Eileen Krepkovich1, Mandeep Kaur2, L Colby Mangum3, Susan Saliba4, Matthew Lichter1, Aaron Olowin1, Neal Richardson1, Joseph Hart5. 1. Barron Associates Inc, Charlottesville, VA,USA. 2. Northern Arizona University, Phoenix Biomedical Campus, Phoenix, AZ,USA. 3. University of Central Florida, Orlando, FL,USA. 4. Department of Kinesiology, University of Virginia, Charlottesville, VA,USA. 5. University of North Carolina, Chapel Hill, NC,USA.
Abstract
CONTEXT: A novel virtual game system Knee Biofeedback Rehabilitation Interface for game-based home therapy (KneeBright) was developed for strength training using integrated electromyography biofeedback of the quadriceps muscle to control the game. The study aimed to compare the KneeBright and electromyography biofeedback interface among patients with knee osteoarthritis. DESIGN: Controlled before and after design. METHODS: Nineteen patients with knee osteoarthritis took part in this laboratory-based study. Exercise sessions took place on 2 separate days. During session 1, participants used a conventional electromyography biofeedback system while performing 3 sets of lower body exercises with emphasis on maximal muscle activation, endurance, and precision. During session 2, participants used the KneeBright game to match the exercise sets in the first session. For both sessions, knee extension torque during the isometric muscle activation exercises and time to voluntary additional exercise were recorded. Patient engagement was assessed using the technology acceptance model and System Usability Score questionnaires. RESULTS: The peak knee extension torque produced during the control exercise session and the KneeBright exercise session were positively correlated. Knee extension torque generated during KneeBright game exercise sessions was increased by an average of 25% compared to the control sessions (2.14 vs 1.77 N·m/kg, P = .02). The mean technology acceptance model score for the KneeBright system was 3.4/5 and the mean System Usability Score was 79, both indicating positive patient engagement. CONCLUSIONS: Patients using the KneeBright game produced greater knee torque than patients using the conventional system, had positive levels of engagement, and exercised longer with the KneeBright game.
CONTEXT: A novel virtual game system Knee Biofeedback Rehabilitation Interface for game-based home therapy (KneeBright) was developed for strength training using integrated electromyography biofeedback of the quadriceps muscle to control the game. The study aimed to compare the KneeBright and electromyography biofeedback interface among patients with knee osteoarthritis. DESIGN: Controlled before and after design. METHODS: Nineteen patients with knee osteoarthritis took part in this laboratory-based study. Exercise sessions took place on 2 separate days. During session 1, participants used a conventional electromyography biofeedback system while performing 3 sets of lower body exercises with emphasis on maximal muscle activation, endurance, and precision. During session 2, participants used the KneeBright game to match the exercise sets in the first session. For both sessions, knee extension torque during the isometric muscle activation exercises and time to voluntary additional exercise were recorded. Patient engagement was assessed using the technology acceptance model and System Usability Score questionnaires. RESULTS: The peak knee extension torque produced during the control exercise session and the KneeBright exercise session were positively correlated. Knee extension torque generated during KneeBright game exercise sessions was increased by an average of 25% compared to the control sessions (2.14 vs 1.77 N·m/kg, P = .02). The mean technology acceptance model score for the KneeBright system was 3.4/5 and the mean System Usability Score was 79, both indicating positive patient engagement. CONCLUSIONS: Patients using the KneeBright game produced greater knee torque than patients using the conventional system, had positive levels of engagement, and exercised longer with the KneeBright game.
Entities:
Keywords:
EMG biofeedback; exercise therapy; video game-based interventions
Authors: Joshua N Farr; Scott B Going; Timothy G Lohman; Lucinda Rankin; Shelley Kasle; Michelle Cornett; Ellen Cussler Journal: Arthritis Rheum Date: 2008-09-15