Computer Vision-Augmented Exergaming for Spine Health
-
Thandavamurthy Jayasree
,
Palchamy Pragathi
,
Saravanan Premkumar
,
Senthilkumar Revathi Sree Krishna
Abstract
This research introduces a novel, technology-driven approach to back pain rehabilitation by integrating real-time pose detection with interactive Unity-based gaming experiences. Our system delivers personalized exercise regimens targeting flexibility, strength, and posture while providing users with immediate feedback. User friendly gaming platform was developed using the Unity engine that integrates real-time analysis of physical exercises. The system successfully analysed the performance of three major exercises Knee-to-chest stretch (cross crunches), side bend, forward and backward bends and demonstrated a measurable improvement in the user scoring pattern, suggesting enhanced engagement and effective performance analysis. By successfully gamifying these therapeutic exercises, we aim to significantly boost user engagement and adherence to treatment protocols, leading to improved long-term spinal health outcomes. This framework offers a dynamic, adaptable, and highly scalable solution for individuals with varying rehabilitation needs, demonstrating the potential to profoundly impact the quality of life for those affected by back pain. Transforming exercises into a game is key to driving better, sustained outcomes that helps in achieving superior long-term therapeutic results.
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[17] S. Schez-Sobrino, D. Vallejo, D. Monekosso, C. Glez-Morcillo, and Paolo Remagnino, A Distributed Gamified System Based on Automatic Assessment of Physical Exercises to Promote Remote Physical Rehabilitation, IEEE Access, 2020;8, p. 91424–91434.
[18] F. M. Alfieri, C. da Silva Dias, N. C. de Oliveira, and L. R. Battistella, Gamification in Musculoskeletal Rehabilitation,” Current Reviews in Musculoskeletal Medicine,2022;15:6, p. 629–636.
[19] C. Scho¨nauer, T. Pintaric, H. Kaufmann, S. M. Kosterink, and M. Marie, Chronic pain rehabilitation with a serious game using multimodal input, International Conference on Virtual Rehabilitation, 2011.
[20] J. Mueller, D. Niederer, S. Tenberg, L. Oberheim, A. Moesner, and S. Mueller, Acute effects of game-based biofeedback training on trunk motion in chronic low back pain: a randomized crossover pilot trial,” BMC Sports Science, Medicine and Rehabilitation,2020;14:1.
[21] Z. Trost et al., The promise and challenge of virtual gaming technolo- gies for chronic pain: the case of graded exposure for low back pain, Pain Management,2015;5:3, p. 197–206.
[22] O. Stamm, R. Dahms, and U. Mu¨ller-Werdan, Virtual reality in pain therapy: a requirements analysis for older adults with chronic back pain, Journal of NeuroEngineering and Rehabilitation, 2020;17: 1.
[23] C. R. France and J. S. Thomas, Virtual immersive gaming to optimize recovery (VIGOR) in low back pain: A phase II randomized controlled trial,” Contemporary Clinical Trials, 2018;69, p. 83–91.
[24] F. Fatoye et al., Cost effectiveness of virtual reality game compared to clinic based McKenzie extension therapy for chronic nonspecific low back pain, British Journal of Pain,2022;16:6, p. 601–609.
[25] S. M. Jansen-Kosterink, R. M. H. A. Huis in ’t Veld, C. Scho¨nauer, H. Kaufmann, H. J. Hermens, and M. M. R. Vollenbroek-Hutten, A Serious Exergame for Patients Suffering from Chronic Musculoskeletal Back and Neck Pain: A Pilot Study, Games for Health Journal, 2013;2:5, p. 299–307.
[26] M. I. Daoud, A. Alhusseini, M. Z. Ali, and R. Alazrai, A Game-Based Rehabilitation System for Upper-Limb Cerebral Palsy: A Feasibility Study, Sensors,2020;20:8, p. 2416.
[27] P. Brauner and M. Ziefle, Serious Motion-Based Exercise Games for Older Adults: Evaluation of Usability, Performance, and Pain Mitiga- tion, JMIR Serious Games,2020;8:2, p. e14182.
[28] Kun Zhang , Pengcheng Zhang, Xintao Tu , Danny Crookes , Zhicheng Liu , Peixia Xu, Chenggang Wu, Danny Crookes , Zhicheng Liu , Peixia Xu , , and Liang Hua, SR-POSE: A Novel Non-Contact Real-Time Rehabilitation Evaluation Method Using Lightweight Technology, IEEE transactions on Neural systems and rehabilitation engineering, 2023, 31, p. 4179- 4188.
[29] Dey, Prof. M., Yoga Pose Detection for Human Rehabilitation Using Deep Leaning., International Journal for Research in Applied Science and Engineering Technology, 2023, 11(12), p.231–235.
[30] Pereira, B., Cunha, B., Viana, P., Lopes, M., Melo, A. S. C., & Sousa, A. S. P. A Machine Learning App for Monitoring Physical Therapy at Home, Sensors, 2024, 24(1).
[31] Adolf, J., Dolezal, J., Kutilek, P., Hejda, J., & Lhotska, L., Single Camera-Based Remote Physical Therapy: Verification on a Large Video Dataset, Applied Sciences (Switzerland), 2022, 12(2).
[32] Palermo, M., Lopes, J. M., André, J., Matias, A. C., Cerqueira, J., & Santos, C. P., A multi-camera and multimodal dataset for posture and gait analysis., Scientific Data, 2022, 9(1).
doi: 10.1002/14651858.CD009790.pub2. PMID: 34580864; PMCID: PMC8477273.
[2] Cheng, M., Tian, Y., Ye, Q. et al. Evaluating the effectiveness of six exercise interventions for low back pain: a systematic review and meta-analysis. BMC Musculoskelet Disord 2025, 26, 433. https://doi.org/10.1186/s12891-025-08658-0
[3] R. S. Gonc¸alves, R. A. Prado, G. M. V. Ladeira, and A. L. P. Gasparini, Development of Serious Games for the Rehabilitation of the Human Vertebral Spine for Home Care, Robotics,2023;12:2, 58.
[4] C. Gmez-Portes, C. Lacave, A. I. Molina, and D. Vallejo, Home Rehabilitation Based on Gamification and Serious Games for Young People: A Systematic Mapping Study, Applied Sciences, 2020;10:24,8849.
[5] M. I. Daoud, A. Alhusseini, M. Z. Ali, and R. Alazrai, A Game-Based Rehabilitation System for Upper-Limb Cerebral Palsy: A Feasibility Study, Sensors,2020;20:8,2416.
[6] R. Alexandre, Octavian Postolache, and Pedro Silva Girao, Physical Rehabilitation based on Smart Wearable and Virtual Reality Serious Game, 2019.
[7] S. Pintado-Izquierdo, R. Cano-de-la-Cuerda, and R. M. Ortiz-Gutie´rrez, Video Game-Based Therapy on Balance and Gait of Patients with Stroke: A Systematic Review, Applied Sciences,2020;10:18, p. 6426.
[8] A. Chow, Pang Ying Han, Khoh Wee How, and Ooi Shih Yin, Hand Gesture Controlled Game for Hand Rehabilitation,2022;205–215.
[9] M. Altayeb, Hand Gestures Replicating Robot Arm based on Medi- aPipe, Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2023;11:3, pp. 727–737.
[10] J.-W. Kim, J.-Y. Choi, E.-J. Ha, and J. Choi, Human Pose Estimation Using MediaPipe Pose and Optimization Method Based on a Humanoid Model, Applied sciences,2023;13:4, 2700–2700.
[11] . Patil, D. Rao, K. Utturwar, T. Shelke, and E. Sarda, Body Posture Detection and Motion Tracking using AI for Medical Exercises and Recommendation System, ITM Web of Conferences, 2022;44, p.03043.
[12] Y.-Y. Chung, T. M. Annaswamy, and B. Prabhakaran, Performance and User Experience Studies of HILLES: Home-based Immersive Lower Limb Exergame System, 2023.
[13] IJsselsteijn, WA, de Kort, YAW, Poels, K, The Game Experience Questionnaire. Technische Universiteit Eindhoven, Eindhoven, 2013.
[14] J. Jane Elona and T. Jayasree, Smart Gaming System for Hand Rehabilitation, Communications in computer and information science, 2024; p. 35–46.
[15] T. Rangari, S. Kumar, P. P. Roy, D. P. Dogra, and B.-G. Kim, Video based exercise recognition and correct pose detection, Multimedia Tools and Applications, 2022.
[16] B. Debnath, M. O’Brien, M. Yamaguchi, and A. Behera, A review of computer vision-based approaches for physical rehabilitation and assessment, Multimedia Systems,2021;28:1,p. 209–239.
[17] S. Schez-Sobrino, D. Vallejo, D. Monekosso, C. Glez-Morcillo, and Paolo Remagnino, A Distributed Gamified System Based on Automatic Assessment of Physical Exercises to Promote Remote Physical Rehabilitation, IEEE Access, 2020;8, p. 91424–91434.
[18] F. M. Alfieri, C. da Silva Dias, N. C. de Oliveira, and L. R. Battistella, Gamification in Musculoskeletal Rehabilitation,” Current Reviews in Musculoskeletal Medicine,2022;15:6, p. 629–636.
[19] C. Scho¨nauer, T. Pintaric, H. Kaufmann, S. M. Kosterink, and M. Marie, Chronic pain rehabilitation with a serious game using multimodal input, International Conference on Virtual Rehabilitation, 2011.
[20] J. Mueller, D. Niederer, S. Tenberg, L. Oberheim, A. Moesner, and S. Mueller, Acute effects of game-based biofeedback training on trunk motion in chronic low back pain: a randomized crossover pilot trial,” BMC Sports Science, Medicine and Rehabilitation,2020;14:1.
[21] Z. Trost et al., The promise and challenge of virtual gaming technolo- gies for chronic pain: the case of graded exposure for low back pain, Pain Management,2015;5:3, p. 197–206.
[22] O. Stamm, R. Dahms, and U. Mu¨ller-Werdan, Virtual reality in pain therapy: a requirements analysis for older adults with chronic back pain, Journal of NeuroEngineering and Rehabilitation, 2020;17: 1.
[23] C. R. France and J. S. Thomas, Virtual immersive gaming to optimize recovery (VIGOR) in low back pain: A phase II randomized controlled trial,” Contemporary Clinical Trials, 2018;69, p. 83–91.
[24] F. Fatoye et al., Cost effectiveness of virtual reality game compared to clinic based McKenzie extension therapy for chronic nonspecific low back pain, British Journal of Pain,2022;16:6, p. 601–609.
[25] S. M. Jansen-Kosterink, R. M. H. A. Huis in ’t Veld, C. Scho¨nauer, H. Kaufmann, H. J. Hermens, and M. M. R. Vollenbroek-Hutten, A Serious Exergame for Patients Suffering from Chronic Musculoskeletal Back and Neck Pain: A Pilot Study, Games for Health Journal, 2013;2:5, p. 299–307.
[26] M. I. Daoud, A. Alhusseini, M. Z. Ali, and R. Alazrai, A Game-Based Rehabilitation System for Upper-Limb Cerebral Palsy: A Feasibility Study, Sensors,2020;20:8, p. 2416.
[27] P. Brauner and M. Ziefle, Serious Motion-Based Exercise Games for Older Adults: Evaluation of Usability, Performance, and Pain Mitiga- tion, JMIR Serious Games,2020;8:2, p. e14182.
[28] Kun Zhang , Pengcheng Zhang, Xintao Tu , Danny Crookes , Zhicheng Liu , Peixia Xu, Chenggang Wu, Danny Crookes , Zhicheng Liu , Peixia Xu , , and Liang Hua, SR-POSE: A Novel Non-Contact Real-Time Rehabilitation Evaluation Method Using Lightweight Technology, IEEE transactions on Neural systems and rehabilitation engineering, 2023, 31, p. 4179- 4188.
[29] Dey, Prof. M., Yoga Pose Detection for Human Rehabilitation Using Deep Leaning., International Journal for Research in Applied Science and Engineering Technology, 2023, 11(12), p.231–235.
[30] Pereira, B., Cunha, B., Viana, P., Lopes, M., Melo, A. S. C., & Sousa, A. S. P. A Machine Learning App for Monitoring Physical Therapy at Home, Sensors, 2024, 24(1).
[31] Adolf, J., Dolezal, J., Kutilek, P., Hejda, J., & Lhotska, L., Single Camera-Based Remote Physical Therapy: Verification on a Large Video Dataset, Applied Sciences (Switzerland), 2022, 12(2).
[32] Palermo, M., Lopes, J. M., André, J., Matias, A. C., Cerqueira, J., & Santos, C. P., A multi-camera and multimodal dataset for posture and gait analysis., Scientific Data, 2022, 9(1).
| Issue | Articles in Press | |
| Section | Research Article(s) | |
| Keywords | ||
| Back pain; Pose detection technology; Rehabilitation; Unity; Spinal health; Gaming exercise | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Jayasree T, Pragathi P, Premkumar S, Krishna SRS. Computer Vision-Augmented Exergaming for Spine Health. jmr. 2026;(-).
