EMG-controlled Virtual Reality to Improve Upper Extremity Function in Chronic Stroke Patients
NCT ID: NCT04154371
Last Updated: 2022-03-09
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
6 participants
INTERVENTIONAL
2019-11-11
2022-12-20
Brief Summary
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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.
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Detailed Description
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The World Health Organization (WHO) defines stroke as rapidly developing clinical signs of focal or global disturbance of cerebral function, with symptoms lasting more than 24 hours or leading to death and with no apparent non-vascular cause. The incidence of stroke in Sweden is 300 cases per 100.000 inhabitants in a year of whom 200 suffer the first incidence of stroke leading to 18.000 new stroke victims. Of these, about 20% will die within the first month and about 1/3 of the survivors will remain significantly disabled after 6-12 months.
The upper extremity function is impaired after stroke in approximately 70-80% of patients in the acute phase and in 40% in chronic phase. This impairment limits the voluntary, well-coordinated, and effective movements as well as a person's level of activity and participation in their social and physical environment. This longstanding disability also affects the quality of life. Improved upper extremity function is one of the suggested areas for research by survivors of stroke.
Objectives
Primary Objective:
Investigate the effectiveness of electromyography-controlled augmented reality, and serious gaming on upper extremity functionality in patients in the chronic recovery stage after stroke, measure with FMA-UE and ARAT tests
Secondary Objectives:
* Investigate changes in the movement quality when performing a daily task using kinematic analysis and perceived difficulties in daily activities.
* Measure how strength changes on the affected limb after the treatment. Measure by a dynamometer.
* Measure with embodiment questioner if the treatment makes some changes on the embodiment of the affected limb.
* Measure with thermography the skin temperature differences between the affected and non-affected limb pre- and post-treatment.
Tertiary Objectives:
The tertiary objectives of this study are to investigate the effect of training on electromyography-based pattern recognition accuracy and Targeted Achievement Control scores, changes in kinematics, and changes in ABILHAND, Barthel index, muscle tone, and sensation scores in the affected limb over the recovery period.
Study Design
Inclusion and exclusion criteria for prospective patients will be addressed at the first measurement session. Baseline measurements will start at week 1 and, if necessary, inclusion and exclusion criteria will be reassessed.
Patients will undergo a single subject design (A-B-A-FU). Intervention stages are as follows:
A (Baseline). 2-3 weeks of no intervention with measurements taken once or twice per week, with a minimum of 3 assessments.
B (Intervention). 6 weeks of intervention three times per week with measurements taken once per week (18 sessions).
A (Reversal). 2-3 weeks of no intervention with measurements taken once or twice per week, with a minimum of 3 assessments.
FU (Follow-up). Follow-up measurements taken after 3 months without treatment.
Treatment Administration
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. If no active sites can be determined, electrodes are placed along with major muscle groups regardless of activation. Electrodes are fixed to an electromyography recording device, and signal acquisition and processing software (BioPatRec) is used to record electromyography (EMG) signals and display feedback. EMG signals are observed, and the most active electrode locations are documented and used for further experiments.
The subject should attempt to perform different hand and arm movements with the extremity indicated by a nearby computer screen while the computer records EMG signals from the arm (referred to as offline training). Agonist-antagonist movement pairs should always be used in combination when selecting movements. Treatment sessions should start with one movement pair at a time and progress to multiple and simultaneous movements as treatment progresses and the patients perform better with the system.
The computer system recognizes the different movements while the computer system records closely related EMG signals and will perform the subject's intended movements with a computer-simulated upper extremity.
The subject will then use previously recorded movements to control a computer-simulated limb and attempt to match limb positions indicated on the computer screen. The system will measure how fast and how efficiently the subject reaches the target position with the simulated extremity Targeted Achievement Control (TAC Test). TAC tests will initially involve control over one degree of freedom at a time, e.g. rotation of the wrist or open/close hand movements. As the patient gains better control of their affected extremity and learn to use the system, the difficulty of the TAC Tests will be increased by adding additional and simultaneous movements.
Duration of the Treatment:
Each intervention session should take approximately two hours. The intervention stage of the trial will last six weeks with three sessions per week, total of 18 sessions.
Conditions
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Study Design
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NA
SINGLE_GROUP
TREATMENT
NONE
Study Groups
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Single-arm or non-randomized trial
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.
Electromyography-controlled virtual and augmented reality using serious gaming
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.
Interventions
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Electromyography-controlled virtual and augmented reality using serious gaming
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.
Eligibility Criteria
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Inclusion Criteria
* 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
Exclusion Criteria
* 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
18 Years
80 Years
ALL
No
Sponsors
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Sahlgrenska University Hospital
OTHER
Göteborg University
OTHER
Chalmers University of Technology
OTHER
Responsible Party
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Max Ortiz Catalan
Associate Professor
Principal Investigators
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Max Ortiz Catalan, PHD
Role: PRINCIPAL_INVESTIGATOR
Chalmers University
Locations
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Chalmers University of Technology
Gothenburg, , Sweden
Countries
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References
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Socialstyrelsen, "Statistical Database: In-Patient Care Diagnosis." [Online]. Available: http://www.socialstyrelsen.se/statistics/statisticaldatabase/. [Accessed: 14-Jan-2018].
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.
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.
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.
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.
M. Klocek, "Quality of life after stroke," in Health-Related Quality of Life in Cardiovascular Patients, 2013.
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.
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.
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.
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.
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.
MAHONEY FI, BARTHEL DW. FUNCTIONAL EVALUATION: THE BARTHEL INDEX. Md State Med J. 1965 Feb;14:61-5. No abstract available.
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.
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.
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.
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.
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.
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.
Other Identifiers
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BNL2019-1
Identifier Type: -
Identifier Source: org_study_id
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