Ann Rehabil Med.  2018 Aug;42(4):514-520. 10.5535/arm.2018.42.4.514.

Investigating the Dose-Related Effects of Video Game Trunk Control Training in Chronic Stroke Patients With Poor Sitting Balance

Affiliations
  • 1Department of Rehabilitation Medicine, Bundang Jesaeng General Hospital, Seongnam, Korea. taeim@hanmail.net

Abstract


OBJECTIVE
To investigate the dose-related effect of trunk control training (TCT) using Trunk Stability Rehabilitation Robot Balance Trainer (TSRRBT) in chronic stroke patients with poor sitting balance.
METHODS
This was a retrospective study of 38 chronic stroke patients with poor sitting balance that underwent TCT with TSRRBT. The participants were assigned either to the low-dose training (LDT) group (n=18) or to the highdose training (HDT) group (n=20). In addition to the conventional rehabilitation therapy, the LDT group received 5 sessions of TSRRBT intervention per week, whereas the HDT group received 10 sessions of TSRRBT intervention per week. The outcome measures were the scores on the Trunk Impairment Scale (TIS) and its subscales, Berg Balance Scale (BBS), Functional Ambulation Classification (FAC), and the Korean version of Modified Barthel Index (K-MBI). All outcome measures were assessed before the training and at the end of the 4-week training.
RESULTS
After the 4-week intervention, TIS, BBS, FAC, and K-MBI scores showed improvement in both LDT and HDT groups. Furthermore, the improvements in TIS scores and its subscales were significantly greater in the HDT group than in the LDT group (p < 0.05).
CONCLUSION
TCT using TSRRBT could be an additional treatment for the conventional rehabilitation therapy of chronic stroke patients with poor sitting balance. HDT may provide more beneficial effects on improving patients' sitting balance than LDT.

Keyword

Chronic stroke; Trunk control; Sitting balance; Biofeedback

MeSH Terms

Biofeedback, Psychology
Classification
Humans
Outcome Assessment (Health Care)
Rehabilitation
Retrospective Studies
Stroke*
Video Games*
Walking

Figure

  • Fig. 1. (A, B) Trunk Stability Rehabilitation Robot Balance Trainer (Man&tel, Gumi, Korea).

  • Fig. 2. (A) Balloon-popping game by moving the center of pressure (left/right). (B) Fruit-catching game by moving the hand icon according to the movement of the center of pressure (left/right and anterior/posterior). (C) Bull’s eye matching game by moving the center of pressure, followed by extending the patient’s arm beyond arm’s length. (D) Basketball game by sit-to-stand movement assisted by chair section of the Trunk Stability Rehabilitation Robot Balance Trainer.


Reference

1. Langhorne P, Bernhardt J, Kwakkel G. Stroke rehabilitation. Lancet. 2011; 377:1693–702.
Article
2. Karatas M, Cetin N, Bayramoglu M, Dilek A. Trunk muscle strength in relation to balance and functional disability in unihemispheric stroke patients. Am J Phys Med Rehabil. 2004; 83:81–7.
Article
3. Bohannon RW, Cassidy D, Walsh S. Trunk muscle strength is impaired multidirectionally after stroke. Clin Rehabil. 1995; 9:47–51.
Article
4. Jung HY, Park BK, Shin HS, Kang YK, Pyun SB, Paik NJ, et al. Development of the Korean Version of Modified Barthel Index (K-MBI): multi-center study for subjects with stroke. J Korean Acad Rehabil Med. 2007; 31:283–97.
5. Verheyden G, Nieuwboer A, Mertin J, Preger R, Kiekens C, De Weerdt W. The Trunk Impairment Scale: a new tool to measure motor impairment of the trunk after stroke. Clin Rehabil. 2004; 18:326–34.
Article
6. Chang WH, Kim YH. Robot-assisted therapy in stroke rehabilitation. J Stroke. 2013; 15:174–81.
Article
7. Kwakkel G. Impact of intensity of practice after stroke: issues for consideration. Disabil Rehabil. 2006; 28:823–30.
Article
8. Walker C, Brouwer BJ, Culham EG. Use of visual feedback in retraining balance following acute stroke. Phys Ther. 2000; 80:886–95.
Article
9. Stoller O, Waser M, Stammler L, Schuster C. Evaluation of robot-assisted gait training using integrated biofeedback in neurologic disorders. Gait Posture. 2012; 35:595–600.
Article
10. Jung KH, Ha HG, Shin HJ, Ohn SH, Sung DH, Lee PK, et al. Effects of robot-assisted gait therapy on locomotor recovery in stroke patients. J Korean Acad Rehabil Med. 2008; 32:258–66.
11. Huh JS, Lee YS, Kim CH, Min YS, Kang MG, Jung TD. Effects of balance control training on functional outcomes in subacute hemiparetic stroke patients. Ann Rehabil Med. 2015; 39:995–1001.
Article
12. Hung JW, Yu MY, Chang KC, Lee HC, Hsieh YW, Chen PC. Feasibility of using tetrax biofeedback video games for balance training in patients with chronic hemiplegic stroke. PM R. 2016; 8:962–70.
Article
13. Verheyden G, Vereeck L, Truijen S, Troch M, Herregodts I, Lafosse C, et al. Trunk performance after stroke and the relationship with balance, gait and functional ability. Clin Rehabil. 2006; 20:451–8.
Article
14. Verheyden G, Nieuwboer A, De Wit L, Feys H, Schuback B, Baert I, et al. Trunk performance after stroke: an eye catching predictor of functional outcome. J Neurol Neurosurg Psychiatry. 2007; 78:694–8.
Article
15. Blum L, Korner-Bitensky N. Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review. Phys Ther. 2008; 88:559–66.
Article
16. Collen FM, Wade DT, Bradshaw CM. Mobility after stroke: reliability of measures of impairment and disability. Int Disabil Stud. 1990; 12:6–9.
Article
17. Mehrholz J, Wagner K, Rutte K, Meissner D, Pohl M. Predictive validity and responsiveness of the functional ambulation category in hemiparetic patients after stroke. Arch Phys Med Rehabil. 2007; 88:1314–9.
Article
18. Goldie PA, Bach TM, Evans OM. Force platform measures for evaluating postural control: reliability and validity. Arch Phys Med Rehabil. 1989; 70:510–7.
19. Huxham FE, Goldie PA, Patla AE. Theoretical considerations in balance assessment. Aust J Physiother. 2001; 47:89–100.
Article
20. Lee SW, Shin DC, Song CH. The effects of visual feedback training on sitting balance ability and visual perception of patients with chronic stroke. J Phys Ther Sci. 2013; 25:635–9.
Article
21. Dean C, Shepherd R, Adams R. Sitting balance I: trunk-arm coordination and the contribution of the lower limbs during self-paced reaching in sitting. Gait Posture. 1999; 10:135–46.
Article
22. Dean CM, Shepherd RB. Task-related training improves performance of seated reaching tasks after stroke: a randomized controlled trial. Stroke. 1997; 28:722–8.
23. Cabanas-Valdes R, Cuchi GU, Bagur-Calafat C. Trunk training exercises approaches for improving trunk performance and functional sitting balance in patients with stroke: a systematic review. NeuroRehabilitation. 2013; 33:575–92.
24. Staubli P, Nef T, Klamroth-Marganska V, Riener R. Effects of intensive arm training with the rehabilitation robot ARMin II in chronic stroke patients: four singlecases. J Neuroeng Rehabil. 2009; 6:46.
Article
25. Teasell R, Bayona N, Salter K, Hellings C, Bitensky J. Progress in clinical neurosciences: stroke recovery and rehabilitation. Can J Neurol Sci. 2006; 33:357–64.
Article
26. Maclean N, Pound P, Wolfe C, Rudd A. Qualitative analysis of stroke patients’ motivation for rehabilitation. BMJ. 2000; 321:1051–4.
Article
27. Lohse KR, Lang CE, Boyd LA. Is more better? Using metadata to explore dose-response relationships in stroke rehabilitation. Stroke. 2014; 45:2053–8.
Article
28. Hsieh YW, Wu CY, Lin KC, Yao G, Wu KY, Chang YJ. Dose-response relationship of robot-assisted stroke motor rehabilitation: the impact of initial motor status. Stroke. 2012; 43:2729–34.
Full Text Links
  • ARM
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr