in the opinion of the investigator would compromise the safety of the patient or the quality of the data
• Patients who have open wounds or other acute complications on their arms

Sponsors & Collaborators

• Chalmers University of Technology: lead
• Sahlgrenska University Hospital: collaborator
• Göteborg University: collaborator

Study Sites (1)

Chalmers University of Technology

Gothenburg, 41701, Sweden

Location

Related Publications (18)

• Socialstyrelsen, "Statistical Database: In-Patient Care Diagnosis." [Online]. Available: http://www.socialstyrelsen.se/statistics/statisticaldatabase/. [Accessed: 14-Jan-2018].

  BACKGROUND

• Raffin E, Hummel FC. Restoring Motor Functions After Stroke: Multiple Approaches and Opportunities. Neuroscientist. 2018 Aug;24(4):400-416. doi: 10.1177/1073858417737486. Epub 2017 Nov 7.

  PMID: 29283026 BACKGROUND

• Miller ET, Easton KL. Perceived losses following stroke. Rehabil Nurs. 2000 Sep-Oct;25(5):192-5. doi: 10.1002/j.2048-7940.2000.tb01904.x. No abstract available.

  PMID: 11998085 BACKGROUND

• Woodman P, Riazi A, Pereira C, Jones F. Social participation post stroke: a meta-ethnographic review of the experiences and views of community-dwelling stroke survivors. Disabil Rehabil. 2014;36(24):2031-43. doi: 10.3109/09638288.2014.887796. Epub 2014 Mar 6.

  PMID: 24597937 BACKGROUND

• Lang CE, Bland MD, Bailey RR, Schaefer SY, Birkenmeier RL. Assessment of upper extremity impairment, function, and activity after stroke: foundations for clinical decision making. J Hand Ther. 2013 Apr-Jun;26(2):104-14;quiz 115. doi: 10.1016/j.jht.2012.06.005. Epub 2012 Sep 10.

  PMID: 22975740 BACKGROUND

• M. Klocek, "Quality of life after stroke," in Health-Related Quality of Life in Cardiovascular Patients, 2013.

  BACKGROUND

• Lyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res. 1981;4(4):483-92. doi: 10.1097/00004356-198112000-00001. No abstract available.

  PMID: 7333761 BACKGROUND

• Perez-Marcos D. Virtual reality experiences, embodiment, videogames and their dimensions in neurorehabilitation. J Neuroeng Rehabil. 2018 Nov 26;15(1):113. doi: 10.1186/s12984-018-0461-0.

  PMID: 30477527 BACKGROUND

• Ortiz-Catalan M, Guethmundsdottir RA, Kristoffersen MB, Zepeda-Echavarria A, Caine-Winterberger K, Kulbacka-Ortiz K, Widehammar C, Eriksson K, Stockselius A, Ragno C, Pihlar Z, Burger H, Hermansson L. Phantom motor execution facilitated by machine learning and augmented reality as treatment for phantom limb pain: a single group, clinical trial in patients with chronic intractable phantom limb pain. Lancet. 2016 Dec 10;388(10062):2885-2894. doi: 10.1016/S0140-6736(16)31598-7. Epub 2016 Dec 2.

  PMID: 27916234 BACKGROUND

• Woytowicz EJ, Rietschel JC, Goodman RN, Conroy SS, Sorkin JD, Whitall J, McCombe Waller S. Determining Levels of Upper Extremity Movement Impairment by Applying a Cluster Analysis to the Fugl-Meyer Assessment of the Upper Extremity in Chronic Stroke. Arch Phys Med Rehabil. 2017 Mar;98(3):456-462. doi: 10.1016/j.apmr.2016.06.023. Epub 2016 Aug 9.

  PMID: 27519928 BACKGROUND

• Simon AM, Hargrove LJ, Lock BA, Kuiken TA. Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses. J Rehabil Res Dev. 2011;48(6):619-27. doi: 10.1682/jrrd.2010.08.0149.

  PMID: 21938650 BACKGROUND

• MAHONEY FI, BARTHEL DW. FUNCTIONAL EVALUATION: THE BARTHEL INDEX. Md State Med J. 1965 Feb;14:61-5. No abstract available.

  PMID: 14258950 BACKGROUND

• Fugl-Meyer AR, Jaasko L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scand J Rehabil Med. 1975;7(1):13-31.

  PMID: 1135616 BACKGROUND

• Moseley GL, Olthof N, Venema A, Don S, Wijers M, Gallace A, Spence C. Psychologically induced cooling of a specific body part caused by the illusory ownership of an artificial counterpart. Proc Natl Acad Sci U S A. 2008 Sep 2;105(35):13169-73. doi: 10.1073/pnas.0803768105. Epub 2008 Aug 25.

  PMID: 18725630 BACKGROUND

• Alt Murphy M, Willen C, Sunnerhagen KS. Kinematic variables quantifying upper-extremity performance after stroke during reaching and drinking from a glass. Neurorehabil Neural Repair. 2011 Jan;25(1):71-80. doi: 10.1177/1545968310370748. Epub 2010 Sep 9.

  PMID: 20829411 BACKGROUND

• Penta M, Tesio L, Arnould C, Zancan A, Thonnard JL. The ABILHAND questionnaire as a measure of manual ability in chronic stroke patients: Rasch-based validation and relationship to upper limb impairment. Stroke. 2001 Jul;32(7):1627-34. doi: 10.1161/01.str.32.7.1627.

  PMID: 11441211 BACKGROUND

• Duncan PW, Bode RK, Min Lai S, Perera S; Glycine Antagonist in Neuroprotection Americans Investigators. Rasch analysis of a new stroke-specific outcome scale: the Stroke Impact Scale. Arch Phys Med Rehabil. 2003 Jul;84(7):950-63. doi: 10.1016/s0003-9993(03)00035-2.

  PMID: 12881816 BACKGROUND

• Munoz-Novoa M, Kristoffersen MB, Sunnerhagen KS, Naber A, Ortiz-Catalan M, Alt Murphy M. Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study. J Neuroeng Rehabil. 2025 Jan 17;22(1):6. doi: 10.1186/s12984-025-01541-y.

  PMID: 39825410 DERIVED

MeSH Terms

Conditions

Stroke

Condition Hierarchy (Ancestors)

Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases

Study Officials

• Max Ortiz Catalan, PHD

  Chalmers University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: October 31, 2019
• First Posted: November 6, 2019
• Study Start: November 11, 2019
• Primary Completion: January 20, 2022
• Study Completion: December 20, 2022
• Last Updated: March 9, 2022

Record last verified: 2022-03

Data Sharing

• IPD Sharing: Will not share

Locations

SE (1)