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Knee Biofeedback Rehabilitation Interface for Game-based Home Therapy for Patients With Knee Osteoarthritis (KneeBRIGHT)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04187092
Recruitment Status : Not yet recruiting
First Posted : December 5, 2019
Last Update Posted : December 5, 2019
Sponsor:
Collaborators:
National Institutes of Health (NIH)
Barron Associates, Inc.
Information provided by (Responsible Party):
Joseph Hart, University of Virginia

Brief Summary:

Osteoarthritis (OA) is the leading cause of disability in the United States. As osteoarthritis is associated with the lower limb muscle weakness, rehabilitation through quadriceps strengthening is a well-established treatment for patients with knee OA, but patient adherence to exercise routines is low due to lack of guidance regarding optimal protocols and lack of engagement during the repetitive routines that patients find tedious and boring.

The Knee Biofeedback Rehabilitation Interface for Game-based Home Therapy ("KneeBRIGHT") system combines electromyography (EMG) biofeedback with video game therapy to provide knee OA patients with an engaging, effective tool for conducting rehabilitation exercises at home. KneeBRIGHT aims to motivate patients with knee OA to conduct regular muscle strengthening exercise through an engaging, EMG-driven video game therapy.

Overall goal of the program is to improve knee OA outcomes through effective and motivating rehabilitation exercises. Participants will be randomized to two groups: (1) KneeBRIGHT group; (2) Standard rehabilitation group. Both groups will undergo baseline and follow up assessment to measure the patient-reported outcomes, thigh muscle strength, and balance. Participants in both groups will undergo a 12-week program including 3 exercise sessions per week that includes a combination of in-person and at home sessions. Pre and post intervention outcome measures will be compared to explore the effectiveness. Technology acceptance will also be studied in patients randomized to KneeBRIGHT group.


Condition or disease Intervention/treatment Phase
Osteo Arthritis Knee Other: KneeBright Group Other: Standard Rehabilitation group Not Applicable

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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 42 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Intervention Model Description:

Participants with knee osteoarthritis will be randomly assigned to Group 1 or 2. During each exercise session all the participants will perform stretching exercises, strengthening exercises and balance exercises. Dosage of exercises will be based on the rehabilitation principles and will be guided and progressed the way the participants feel about their knee health throughout the rehabilitation program.

Participants in Group1 (KneeBright group), will perform some of the exercises with the KneeBright Device and while playing a video game, while Group 2 will undergo standard knee rehabilitation exercises without the KneeBright device.

Both groups will undergo a 12 week program including 3 exercise sessions per week that include a combination of in-person and at home sessions. Participants in both groups will undergo 36 exercise sessions in total, each lasting for 1 hour. Among these 36 sessions 20 will be performed in clinic under supervision and 16 will be performed at home.

Masking: Single (Outcomes Assessor)
Masking Description: Outcome assessors will be blinded and will be responsible for executing the baseline and follow-up outcome measures. Assessors have the adequate training and experience for recording the patient reported outcome measures along with conducting the thigh muscle strength and balance testing.
Primary Purpose: Treatment
Official Title: Knee Biofeedback Rehabilitation Interface for Game-based Home Therapy ("KneeBRIGHT") Phase II
Estimated Study Start Date : December 1, 2019
Estimated Primary Completion Date : February 28, 2021
Estimated Study Completion Date : September 30, 2021

Resource links provided by the National Library of Medicine


Arm Intervention/treatment
Experimental: KneeBright group
Participants in this group will perform exercises aimed to improve the muscle strength, balance and precision. Participants will perform exercises three times a week for 12 weeks. Each session will last for an hour. Some of the exercises will be performed with the KneeBright Device while playing a video game.
Other: KneeBright Group

The KneeBRIGHT group will use KneeBright device which consists of an EMG biofeedback interface software that guides users through exercise routines. The wireless EMG sensors includes two small electrodes that will be made to stick to the quadriceps muscles both sides. KneeBRIGHT software features a virtual world wherein patients complete challenges controlling the in-game avatar with the EMG units during exercises specific to knee osteoarthritis rehabilitation.

The KneeBRIGHT software will incorporates a variety of exercises for strengthening the quadriceps and will employ algorithms based on the Daily Adjustable Progressive Resistance Exercise (DAPRE) technique, in which the quantity of repetitions performed in these sets is then used to determine the appropriate increase (or possibly decrease) in target resistance for the next sets/sessions.


Active Comparator: Standard Rehabilitation group
Participants in this group will perform exercises with the same focus and frequency. No exercises will be performed with the KneeBright device.
Other: Standard Rehabilitation group
Participants in this group will undergo standard clinic based knee rehabilitation. Both groups will perform exact same exercises, however, no KneeBRIGHT device will be used in this group.




Primary Outcome Measures :
  1. Change in Knee injury and osteoarthritis outcome score (KOOS) [ Time Frame: KOOS scores will be measured at baseline, day 1 and at the end of intervention, at 12 weeks. ]
    Knee function will be assessed by composite KOOS score prior to the study and will be compared to the KOOS score recorded post-intervention to test the primary hypothesis that patients conducting the KneeBRIGHT exercise will significantly improve knee function compared to the control group. Pre-intervention KOOS scores measures will be subtracted from the post-intervention scores.


Secondary Outcome Measures :
  1. Change in Peak torque of hip and thigh muscles strength testing [ Time Frame: Peak torque (muscle strength) will be measured at baseline, day 1 and at the end of intervention, at 12 weeks. ]

    Thigh muscle strength will be measured at baseline and follow up. Participants will be asked to perform thigh muscle contractions while measures of strength using a dynamometer (biodex system 4) are recorded.

    Participants will be asked to perform repeated, maximal muscle contractions bilaterally to test muscle strength and endurance of the hip and thigh muscles (knee flexion and extension, hip abduction and adduction). This test takes 25 minutes to complete.


  2. Change in Balance performance [ Time Frame: Balance will be tested at baseline, day 1 and at the end of intervention, at 12 weeks. ]
    Bilateral balance performance will be tested at the baseline and follow up. Participants will be asked to stand on a pressure mat for 30 seconds while balance measures are recorded. Participants will be asked to perform 2 repetitions on both right and left sides. Testing is performed by a blinded investigator with experience and training to perform these measures in patients with knee injuries.



Information from the National Library of Medicine

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Ages Eligible for Study:   40 Years to 75 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  • Age 40-75
  • Diagnosis of Osteoarthritis
  • Independent ambulation without assistive device

Exclusion Criteria:

  • Individuals who have psychiatric or cognitive impairment (e.g., dementia) that interferes with their ability to follow instructions or provide voluntary consent
  • Symptomatic spine, hip, ankle, or foot disease other than osteoarthritis that would interfere with assessment of the knee.
  • Balance or vestibular disorders
  • Peripheral neuropathy
  • Skin conditions that prevent EMG electrode placement
  • Prisoner
  • Pregnant (by report)
  • Non-English-speaking
  • Individuals who are visually and/or hearing impaired

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04187092


Contacts
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Contact: Joseph M Hart, PhD 434 243 0256 jmh3zf@virginia.edu
Contact: Mandeep Kaur, PhD mk6kz@virginia.edu

Locations
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United States, Virginia
University of Virginia
Charlottesville, Virginia, United States, 22903
Contact: Jospeph Hart, PhD    434-243-0256    Jmh3zf@virginia.edu   
Principal Investigator: Susan Saliba, PhD         
Principal Investigator: Joesph Hart, PhD         
Sub-Investigator: Eileen Krepkovich         
Sub-Investigator: William Gressick         
Sub-Investigator: Matthew Lichter         
Sub-Investigator: Aaron Olowin         
Sub-Investigator: Jeames Patrie         
Sub-Investigator: Neal Richardson         
Sub-Investigator: Christina Tieu         
Sponsors and Collaborators
University of Virginia
National Institutes of Health (NIH)
Barron Associates, Inc.
Investigators
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Principal Investigator: Joseph M Hart, PhD University of Virginia
  Study Documents (Full-Text)

Documents provided by Joseph Hart, University of Virginia:

Additional Information:
Publications:
Adams RJ. Strength and BALance (SABAL) Virtual Trainer. NIA: 1R41AG046958-01A1, 2015.
Chen H, Rong W, Ma X, Qu,Y and Xiong Z. An Extended Technology Acceptance Model for MobileSocial Gaming Service Popularity Analysis. Mobile Information Systems, vol. 2017. doi:10.1155/2017/3906953
Creating healthcare data applications to promote HIPAA and HITECH Compliance. Amazon Web Services. http://aws.amazon.com/compliance/#hipaa
Davis FD. Perceived Usefulness, Ease of Use, and User Acceptance of IT. MIS Quarterly. 1989;13(3):319-40.
Fetscherin M, Lattemann C, User Acceptance of Virtual Worlds. J Electronic Comm Research. 2008; 9(3):231-42.
Khaled Takey ,Olfat A. Kandil, and, Shimaa N. Abo Elazm. Isokinetic quadriceps peak torque, average power and total work at different angular knee velocities of physical therapy for internal medicine its surgery and geriatrics , Basic Science Dept. 1, 2,3 Misr University for science and technology.
Laferriere P, Lemaire ED, Chan ADC. Surface Electromyographic Signals Using Dry Electrodes. IEEE Trans Ins Meas 60(10): 3259- 3268, 2011.
Lyons GM, Sharma P, Baker M, O'Malley S, Shanahan A, A computer game-based EMG biofeedback system for muscle rehabilitation. Proc 25th Annual International Conference of the IEEE Eng Med Biol Society, 2003, 2:1625 - 8.
MarketResearch.com,
McCreadie C, Tinker A. The acceptability of assistive technology to older people. Ageing and Society 2005;25(1);91-110.
National Center for Chronic Disease Prevention and Health Promotion. Arthritis: Meeting the Challenge of living well (2013). Report available through: http://www.cdc.gov/chronicdisease/resources/publications/aag/pdf/2013/arthritis-aag-2013_508.pdf
Ostir GV, Cohen-Mansfield J, Leveille S, Volpto S and Guralnik JM. The association of positive and negative affect and exercise self-efficacy in older adults. J Aging Phys Act 2003; 11: 265-74.
Parker E. A new approach to vision therapy based on naturalistic 3-D computer gaming. NEI: 5R44EY021079-04, 2013.
Parker E. A wireless EMG data collection and analysis system. NIAMS: 5R44AR047274-03, 2004.
Rigby C and Przybylski A. Virtual worlds and the learner hero: How today's video games can inform tomorrow's digital learning environments. Theory and Research in Education. 2009; 7(2):214-23.
Rigby, CS, Ryan, RM. Glued to games: How video games draw us in and hold us spellbound. Santa Barbara: Praeger; 2011. 173
Ryan, RM, Rigby, CS, Przybylski, AK. Motivation pull of video games: A Self-determination theory approach. Motivation and Emotion 2006; 30:347-365.

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Responsible Party: Joseph Hart, Associate Professor, University of Virginia
ClinicalTrials.gov Identifier: NCT04187092    
Other Study ID Numbers: IRB-HSR# 21926
First Posted: December 5, 2019    Key Record Dates
Last Update Posted: December 5, 2019
Last Verified: December 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Joseph Hart, University of Virginia:
knee osteoarthritis
video-game based interventions
strength
Balance
Precision
Additional relevant MeSH terms:
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Osteoarthritis
Osteoarthritis, Knee
Arthritis
Joint Diseases
Musculoskeletal Diseases
Rheumatic Diseases