Investigation of brain computer interface combined with wrist passive motion training in chronic stroke patients_West China Medical Journal

Authors：

LU Rongrong ¹ , GAO Tianhao ¹ , LI Jie ² , BAI Yulong ¹ , PANG Zilong ² ,  WU Yi ¹

1. Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, P. R. China;
2. Department of Computer Science and Technology, School of Electronics and Information Engineering, Tongji University, Shanghai 200092, P. R. China;

Corresponding author：

WU Yi, Email: wuyi4000@163.com

Keywords：

Stroke; Brain computer interface; Motor imagery; Motor recovery

DOI：

10.7507/1002-0179.201903229

Video：

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Objective To investigate the feasibility and effectiveness of motor imagery based brain computer interface with wrist passive movement in chronic stroke patients with wrist extension impairment.Methods Fifteen chronic stroke patients with a mean age of (47.60±14.66) years were recruited from March 2017 to June 2018. At baseline, motor imagery ability was assessed first. Then motor imagery based brain computer interface with wrist passive movement was given as an intervention. Both range of motion of paretic wrist and Barthel index was assessed before and after the intervention.Results Among the 15 chronic stroke patients admitted in the study, 12 finished the whole therapy, and 3 failed to pass the initial assessment. After the therapy, the 12 participants who completed the whole sessions of the treatment and follow up had improved ability of control electroencephalogram, in whom 9 regained the ability to actively extend the affected wrist, and the other 3 failed to actively extend their wrist (the rate of active extending wrist was 75%). The activity of daily life of all the participants did not change significantly before and after intervention, and no discomfort was found after daily treatment.Conclusion In chronic stroke patients with wrist extension impairment, motor imagery based brain computer interface with wrist passive movement training is feasible and effective.

Citation： LU Rongrong, GAO Tianhao, LI Jie, BAI Yulong, PANG Zilong, WU Yi. Investigation of brain computer interface combined with wrist passive motion training in chronic stroke patients. West China Medical Journal, 2019, 34(9): 1028-1032. doi: 10.7507/1002-0179.201903229 Copy

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24.	Buch E, Weber C, Cohen LG, et al. Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke, 2008, 39(3): 910-917.
25.	Wolpaw JR, Birbaumer N, Heetderks WJ, et al. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng, 2000, 8(2): 164-173.
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27.	McCrimmon CM, King CE, Wang PT, et al. Brain-controlled functional electrical stimulation therapy for gait rehabilitation after stroke: a safety study. J Neuroeng Rehabil, 2015, 12: 57.

1. Feigin VL, Forouzanfar MH, Krishnamurthi R, et al. Global and regional burden of stroke during 1990-2010: findings from the Global Burden of Disease Study 2010. Lancet, 2014, 383(9913): 245-255.
2. Benjamin EJ, Blaha MJ, Chiuve SE, et al. Heart disease and stroke statistics-2017 update: a report from the American Heart Association. Circulation, 2017, 135(10): e146-e603.
3. 陈伟伟, 高润霖, 刘力生, 等. 《中国心血管病报告2016》概要. 中国循环杂志, 2017, 32(6): 521-530.
4. Langhorne P, Coupar F, Pollock A. Motor recovery after stroke: a systematic review. Lancet Neurol, 2009, 8(8): 741-754.
5. Langhorne P, Bernhardt J, Kwakkel G. Stroke rehabilitation. Lancet, 2011, 377(9778): 1693-1702.
6. 陆蓉蓉, 吴毅. 脑机接口技术在康复中的应用. 中华物理医学与康复杂志, 2009, 31(10): 715-718.
7. Blain-Moraes S, Schaff R, Gruis KL, et al. Barriers to and mediators of brain-computer interface user acceptance: focus group findings. Ergonomics, 2012, 55(5): 516-525.
8. Jackson PL, Lafleur MF, Malouin F. Potential role of mental practice using motor imagery in neurologic rehabilitation. Arch Phys Med Rehabil, 2001, 82(8): 1133-1141.
9. Ietswaart M, Johnston M, Dijkerman HC, et al. Mental practice with motor imagery in stroke recovery: randomized controlled trial of efficacy. Brain, 2011, 134(Pt 5): 1373-1386.
10. Ang KK, Chua KS, Phua KS, et al. A randomized controlled trial of EEG-based motor imagery brain-computer interface robotic rehabilitation for stroke. Clin EEG Neurosci, 2015, 46(4): 310-320.
11. Mrachacz-Kersting N, Jiang N, Stevenson AJ, et al. Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface. J Neurophysiol, 2016, 115(3): 1410-1421.
12. van Dokkum LE, Ward T, Laffont I. Brain computer interfaces for neurorehabilitation - its current status as a rehabilitation strategy post-stroke. Ann Phys Rehabil Med, 2015, 58(1): 3-8.
13. Taherian S, Selitskiy D, Pau J, et al. Training to use a commercial brain-computer interface as access technology: a case study. Disabil Rehabil Assist Technol, 2016, 11(4): 345-350.
14. Chung E, Kim JH, Park DS, et al. Effects of brain-computer interface-based functional electrical stimulation on brain activation in stroke patients: a pilot randomized controlled trial. J Phys Ther Sci, 2015, 27(3): 559-562.
15. Jang YY, Kim TH, Lee BH. Effects of brain-computer interface-controlled functional electrical stimulation training on shoulder subluxation for patients with stroke: a randomized controlled trial. Occup Ther Int, 2016, 23(2): 175-185.
16. Cuccurullo SJ. Physical medicine and rehabilitation board review. 3rd Edition. New York: Demos Medical Publishing, 2014: 18-19, 26-47.
17. Kübler A, Nijboer F, Mellinger J, et al. Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. Neurology, 2005, 64(10): 1775-1777.
18. 中华医学会神经病学分会, 中华医学会神经病学分会脑血管病学组. 中国脑血管疾病分类2015. 中华神经科杂志, 2017, 50(3): 168-171.
19. Dick JP, Guiloff RJ, Stewart A, et al. Mini-mental state examination in neurological patients. J Neurol Neurosurg Psychiatry, 1984, 47(5): 496-499.
20. 陆蓉蓉, 高天昊, 黄崧华, 等. 脑-计算机接口技术辅助治疗脑梗死后上肢运动功能障碍. 中华物理医学与康复杂志, 2017, 39(5): 386-388.
21. 王茂斌. 康复医学. 北京: 人民卫生出版社, 2009: 87, 164-164.
22. Müller-Putz GR, Scherer R, Pfurtscheller G, et al. EEG-based neuroprosthesis control: a step towards clinical practice. Neurosci Lett, 2005, 382(1-2): 169-174.
23. Enzinger C, Ropele S, Fazekas F, et al. Brain motor system function in a patient with complete spinal cord injury following extensive brain-computer interface training. Exp Brain Res, 2008, 190(2): 215-223.
24. Buch E, Weber C, Cohen LG, et al. Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke, 2008, 39(3): 910-917.
25. Wolpaw JR, Birbaumer N, Heetderks WJ, et al. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng, 2000, 8(2): 164-173.
26. Twitchell TE. The restoration of motor function following hemiplegia in man. Brain, 1951, 74(4): 443-480.
27. McCrimmon CM, King CE, Wang PT, et al. Brain-controlled functional electrical stimulation therapy for gait rehabilitation after stroke: a safety study. J Neuroeng Rehabil, 2015, 12: 57.

West China Medical Journal

Investigation of brain computer interface combined with wrist passive motion training in chronic stroke patients

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