Converging Technologies in Cardiopulmonary Physiotherapy: A Review of VR, AR, AI, and IOT-Based Rehabilitation Frameworks and Clinical Outcomes: Comprehensive Review
Hemangkumar Sudhakaubhai Jani Subhadraben Sureshchandra Institute of Physiotherapy, Ganpat university, Kherva, Gujarat, India
Brijesh Varma 2nd, Subhadraben Sureshchandra Institute of Physiotherapy, Ganpat university, Kherva, Gujarat, India
Riya Pancholi 3rd, Subhadraben Sureshchandra Institute of Physiotherapy, Ganpat university, Kherva, Gujarat, India
Address for correspondence: Hemangkumar Sudhakaubhai Jani, Subhadraben Sureshchandra Institute of Physiotherapy, Ganpat university, Kherva, Gujarat, India E-mail: hsj01@ganpatuniversity.ac.in
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Hemangkumar Sudhakarbhai Jani, Brijesh Varma, Riya Pancholi. Converging Technologies in Cardiopulmonary Physiotherapy: A Review of VR, AR, AI, and IOT-Based Rehabilitation Frameworks and Clinical Outcomes: Comprehensive Review. Therapy Jr. 2026; 19(2): 159-166.
Timeline
Received : April 22, 2026
Accepted : May 20, 2026
Published : June 30, 2026
Abstract
Background: The integration of Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), and Internet of Things (IoT) technologies into cardiopulmonary physiotherapy represents one of the most consequential shifts in modern rehabilitation medicine. While individual modalities have attracted growing research attention, their deliberate convergence as a unified rehabilitation framework remains insufficiently synthesised. Objective: To examine the clinical evidence, implementation challenges, and future directions of converging VR, AR, AI, and IoT technologies in cardiac and pulmonary rehabilitation. Methods: A structured narrative review of 217 peer-reviewed articles (2001–2025) was conducted across PubMed/MEDLINE, Scopus, CINAHL, IEEE Xplore, and the Cochrane Library, synthesised thematically. Results: Immersive VR consistently improves exercise adherence and psychological outcomes; IoT-based remote monitoring extends physiological supervision beyond clinical walls; AI systems advance protocol individualisation; AR augments procedural guidance and self-efficacy. Critical gaps persist in long-term outcome data, standardised protocols, equitable access, and data governance. Conclusions: Converging digital technologies hold substantive potential to reshape cardiopulmonary physiotherapy. Realising this demands interdisciplinary collaboration, representative clinical trials, and patient-centred, equity-informed implementation.
References
1. Tsai T.Y., Finkelstein J. Metaverse application for cycling exercise rehabilitation: development and pilot evaluation. [Unpublished/ repository]. 2023.
2. Mamodiya U., Kishor I., Almaiah M.A., et al. AI-enhanced AR/VR systems for remote healthcare: overcoming real-time data integration and security challenges with IoT. Int J Innov Res Sci Stud. 2025. doi:10.53894/ijirss.v8i1.4999
3. Singh G., Singh V. Robotics and IoT integration for smart remote rehabilitation and patient-centered healthcare systems. 2025. doi:10.4018/979-8-3373-5447-7.ch003
4. Tsai T.Y., Finkelstein J. Promoting safety and quality of home-based exercise using IoT architecture. Stud Health Technol Inform. 2025. doi:10.3233/shti251196
5. Marketou M., Anastasiou I., Fourlis A., et al. Efficacy of an Internet of Things-based system for cardiac rehabilitation monitoring: insights from the IntellIoT pivotal trial in heart failure patients. Eur Heart J Digit Health. 2024. doi:10.1093/ehjdh/ztae093
6. Automated personalized cardiac rehabilitation protocol generation using federated learning and real-time physiological data integration. Zenodo. 2025. doi:10.5281/zenodo.17105688
7. Li X., Zhao L., Xu T., et al. Cardiac telerehabilitation under 5G internet of things monitoring: a randomized pilot study. Sci Rep. 2023. doi:10.1038/s41598-023-46175-z
8. Shaji S., Sankaran R., Guntha R., et al. A real-time IoMT enabled remote cardiac rehabilitation framework. Proc IEEE COMSNETS. 2023. doi:10.1109/COMSNETS56262.2023.10041272
9. Brewer L.C., Abraham H., Clark D., et al. Efficacy and adherence rates of a novel community-informed virtual world-based cardiac rehabilitation program: protocol for the Destination Cardiac Rehab randomized controlled trial. J Am Heart Assoc. 2023; 12: e030883. doi:10.1161/jaha.123.030883
10. Chen Y., Zhang Y., Long X., et al. Effectiveness of virtual reality-complemented pulmonary rehabilitation on lung function, exercise capacity, dyspnea, and health status in COPD: systematic review and meta-analysis. JMIR Preprints. 2024. doi:10.2196/preprints.64742
11. Peinado-Rubia A.B., Verdejo-Herrero A., Obrero-Gaitan E., et al. Non-immersive virtual reality-based therapy applied in cardiac rehabilitation: A systematic review with metaanalysis. Sensors. 2024; 24(3): 903. doi:10.3390/s24030903
12. Moghaddam N.G., Namazinia M., Hajiabadi F., et al.The efficacy of phase I cardiac rehabilitation training based on augmented reality on the self-efficacy of patients undergoing coronary artery bypass graft surgery: A randomized clinical trial. BMC Sports Sci Med Rehabil. 2023. doi:10.1186/s13102-023-00770-9
13. Oanesa R.D., Atluri N., Ali Y.Z., et al. Humancentered design to tailor telehealth cardiac rehabilitation to diverse populations: the MCNAIR study. Circulation. 2024; 150 (suppl 1). doi:10.1161/circ.150.suppl_1.4141523
14. Postolache O., Monge J., Alexandre R., et al. Virtual reality and augmented reality technologies for smart physical rehabilitation. In: Springer; 2021: chap 8. doi:10.1007/978-3-030-71221-1_8
15. Shoba L.K., Maruthukannan B., Venkataraman N., et al. Dynamic cardiovascular rehabilitation for personalized exercise plans guided by recurrent neural networks in the cloud. Proc IEEE ICSSES. 2024. doi:10.1109/icsses62373.2024.10561424
16. Hussain Z., Rayani A., Isakadze N., et al. Optimizing representation and retention in hybrid cardiac rehabilitation: lessons learned from the mTECH-Rehab randomized controlled trial. Circulation. 2025; 152 (suppl 3). doi:10.1161/circ.152.suppl_3.4366999
17. Koulouris D., Menychtas A., Maglogiannis I. An IoT-enabled platform for the assessment of physical and mental activities utilizing augmented reality exergaming. Sensors. 2022; 22(9): 3181. doi:10.3390/s22093181
18. Yuenyongchaiwat K., Boonkawee T., Pipatsart P., et al. Effects of virtual exercise on cardiopulmonary performance and depression in cardiac rehabilitation phase I: a randomized control trial. Physiother Res Int. 2023. doi:10.1002/pri.2066
19. Shah N.D., Banta C.W., Berger A.L., et al. Retrospective comparison of outcomes and cost of a virtual vs center-based cardiac rehabilitation program. medRxiv. 2024. doi:10.1101/2024.05.05.24306717
20. Jia Y.Y., Song J.P., Yang L. Can virtual reality have effects on cardiac rehabilitation? An overview of systematic reviews. Curr Probl Cardiol. 2023. doi:10.1016/j.cpcardiol.2023.102231
21. Antoniou V., Davos C.H., Kapreli E., et al. Effectiveness of home-based cardiac rehabilitation using wearable sensors: a systematic review and meta-analysis. J Clin Med. 2022; 11(13): 3772. doi:10.3390/jcm11133772
22. Hughes J.W., Berry R, Brown TM, et al. Consensus statement on the virtual and remote delivery of cardiac and pulmonary rehabilitation and their components. J Cardiopulm Rehabil Prev. 2025. doi:10.1097/hcr.0000000000001002
23. Micheluzzi V., Navarese E.P., Merella P., et al. Clinical application of virtual reality in patients with cardiovascular disease: State of the art. Front Cardiovasc Med. 2024. doi:10.3389/fcvm.2024.1356361
24. Garofano M., Vecchione C., Calabrese M., et al. Technological developments, exercise training programs, and clinical outcomes in cardiac telerehabilitation in the last ten years: a systematic review. Healthcare. 2024; 12(15): 1534. doi:10.3390/healthcare12151534
25. Harzand A., Alrohaibani A., Idris M.Y., et al. Effects of a patient-centered digital health intervention in patients referred to cardiac rehabilitation: the Smart HEART clinical trial. BMC Cardiovasc Disord. 2023. doi:10.1186/s12872-023-03471-w
26. Golbus J.R., Lopez-Jimenez F., Barac A., et al. Digital technologies in cardiac rehabilitation: a science advisory from the American Heart Association. Circulation. 2023. doi:10.1161/CIR.0000000000001150
27. Anupama F. Revolutionizing remote patient monitoring with AI and IoT. Int J Manag Technol. 2025. doi:10.37745/ijmt.2013/vol12n34755
28. Ferrel-Yui D., Candelaria D., Pettersen T.R., et al. Uptake and implementation of cardiac telerehabilitation: a systematic review of provider and system barriers and enablers. Int J Med Inform. 2024. doi:10.1016/j.ijmedinf.2024.105346
29. Jung T., Moorhouse N., Shi X., et al. A virtual reality-supported intervention for pulmonary rehabilitation of patients with COPD: mixed methods study. J Med Internet Res. 2020. doi:10.2196/14178
30. Zhang S., Wang Y., Wu J, et al. Effectiveness of smartwatch device on adherence to homebased cardiac rehabilitation in patients with coronary heart disease: a randomized controlled trial. JMIR Mhealth Uhealth. 2025. doi:10.2196/70848
31. Schmitz B., Bosch J.A. TIMELY: providing intime and intelligent support for cardiovascular rehabilitation with ‘patients and practitioners in the loop’ interaction. Proc CHI. 2023. doi:10.1145/3581754.3584158
32. Shaji S., Krishnan Pathinarupothi R, Guntha R, et al. IoMT and AI enabled time critical system for tele-cardiac rehabilitation. IEEE Access. 2024. doi:10.1109/access.2024.3409759
33. Oanesa R.D., Atluri N., Boyd A., et al. Humancentered design to tailor telehealth cardiac rehabilitation to diverse populations: the MCNAIR study. J Am Heart Assoc. 2025. doi:10.1161/jaha.124.040711
34. Claes J., Cornelissen V., McDermott C.M., et al. Feasibility, acceptability, and clinical effectiveness of a technology-enabled cardiac rehabilitation platform (PATH-I): randomized controlled trial. J Med Internet Res. 2019. doi:10.2196/14221
35. Johnson T.E., Isakadze N., Mathews L, et al. Building a hybrid virtual cardiac rehabilitation program to promote health equity: lessons learned. Cardiovasc Digit Health J. 2022. doi:10.1016/j.cvdhj.2022.06.002
36. Raja M.A., Loughran R., Mc Caffery F. A review of applications of artificial intelligence in cardiorespiratory rehabilitation. Inform Med Unlocked. 2023. doi:10.1016/j.imu.2023.101327
37. Gulick V., Graves D.E., Ames S., et al. Effect of a virtual reality-enhanced exercise and education intervention on patient engagement and learning in cardiac rehabilitation: randomized controlled trial. J Med Internet Res. 2021. doi:10.2196/23882
38. Aharon K.B., Gershfeld-Litvin A., Amir O., et al. Improving cardiac rehabilitation patient adherence via personalized interventions. PLoS ONE. 2022. doi:10.1371/journal.pone.0273815
39. Keteyian S.J., Grimshaw C., Ehrman J.K., et al. The iATTEND trial: a trial comparing hybrid versus standard cardiac rehabilitation. Am J Cardiol. 2024. doi:10.1016/j. amjcard.2024.04.034
40. Azad M.K. The cost-effectiveness of exercisebased cardiac telerehabilitation intervention: a systematic review. Eur J Phys Rehabil Med. 2023. doi:10.23736/s1973-9087.23.07773-0
41. Blasco-Peris C., Fuertes-Kenneally L., Vetrovský T., et al. Effects of exergaming in patients with cardiovascular disease compared to conventional cardiac rehabilitation: a systematic review and meta-analysis. Int J Environ Res Public Health. 2022. doi:10.3390/ijerph19063492
42. Van Iterson E.H., Laffin L.J., Cho L. National, regional, and urban-rural patterns in fixedterrestrial broadband internet access and cardiac rehabilitation utilization in the United States. Am J Prev Cardiol. 2022. doi:10.1016/j. ajpc.2022.100454
43. Driesse E., Gajane P., Barakova E.I. WeHeart: a personalized recommendation device for physical activity encouragement in cardiac rehabilitation. Front Artif Intell Appl. 2023. doi:10.3233/FAIA230122
44. Chen Y., Cao L., Xu Y., et al. Effectiveness of virtual reality in cardiac rehabilitation: a systematic review and meta-analysis of randomized controlled trials. Int J Nurs Stud. 2022. doi:10.1016/j.ijnurstu.2022.104323
45. Jolliffe J., Rees K., Taylor R.S., et al. Exercisebased rehabilitation for coronary heart disease. Cochrane Database Syst Rev. 2001. doi:10.1002/14651858.CD001800
46. Nabutovsky I., Nachshon A., Klempfner R., et al. Digital cardiac rehabilitation programs: the future of patient-centered medicine. Telemed J E Health. 2020. doi:10.1089/TMJ.2018.0302
47. Taylor R.S., Brown A., Ebrahim S., et al. Exercise-based rehabilitation for patients with coronary heart disease: systematic review and meta-analysis of randomized controlled trials. Am J Med. 2004;116(10). doi:10.1016/J.AMJMED.2004.01.009
48. Szczepańska-Gieracha J., Józwik S., Cieślik B., et al. Immersive virtual reality therapy as a support for cardiac rehabilitation: a pilot randomized-controlled trial. Cyberpsychol Behav Soc Netw. 2021. doi:10.1089/CYBER.2020.0297
49. Bashir Z., Misquith C., Shahab A., et al. The impact of virtual reality on anxiety and functional capacity in cardiac rehabilitation: a systematic review and meta-analysis. Curr Probl Cardiol. 2023. doi:10.1016/j.cpcardiol.2023.101628
50. Colombo V., Bocca G., Mondellini M., et al. Evaluating the effects of virtual reality on perceived effort during cycling: preliminary results on healthy young adults. Proc IEEE MeMeA. 2022. doi:10.1109/memea54994.2022.9856467
51. Chong M.S., Sit J.W.H., Karthikesu K. Effectiveness of technology-assisted cardiac rehabilitation: a systematic review and metaanalysis. Int J Nurs Stud. 2021. doi:10.1016/J.IJNURSTU.2021.104087
Data Sharing Statement
There are no additional data available. All raw data and code are available upon request.
Funding
This research received no funding.
Author Contributions
All authors contributed significantly to the work and approve its publication.
Ethics Declaration
This article does not involve any human or animal subjects, and therefore does not require ethics approval.
Acknowledgements
We would like to express our gratitude to the patients, their families, and all those who have contributed to this study.
Conflicts of Interest
No conflicts of interest in this work.
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Hemangkumar Sudhakarbhai Jani, Brijesh Varma, Riya Pancholi. Converging Technologies in Cardiopulmonary Physiotherapy: A Review of VR, AR, AI, and IOT-Based Rehabilitation Frameworks and Clinical Outcomes: Comprehensive Review. Therapy Jr. 2026; 19(2): 159-166.
This license enables
reusers to distribute, remix, adapt, and build upon the material in any medium
or format for noncommercial purposes only, and only so long as attribution is
given to the creator.
This license enables
reusers to distribute, remix, adapt, and build upon the material in any medium
or format for noncommercial purposes only, and only so long as attribution is
given to the creator.