Review of modern technologies for hand recovery with learned non-use
Abstract
Improving upper limb function is an important part of rehabilitation to reduce disability. About 20 % of patients after a stroke do not use their hand, despite the ability of movements. Functional recovery after shoulder fracture is slow and results are also disappointing. One of the reasons for the lack of restoration of hand function is the syndrome of learned non-use. This review presents the advantages and limitations of the two most modern and common technologies for both the rehabilitation of the proximal upper limb (robotics and virtual reality) and the rehabilitation of the hand with learned non-use syndrome using a sensory glove with computer programs based on the biofeedback.
Supporting agencies: Article written within the scope of the state task — 121031100289–2
About the Authors
E. M. Vyazgina
“Polenov Neurosurgical Institute” — a branch of the Almazov National Medical Research Centre Ministry of Health of the Russian Federation; Rehabilitation Center “Sputnik in Komarovo”
Russian Federation
Russian Federation
St. Petersburg
A. V. Borisov
Rehabilitation Center “Sputnik in Komarovo”
Russian Federation
Russian Federation
St. Petersburg
A. Yu. Polezhaeva
Rehabilitation Center “Sputnik in Komarovo”
Russian Federation
Russian Federation
St. Petersburg
R. I. Tuzov
Rehabilitation Center “Sputnik in Komarovo”
Russian Federation
Russian Federation
St. Petersburg
N. E. Ivanova
“Polenov Neurosurgical Institute” — a branch of the Almazov National Medical Research Centre Ministry of Health of the Russian Federation
Russian Federation
Russian Federation
St. Petersburg
References
1. Adomavičienė A., daunoravičienė K., Kubilius r., et al. Influence of New Technologies on post-Stroke rehabilitation: A Comparison of Armeo Spring to the Kinect System. medicina. 2019; vol. 55 (4): 98. doi.org/10.3390/medicina55040098
2. Freeman С.T., Hughes A.-m ., Burridge j . H., et al. A robotic workstation for stroke rehabilitation of the upper extremity using FeS. 2009; 31(3): 364–373. doi.org/10.1016/j.medengphy.2008.05.008
3. Carter A. r ., Connor l . T., d romerick A. W. r ehabilitation After Stroke: Current State of the Science. Neurol Neuroscince rep. 2010; 10: 158–166. https://doi.org/10.1007/s11910-010-0091-9
4. Nerz C., Schwickert l ., Becker C. et al. e ffectiveness of robot-assisted training added to conventional rehabilitation in patients with humeral fracture early after surgical treatment: protocol of a randomised, controlled, multicentre trial. 2017; Trials 18, 589. doi.org/10.1186/s13063–017–2274-z
5. paušić v ., jovanović g., Simić S. r obotics in physical medicine and neurorehabilitation. medicinski pregled. 2021; vol.74 (1–2): 50–53. doi.org/10.2298/mpNS2102050p
6. meziani y., m orere y., Abdelkader A. H. Towards adaptive and finer rehabilitation assessment: A learning framework for kinematic evaluation of upper limb rehabilitation on an Armeo Spring exoskeleton. Control engineering practice. 2021; vol. 111: e104804. doi.org/10.1016/j.conengprac.2021.104804
7. Scotto di l uzio F., Bagnara S., Tartaglia r ., et al. (2019) A Bio-cooperative robotic System to ensure ergonomic postures during upper limb rehabilitation in occupational Contexts. proceedings of the 20th Congress of the International e rgonomics Association (I eA 2018). Advances in Intelligent Systems and Computing. vol. 826. Springer. doi.org/10.1007/978-3-319-96065-4_37
8. oña e. d. et al. robotics in health care: p erspectives of robot-aided interventions in clinical practice for rehabilitation of upper limbs //Applied sciences. 2019; vol. 9 (13): 2586. doi.org/10.3390/app9132586
9. Khalid S., Alnajjar A., gochoo m., renawi A., Shimoda S. r obotic assistive and rehabilitation devices leading to motor recovery in upper limb: a systematic review. d isability and r ehabilitation: Assistive Technology. 2021. doi.org/10.1080/17483107.2021.1906960
10. Arumugam A., g ururaj S. e ffects of game-based rehabilitation on upper limb function in adults within the first six months following stroke: protocol for a systematic review and meta-analysis. j BI evidence synthesis. 2021; vol. 19 (8): 1954–1963. doi.org/10.11124/jBIeS-20–00349
11. Serrano-l opez-Terradas p. A., Seco-rubio r. effectiveness of robotic therapy in the proximal and distal rehabilitation of the upper limb in patients after stroke using the Amadeo ® and Armeo ® devices: a systematic review of randomized clinical trials//Studies in p sychology. 2022: 1–47. doi.org/10.1080/02109395.2021.2009677
12. page S. j ., levine p., leonard A. C. effects of mental practice on affected limb use and function in chronic stroke. 2005; vol. 86(3); 399–402. doi.org/10.1016/j.apmr.2004.10.002
13. mcgeoch, j . A. Forgetting and the law of disuse. psychological review. 1932; 39(4), 352–370. doi.org/10.1037/h0069819
14. prokopenko S. v ., mozheiko e. y u., Alekseevich g . v . The possibility of restoring the advanced hand activity using the sensorial glove in patients with stroke. Siberian medical review. 2014; Т. 2 (86): 72–77 (In r uss.)] https://cyberleninka.ru/article/n/vozmozhnosti-vosstanovleniya-tonkoy-motoriki-kisti-s-ispolzovaniem-sensornoy-perchatki-u-bolnyh-perenesshih-insult
15. Ivanilova T. N., mozheiko e . y u., prokopenko S. v . development of the hardware part of the limbtracker complex for wireless p C control for people with impaired motor functions. South-Seberian Science vestnik. 2017; 2: 47–54 (In russ.) doi.org/10.25699/SSSB.2021.36.2.027
16. mozheiko e.yu., prokopenko S.v., Alekseevich g.v. The optimization of restoration approaches of advanced hand activity using the sensorial glove and the mCIm T method. S. S. Korsakov j ournal of Neurology and psychiatry. 2017; vol. 117 (10): 101 (In russ.) doi.org/10.17116/jnevro2017117101101–105
Review
For citations:
Vyazgina E.M., Borisov A.V., Polezhaeva A.Yu., Tuzov R.I., Ivanova N.E. Review of modern technologies for hand recovery with learned non-use. Russian Neurosurgical Journal named after Professor A. L. Polenov. 2022;14(1-2):17-22. (In Russ.)
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