The site of the Media Sphera Publishers contains materials intended solely for healthcare professionals.
By closing this message, you confirm that you are a certified medical professional or a student of a medical educational institution.

Login
EN
+7 (495) 482-4118
+7 (495) 482-4329
+8 800 250-18-12
  • (toll-free number for subscriptions)
    Mon-Fri from 10 a.m. to 6 p.m.

  • © 1998-2026
+7 (495) 482-43-29
EN
All journals
Journal
Year
Year
Search result: 0

Sufelfa A.R.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation

Petrishcheva K.N.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation;
St. Petersburg University

Shcherbina K.K.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation

Ponomarenko G.N.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation;
North-Western State Medical University named after I.I. Mechnikov

Ivanova N.V.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation

Artificial intelligence in comprehensive rehabilitation of people with disabilities. (Literature review)

Authors:

Sufelfa A.R., Petrishcheva K.N., Shcherbina K.K., Ponomarenko G.N., Ivanova N.V.

More about the authors

Journal: Problems of Balneology, Physiotherapy and Exercise Therapy. 2025;102(3): 54‑61

DOI: 10.17116/kurort202510203154

Read: 1433 times

Buy for 300₽
Contact the author
Table of contents

ARTIFICIAL INTELLIGENCE IN COMPREHENSIVE REHABILITATION OF PEOPLE WITH DISABILITIES. (LITERATURE REVIEW)
ARTIFICIAL INTELLIGENCE IN COMPREHENSIVE REHABILITATION OF PEOPLE WITH DISABILITIES. (LITERATURE REVIEW)

To cite this article:

Sufelfa AR, Petrishcheva KN, Shcherbina KK, Ponomarenko GN, Ivanova NV. Artificial intelligence in comprehensive rehabilitation of people with disabilities. (Literature review). Problems of Balneology, Physiotherapy and Exercise Therapy. 2025;102(3):54‑61. (In Russ.)
https://doi.org/10.17116/kurort202510203154

Подписка 2026 Вопросы курортологии, физиотерапии и лечебной физической культуры (Problems of Balneology, Physiotherapy and Exercise Therapy)
МСФ на ЯМ
Использование инфографики авторами научных работ
Recommended articles:
On the path to personalized cardiology: prospects of precise asse­ssment of cardiovascular risks and predictive-prognostic diagnostics. Russian Journal of Cardiology and Cardiovascular Surgery. 2025;(2):206-215
Diagnosis of pathological and adaptive bala­nce changes in Parkinson’s disease to select a reha­bilitation program. S.S. Korsakov Journal of Neurology and Psychiatry. 2025;(4):88-94
Arti­ficial inte­lligence in evaluating reju­venation effect after periorbital endo­scopic surgery. Plastic Surgery and Aesthetic Medi­cine. 2025;(2):42-51
Arti­ficial inte­lligence in asse­ssment of indi­vidual risks of age-related macu­lar dege­neration progression. Russian Annals of Ophthalmology. 2025;(2):123-128
Factors of health formation in disa­bled children with congenital cleft lip and/or palate. Stomatology. 2025;(2):30-36
Prognostic model and calculator for asse­ssing the risk of prolonged pleural effu­sion after lobe­ctomy. Piro­gov Russian Journal of Surgery. 2025;(6):26-34
Arti­ficial inte­lligence capa­bilities in multiple scle­rosis. S.S. Korsakov Journal of Neurology and Psychiatry. 2025;(5):14-21
Arti­ficial inte­lligence in surgery. Redu­cing the risks rela­ted to poly­pharmacy in perioperative period. Piro­gov Russian Journal of Surgery. 2025;(7):59-66
Rela­tionship of the professional characteristics and the orga­nization of the mid-level medi­cal personnel reha­bilitation depa­rtments acti­vity to the health psychophysical indi­cators of children with disa­bilities. Russian Journal of Preventive Medi­cine. 2025;(7):28-35
Reha­bilitation of persons with primary orga­nic mental diso­rders complicated by alco­holism in middle and elde­rly age. S.S. Korsakov Journal of Neurology and Psychiatry. 2025;(7):55-63
Abstract:

Artificial intelligence (AI) technologies have been increasingly used in the field of healthcare over the past decade, which significantly increases the effectiveness of diagnostic, preventive and therapeutic measures. The development of comprehensive rehabilitation for the people with disabilities, is at the intersection of social and medical fields, and it is classically adopting innovative methods of healthcare, AI technologies in particular. However, the use of such technologies for various targeted rehabilitation groups (TRGs) people with disabilities, taking into account the specifics of possible rehabilitation measures and services, has not been sufficiently studied for today. The aim of the work is to identify the existing, most widespread and successfully applied AI technologies by analyzing foreign publications on the use of AI technologies in the comprehensive rehabilitation of the people with disabilities. The paper analyzed foreign studies described in systematic reviews and randomized controlled trials (RCTs) in the PubMed international medical database over the past 5 years (from January 2019 to May 2024). AI technologies were considered from the point of view of application in the areas of complex rehabilitation for different TRGs. The concept of TRGs is new and has no analogues abroad, however, its use in the analysis allows to systematize information about AI technologies in terms of applied tasks of rehabilitation of the disabled. The largest number of studies on the use of AI technologies in rehabilitation relate to the restoration of motor functions of people with disabilities. The analysis of the publication flow makes it possible to assess the prospects and identify areas of rehabilitation and TRGs where the use of AI technologies has been studied to a greater or lesser extent.

Keywords:

artificial Intelligence
Rehabilitation
Disabled Persons
Targeted Rehabilitation Groups

Authors:

Sufelfa A.R.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation

Petrishcheva K.N.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation;
St. Petersburg University

Shcherbina K.K.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation

Ponomarenko G.N.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation;
North-Western State Medical University named after I.I. Mechnikov

Ivanova N.V.

Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation

Received:

03.02.2025

Accepted:

13.04.2025

Close metadata

References:

  1. Polozhenie invalidov. Federal’naya sluzhba gosudarstvennoi statistiki. Accessed May 14, 2025. https://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/population/disabilities/
  2. Sumner J, Lim HW, Chong LS, Bundele A, Mukhopadhyay A, Kayambu G. Artificial intelligence in physical rehabilitation: A systematic review. Artificial intelligence in medicine. 2023;146:102693. https://doi.org/10.1016/j.artmed.2023.102693
  3. Noorbakhsh-Sabet N, Zand R, Zhang Y, Abedi V. Artificial intelligence transforms the future of health care. The American journal of medicine. 2019;132(7):795-801.  https://doi.org/10.1016/j.amjmed.2019.01.017
  4. Patel VL, Shortliffe EH, Stefanelli M, Szolovits P, Berthold MR, Bellazzi R, Abu-Hanna A. The coming of age of artificial intelligence in medicine. Artificial intelligence in medicine. 2009;46(1):5-17.  https://doi.org/10.1016/j.artmed.2008.07.017
  5. Gómez-González E. Artificial Intelligence in Medicine and Healthcare: applications, availability and societal impact. Luxembourg: Publications Office of the European Union; 2020.
  6. Ahuja AS. The impact of artificial intelligence in medicine on the future role of the physician. Peer J. 2019;7:e7702. https://doi.org/10.7717/peerj.7702
  7. Ramesh AN, Kambhampati C, Monson JR, Drew PJ. Artificial intelligence in medicine. Annals of The Royal College of Surgeons of England. 2004;86(5):334-338. 
  8. https://doi.org/10.26102/2310-6018/2024.46.3.026 
  9. Sumner J, Lim HW, Chong LS, Bundele A, Mukhopadhyay A, Kayambu G. Artificial intelligence in physical rehabilitation: A systematic review. Artif Intell Med. 2023 Dec;146:102693. https://doi.org/10.1016/j.artmed.2023.102693
  10. Luvizutto GJ, Silva GF, Nascimento MR, Sousa Santos KC, Appelt PA, de Moura Neto E, de Souza JT, Wincker FC, Miranda LA, Hamamoto Filho PT, de Souza LAPS, Simões RP, de Oliveira Vidal EI, Bazan R. Use of artificial intelligence as an instrument of evaluation after stroke: a scoping review based on international classification of functioning, disability and health concept. Topics in Stroke Rehabilitation. 2022;29(5):331-346.  https://doi.org/10.1080/10749357.2021.1926149
  11. Santilli V. Application of machine learning techniques to physical and rehabilitative medicine. Annali di Igiene. 2022;34(1):79-83. 
  12. D’Antoni F, Russo F, Ambrosio L, Vollero L, Vadalà G, Merone M, Papalia R, Denaro V. Artificial Intelligence and Computer Vision in Low Back Pain: A Systematic Review. International Journal of Environmental Research and Public Health. 2021;18(20):10909. https://doi.org/10.3390/ijerph182010909
  13. Burdea G, Kim N, Polistico K, Kadaru A, Grampurohit N, Roll D, Damiani F. Assistive game controller for artificial intelligence-enhanced telerehabilitation post-stroke. Assist Technol. 2021 May 4;33(3):117-128.  https://doi.org/10.1080/10400435.2019.1593260
  14. Zhang L, Tashiro S, Mukaino M, Yamada S. Use of artificial intelligence large language models as a clinical tool in rehabilitation medicine: a comparative test case. J Rehabil Med. 2023 Sep 11;55:jrm13373. https://doi.org/10.2340/jrm.v55.13373
  15. Luu DK, Nguyen AT, Jiang M, Drealan MW, Xu J, Wu T, Tam WK, Zhao W, Lim BZH, Overstreet CK, Zhao Q, Cheng J, Keefer EW, Yang Z. Artificial Intelligence Enables Real-Time and Intuitive Control of Prostheses via Nerve Interface. IEEE Transactions on Biomedical Engineering. 2022;69(10):3051-3063. https://doi.org/10.1109/TBME.2022.3160618
  16. Olsen S, Zhang J, Liang KF, Lam M, Riaz U, Kao JC. An artificial intelligence that increases simulated brain-computer interface performance. J Neural Eng. 2021 May;18(4). https://doi.org/10.1088/1741-2552/abfaaa
  17. Krasoulis A, Vijayakumar S, Nazarpour K. Multi-Grip Classification-Based Prosthesis Control With Two EMG-IMU Sensors. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2020;28(2):508-518.  https://doi.org/10.1109/TNSRE.2019.2959243
  18. Malcangi M. AI-Based Methods and Technologies to Develop Wearable Devices for Prosthetics and Predictions of Degenerative Diseases. Methods in Molecular Biology. 2021;2190:337-354.  https://doi.org/10.1007/978-1-0716-0826-5_17
  19. Barua PD, Vicnesh J, Gururajan R, Oh SL, Palmer E, Azizan MM, Kadri NA, Acharya UR. Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders-A Review. International Journal of Environmental Research and Public Health. 2022;19(3):1192. https://doi.org/10.3390/ijerph19031192
  20. Bublin M, Werner F, Kerschbaumer A, Korak G, Geyer S, Rettinger L, Schönthaler E, Schmid-Kietreiber M. Handwriting Evaluation Using Deep Learning with SensoGrip. Sensors (Basel). 2023;23(11):5215. https://doi.org/10.3390/s23115215
  21. Devi A, Kavya G. Dysgraphia disorder forecasting and classification technique using intelligent deep learning approaches. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2023;120:110647. https://doi.org/10.1016/j.pnpbp.2022.110647
  22. Zdravkova K, Krasniqi V, Dalipi F, Ferati M. Cutting-edge communication and learning assistive technologies for disabled children: An artificial intelligence perspective. Frontiers in Artificial Intelligence. 2022;5:970430. https://doi.org/10.3389/frai.2022.970430
  23. Draffan EA, Wald M, Ding C, Yin Y. AI Supporting AAC Pictographic Symbol Adaptations. Stud Health Technol Inform. 2023;306:215-221.  https://doi.org/10.3233/SHTI230622
  24. Gross DP, Steenstra IA, Harrell FE Jr, Bellinger C, Zaïane O. Machine Learning for Work Disability Prevention: Introduction to the Special Series. Journal of Occupational Rehabilitation. 2020;30(3):303-307.  https://doi.org/10.1007/s10926-020-09910-1
  25. Cheng ASK, Ng PHF, Sin ZPT, Lai SHS, Law SW. Smart Work Injury Management (SWIM) System: Artificial Intelligence in Work Disability Management. Journal of Occupational Rehabilitation. 2020;30(3):354-361.  https://doi.org/10.1007/s10926-020-09886-y
  26. de Freitas MP, Piai VA, Farias RH, Fernandes AMR, de Moraes Rossetto AG, Leithardt VRQ. Artificial Intelligence of Things Applied to Assistive Technology: A Systematic Literature Review. Sensors (Basel). 2022;22(21):8531. https://doi.org/10.3390/s22218531
  27. Qi J, Wu C, Yang L, Ni C, Liu Y. Artificial intelligence (AI) for home support interventions in dementia: a scoping review protocol. BMJ Open. 2022;12(9):e062604. https://doi.org/10.1136/bmjopen-2022-062604
  28. Huq SM, Maskeliūnas R, Damaševičius R. Dialogue agents for artificial intelligence-based conversational systems for cognitively disabled: a systematic review. Disabil Rehabil Assist Technol. 2024 Apr;19(3):1059-1078. https://doi.org/10.1080/17483107.2022.2146768
  29. Pousada García T, Groba Gonzalez B, Nieto-Riveiro L, Canosa Domínguez N, Maldonado-Bascón S, López-Sastre RJ, Pacheco DaCosta S, González-Gómez I, Molina-Cantero AJ, Pereira Loureiro J. Assessment and counseling to get the best efficiency and effectiveness of the assistive technology (MATCH): Study protocol. PLoS One. 2022 Mar 16;17(3):e0265466. https://doi.org/10.1371/journal.pone.0265466
  30. Herbuela VRDM, Karita T, Furukawa Y, Wada Y, Toya A, Senba S, Onishi E, Saeki T. Machine learning-based classification of the movements of children with profound or severe intellectual or multiple disabilities using environment data features. PLoS One. 2022;17(6):e0269472. https://doi.org/10.1371/journal.pone.0269472
  31. Mulfari D, La Placa D, Rovito C, Celesti A, Villari M. Deep learning applications in telerehabilitation speech therapy scenarios. Computers in Biology and Medicine. 2022 Sep;148:105864. https://doi.org/10.1016/j.compbiomed.2022.105864
  32. Tanabe H, Shiraishi T, Sato H, Nihei M, Inoue T, Kuwabara C. A concept for emotion recognition systems for children with profound intellectual and multiple disabilities based on artificial intelligence using physiological and motion signals. Disabil Rehabil Assist Technol. 2024 May;19(4):1319-1326. https://doi.org/10.1080/17483107.2023.2170478
  33. Liu K, Yu Y, Liu Y, Tang J, Liang X, Chu X, Zhou Z. A novel brain-controlled wheelchair combined with computer vision and augmented reality. BioMedical Engineering OnLine. 2022;21(1):50.  https://doi.org/10.1186/s12938-022-01020-8
  34. Gupta C, Chandrashekar P, Jin T, He C, Khullar S, Chang Q, Wang D. Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases. Journal of Neurodevelopmental Disorders. 2022;14(1):28.  https://doi.org/10.1186/s11689-022-09438-w
  35. Bertoncelli CM, Altamura P, Vieira ER, Bertoncelli D, Solla F. Using Artificial Intelligence to Identify Factors Associated with Autism Spectrum Disorder in Adolescents with Cerebral Palsy. Neuropediatrics. 2019 Jun;50(3):178-187.  https://doi.org/10.1055/s-0039-1685525
  36. Triantafyllidis AK, Tsanas A. Applications of Machine learning in Real-Life Digital Health Interventions: Review of the Literature. J Med Internet Res. 2019 Apr;21(4):e12286. https://doi.org/10.2196/12286
  37. Pueyo V, Pérez-Roche T, Prieto E, Castillo O, Gonzalez I, Alejandre A, Pan X, Fanlo-Zarazaga A, Pinilla J, Echevarria JI, Gutierrez D, Altemir I, Romero-Sanz M, Cipres M, Ortin M, Masia B. Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project. BMJ Open. 2020 Feb;10(2):e033139. https://doi.org/10.1136/bmjopen-2019-033139
  38. Domingo MC. An Overview of Machine Learning and 5G for People with Disabilities. Sensors (Basel). 2021;21(22):7572. https://doi.org/10.3390/s21227572
  39. Takahashi S, Nonomiya Y, Terai H, Hoshino M, Ohyama S, Shintani A, Nakamura H. Artificial intelligence model to identify elderly patients with locomotive syndrome: A cross-section study. Journal of Orthopaedic Science. 2023;28(3):656-661.  https://doi.org/10.1016/j.jos.2022.01.010
  40. Ventura S, Ottoboni G, Lullini G, Chattat R, Simoncini L, Magni E, Piperno R, La Porta F, Tessari A. Co-designing an interactive artificial intelligent system with post-stroke patients and caregivers to augment the lost abilities and improve their quality of life: a human-centric approach. Front Public Health. 2023 Sep;11:1227748. https://doi.org/10.3389/fpubh.2023.1227748
  41. Soin A, Hirschbeck M, Verdon M, Manchikanti L. A Pilot Study Implementing a Machine Learning Algorithm to Use Artificial Intelligence to Diagnose Spinal Conditions. Pain Physician. 2022;25(2):171-178. 
  42. Rughani G, Nilsen TIL, Wood K, Mair FS, Hartvigsen J, Mork PJ, Nicholl BI. The selfBACK artificial intelligence-based smartphone app can improve low back pain outcome even in patients with high levels of depression or stress. Eur J Pain. 2023 May;27(5):568-579.  https://doi.org/10.1002/ejp.2080
  43. Nguyen AT, Xu J, Jiang M, Luu DK, Wu T, Tam WK, Zhao W, Drealan MW, Overstreet CK, Zhao Q, Cheng J, Keefer EW, Yang Z. A bioelectric neural interface towards intuitive prosthetic control for amputees. J Neural Eng. 2020 Nov;17(6). https://doi.org/10.1088/1741-2552/abc3d3
  44. Alarcón-Paredes A, Guzmán-Guzmán IP, Hernández-Rosales DE, Navarro-Zarza JE, Cantillo-Negrete J, Cuevas-Valencia RE, Alonso GA. Computer-aided diagnosis based on hand thermal, RGB images, and grip force using artificial intelligence as screening tool for rheumatoid arthritis in women. Med Biol Eng Comput. 2021 Feb;59(2):287-300.  https://doi.org/10.1007/s11517-020-02294-7
  45. Capecci M, Cima R, Barbini FA, Mantoan A, Sernissi F, Lai S, Fava R, Tagliapietra L, Ascari L, Izzo RN, Leombruni ME, Casoli P, Hibel M, Ceravolo MG. Telerehabilitation with ARC Intellicare to Cope with Motor and Respiratory Disabilities: Results about the Process, Usability, and Clinical Effect of the «Ricominciare» Pilot Study. Sensors (Basel). 2023 Aug;23(16):7238. https://doi.org/10.3390/s23167238
  46. Roca P, Attye A, Colas L, Tucholka A, Rubini P, Cackowski S, Ding J, Budzik JF, Renard F, Doyle S, Barbier EL, Bousaid I, Casey R, Vukusic S, Lassau N, Verclytte S, Cotton F; OFSEP Investigators. Artificial intelligence to predict clinical disability in patients with multiple sclerosis using FLAIR MRI. Diagnostic and Interventional Imaging. 2020;101(12):795-802.  https://doi.org/10.1016/j.diii.2020.05.009
  47. Bertoncelli CM, Altamura P, Vieira ER, Bertoncelli D, Solla F. Using Artificial Intelligence to Identify Factors Associated with Autism Spectrum Disorder in Adolescents with Cerebral Palsy. Neuropediatrics. 2019 Jun;50(3):178-187.  https://doi.org/10.1055/s-0039-1685525
Contact the author
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.

Email Confirmation

An email was sent to test@gmail.com with a confirmation link. Follow the link from the letter to complete the registration on the site.

Email Confirmation

Submit Application

You can become an author of one of our magazines, send a request and we will consider it in during the day.

Name
Phone
E-mail
Message
Login
Registration
E-mail
Password
Forgot Password?

Log in to the site using your account in one of the services

Password recovery
E-mail
Login
Register

We use cооkies to improve the performance of the site. By staying on our site, you agree to the terms of use of cооkies. To view our Privacy and Cookie Policy, please. click here.