影响脑卒中患者脑机接口上肢训练效果的相关因素

doi:10.3969/j.issn.1006-9771.2021.03.004

《中国康复理论与实践》 ›› 2021, Vol. 27 ›› Issue (3): 269-276.doi: 10.3969/j.issn.1006-9771.2021.03.004

影响脑卒中患者脑机接口上肢训练效果的相关因素

吴琼¹,葛云祥²,马迪¹,庞雪¹,曹莹瑜³,潘钰¹(),窦维蓓^2,⁴()

^1.清华大学附属北京清华长庚医院/清华大学临床医学院康复医学科，北京市 102218
^2.清华大学电子工程系，北京市 100084
^3.北京石油化工学院光机电装备技术北京市重点实验室，北京市 102617
^4.北京信息科学与技术国家研究中心，北京市 100084

收稿日期:2020-06-18 修回日期:2020-08-03 出版日期:2021-03-25 发布日期:2021-04-02
通讯作者: 潘钰,窦维蓓 E-mail:py10335@163.com;douwb@tsinghua.edu.cn
作者简介:吴琼(1982-)，女，满族，山西晋中市人，硕士，主治医师，主要研究方向：神经康复、脑机接口技术。
基金资助:
北京市科技计划课题(Z181100009218003);北京市自然科学基金项目(L182028);光机电装备技术北京重点实验室开放基金项目(BTPT-OMET-OF-2020-1)

Factors Related to Curative Effect of Brain-computer Interface Training on Upper Limb Paralysis after Stroke

Qiong WU¹,Yun-xiang GE²,Di MA¹,Xue PANG¹,Ying-yu CAO³,Yu PAN¹(),Wei-bei DOU^2,⁴()

^1.Department of Rehabilitation Medicine, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China
^2.Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
^3.Beijing Institute of Petrochemical Technology, Beijing 102617, China
^4.Beijing National Research Center for Information Science and Technology, Beijing 100084, China

Received:2020-06-18 Revised:2020-08-03 Published:2021-03-25 Online:2021-04-02
Contact: Yu PAN,Wei-bei DOU E-mail:py10335@163.com;douwb@tsinghua.edu.cn
Supported by:
Beijing Science and Technology Plan(Z181100009218003);Beijing Natural Science Foundation(L182028);Opto-Mechatronic Equipment Technology Beijing Area Major Laboratory, Beijing Institute of Petrochemical Technology(BTPT-OMET-OF-2020-1)

摘要/Abstract

摘要： 目的

探讨影响接受基于运动想象的脑机接口(MI-BCI)综合康复训练的亚急性期脑卒中患者上肢运动功能疗效的相关因素。

方法

2018年1月至2019年7月，北京清华长庚医院完成MI-BCI综合康复训练的脑卒中患者23例，收集性别、年龄、病程、是否伴有失语症、病变部位、病变性质、是否使用肉毒毒素、损伤半球、患侧手指屈肌改良Ashworth量表(MAS)评分。训练前后采用Fugl-Meyer评定量表上肢部分(FMA-UE)进行评定，以训练后FMA-UE腕手部分评分提高≥ 2分为标准，将患者分为显效组(n = 11)和非显效组(n = 12)。

结果

训练前，非显效组患侧手指屈肌MAS评分(t = 2.677, P < 0.05)和曾使用肉毒毒素人数(Z = 0.000, P < 0.05)高于显效组；训练后FMA-UE总分及各项评分与训练前FMA-UE相应评分呈正相关(r > 0.831, P < 0.01)；是否伴失语症与训练后FMA-UE总分(Eta = 0.453, P < 0.05)和上臂评分(Eta = 0.506, P < 0.05)相关；患侧手指屈肌MAS评分与训练后FMA-UE腕手评分呈负相关(r = -0.521, P < 0.05)。

结论

基础运动功能较差、伴有言语障碍和痉挛可能是影响脑卒中上肢功能障碍患者MI-BCI训练效果的不利因素。

关键词: 脑卒中, 脑机接口, 上肢, 运动功能, 康复, 相关因素

Abstract: Objective

To explore the factors affecting curative effect of motor imagery brain-computer interface (MI-BCI) training on upper limb paralysis for subacute stroke patients.

Methods

From January, 2018 to July, 2019, 23 inpatients with post-stroke upper limb paralysis accepting MI-BCI training were reviewed. The gender, age, course of disease, aphasia, location and nature of lesion, history of Botulinum toxin, hemisphere injured and modified Ashworth Scale (MAS) score of affected fingers were recorded, and they were assessed with Fugl-Meyer Assessment-Upper Extremities (FMA-UE) before and four weeks after MI-BCI training. According to improvement of FMA-UE wrist and hand scores (≥ 2), the patients were divided into effective group (n = 11) and inefficacy group (n = 12).

Results

The MAS scores before MI-BCI training (t = 2.677, P < 0.05) and history of botulinum toxin (Z = 0.000, P < 0.05) were more in the inefficacy group than in the efficacy group. FMA-UE scores (total and dimensions) after training were correlated to their baseline levels (r > 0.831, P < 0.01), FMA-UE total scores (Eta = 0.453, P < 0.05) and upper arms scores (Eta = 0.506, P < 0.05) were correlated to aphasia, FMA-UE scores of hands were correlated with MAS (r = -0.521, P < 0.05).

Conclusion

Poor baseline motor function, spasticity and complication with aphasia were the factors unfavorable to MI-BCI training for subacute stroke patients with upper limb paralysis.

Key words: stroke, brain-computer interface, upper limb, motor function, rehabilitation, relative factors

中图分类号:

R743.3

吴琼,葛云祥,马迪,庞雪,曹莹瑜,潘钰,窦维蓓. 影响脑卒中患者脑机接口上肢训练效果的相关因素[J]. 《中国康复理论与实践》, 2021, 27(3): 269-276.

Qiong WU,Yun-xiang GE,Di MA,Xue PANG,Ying-yu CAO,Yu PAN,Wei-bei DOU. Factors Related to Curative Effect of Brain-computer Interface Training on Upper Limb Paralysis after Stroke[J]. 《Chinese Journal of Rehabilitation Theory and Practice》, 2021, 27(3): 269-276.

图/表 8

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参考文献 36

1	Biasiucci A, Leeb R, Iturrate I, et al. Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke [J]. Nat Commun, 2018, 9(1): 2421.
2	Carino-Escobar R I, Carrillo-Mora P, Valdés-Cristerna R, et al. Longitudinal analysis of stroke patients' brain rhythms during an intervention with a brain-computer interface [J]. Neural Plast, 2019, 2019(7084618): 1-11.
3	Rosenfeld J V, Wong Y T. Neurobionics and the brain-computer interface: current applications and future horizons [J]. Med J Aust, 2017, 206(8): 363-368.
4	Mattia D, Pichiorri F, Colamarino E, et al. The promotoer, a brain-computer interface-assisted intervention to promote upper limb functional motor recovery after stroke: a study protocol for a randomized controlled trial to test early and long-term efficacy and to identify determinants of response [J]. BMC Neurol, 2020, 20(1): 254.
5	Jeunet C, N'Kaoua B, Subramanian S, et al. Predicting mental imagery-based BCI performance from personality, cognitive profile and neurophysiological patterns [J]. PLoS One, 2015, 10(12): e0143962.
6	郑玉甫,许敏鹏,明东. 脑-机接口操控效果差异及其预测研究综述[J]. 中国生物医学工程学报, 2018, 37(6): 749-755.
	Zheng Y F, Xu M P, Ming D. Research advancements on the variation and prediction of brain control performance for brain-computer interfaces (BCIs) [J]. Chin J Biomed Engin, 2018, 37(6): 749-755.
7	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. 中国急性脑卒中临床研究规范共识2018 [J]. 中华神经科杂志, 2018, 51(4): 247-255.
	Neurology Branch of Chinese Medical Association, Cerebrovascular Group of Neurology Branch of Chinese Medical Association. Chinese Consensus for Clinical Study Standards of Acute Stroke 2018 [J]. Chin J Neurol, 2018, 51(4): 247-255.
8	Wu Q, Yue Z, Ge Y, et al. Brain functional networks study of subacute stroke patients with upper limb dysfunction after comprehensive rehabilitation including BCI training [J]. Front Neurol, 2019, 10: 1419.
9	张填,冯晓丽,王埮,等. H型高血压与急性脑梗死牛津郡社区卒中项目分型及近期预后的关系[J]. 中国全科医学, 2019, 22(25): 3110-3115.
	Zhang T, Feng X L, Wang T, et al. Relationship of H-type hypertension with Oxfordshire Community Stroke Project classification and short-term outcome of acute cerebral infarction [J]. Chin Gener Prac, 2019, 22(25): 3110-3115.
10	吴琼,任诗媛,乐赞,等. 脑机接口综合康复训练对亚急性期脑卒中疗效的静息态功能磁共振研究[J]. 中国康复理论与实践, 2020, 26(1): 77-84.
	Wu Q, Ren S Y, Yue Z, et al. Brain-computer interface and comprehensive training for stroke: a resting state functional magnetic resonance imaging study [J]. Chin J Rehabil Theory Pract, 2020, 26(1): 77-84.
11	刘霖,朱琳,侯敬贤,等. 布勒茨手部测试量表在卒中急性期上肢及手功能障碍患者中的初步应用分析[J]. 中国脑血管病杂志, 2019, 16(2): 20-23, 29.
	Liu L, Zhu L, Hou J X, et al. Preliminary application analysis of Broetz hand test in patients with upper limb and hand dysfunction in acute stage of stroke [J]. Chin J Cerebrovasc Dis, 2019, 16(2): 20-23, 29.
12	Plantin J, Pennati G V, Roca P, et al. Quantitative assessment of hand spasticity after stroke: imaging correlates and impact on motor recovery [J]. Front Neurol, 2019, 10: 836.
13	董燕. A型肉毒毒素治疗脑损伤后上下肢痉挛的效果和安全性分析:系统综述及meta分析[D]. 南京:南京医科大学, 2019.
	Dong Y. Efficacy and safety of Botulinum toxin type A for upper limb spasticity after stroke or traumatic brain injury: a systematic review with meta-analysis and trial sequential [D]. Nanjing: Nanjing Medical University, 2019.
14	芦海涛,崔利华,王艺铮. 不同方式引导肉毒毒素注射治疗脑卒中后屈腕屈指肌痉挛的效果比较[J]. 中国康复理论与实践, 2019, 25(11): 1352-1355.
	Lu H T, Cui L H, Wang Y Z. Comparation of effects of Botulinum toxin type A injection under different guidance approaches on wrist and finger spasticity in stroke patients [J]. Chin J Rehabil Theory Pract, 2019, 25(11): 1352-1355.
15	Woytowicz E J, Rietschel J C, Goodman R N, et al. Determining levels of upper extremity movement impairment by applying a cluster analysis to the Fugl-Meyer Assessment of the upper extremity in chronic stroke [J]. Arch Phys Med Rehabil, 2017, 98(3): 456-462.
16	Arya K N, Verma R, Garg R K. Estimating the minimal clinically important difference of an upper extremity recovery measure in subacute stroke patients [J]. Top Stroke Rehabil, 2011, 18(): 599-610.
17	Delavaran H, Aked J, Sjunnesson H, et al. Spontaneous recovery of upper extremity motor impairment after ischemic stroke: implications for stem cell-based therapeutic approaches [J]. Transl Stroke Res, 2017, 8(4): 351-361.
18	Kuceyeski A, Navi B B, Kamel H, et al. Structural connectome disruption at baseline predicts 6-months post-stroke outcome [J]. Hum Brain Mapp, 2016, 37(7): 2587-2601.
19	Haselbach D, Renggli A, Carda S, et al. Determinants of neurological functional recovery potential after stroke in young adults [J]. Cerebrovasc Dis Extra, 2014, 4(1): 77-83.
20	Abdel Majeed Y, Awadalla S S, Patton J L. Regression techniques employing feature selection to predict clinical outcomes in stroke [J]. PLoS One, 2018, 13(10): e0205639.
21	Katrak P H. Shoulder shrug: a prognostic sign for recovery of hand movement after stroke [J]. Med J Aust, 1990, 152(6): 297-301.
22	Winters C, van Wegen E E, Daffertshofer A, et al. Generalizability of the proportional recovery model for the upper extremity after an ischemic stroke [J]. Neurorehabil Neural Repair, 2015, 29(7): 614-622.
23	Lindow J, Domin M, Grothe M, et al. Connectivity-based predictions of hand motor outcome for patients at the subacute stage after stroke [J]. Front Hum Neurosci, 2016, 10: 101.
24	Pitt K M, Brumberg J S. Guidelines for feature matching assessment of brain-computer interfaces for augmentative and alternative communication [J]. Am J Speech Lang Pathol, 2018, 27(3): 950-964.
25	Wortman-Jutt S, Edwards D. Poststroke aphasia rehabilitation: why all talk and no action? [J]. Neurorehabil Neural Repair, 2019, 33(4): 235-244.
26	Frolov A A, Mokienko O, Lyukmanov R, et al. Post-stroke rehabilitation training with a motor-imagery-based brain-computer interface (BCI)-controlled hand exoskeleton: a randomized controlled multicenter trial [J]. Front Neurosci, 2017, 11: 400.
27	Liew S L, Garrison K A, Ito K L, et al. Laterality of poststroke cortical motor activity during action observation is related to hemispheric dominance [J]. Neural Plast, 2018, 2018: 3524960.
28	Kasahara K, DaSalla C S, Honda M, et al. Neuroanatomical correlates of brain-computer interface performance [J]. Neuroimage, 2015, 110: 95-100.
29	van der Vliet R, Selles R W, Andrinopoulou E R, et al. Predicting upper limb motor impairment recovery after stroke: a mixture model [J]. Ann Neurol, 2020, 87(3): 383-393.
30	Kadosh K C, Staunton G. A systematic review of the psychological factors that influence neurofeedback learning outcomes [J]. Neuroimage, 2019, 185: 545-555.
31	Zich C, Debener S, de Vos M, et al. Lateralization patterns of covert but not overt movements change with age: an EEG neurofeedback study [J]. Neuroimage, 2015, 116: 80-91.
32	Jeunet C, Lotte F, Batail J M, et al. Using recent BCI literature to deepen our understanding of clinical neurofeedback: a short review [J]. Neuroscience, 2018, 378: 225-233.
33	Zapała D, Zabielska-Mendyk E, Augustynowicz P, et al. The effects of handedness on sensorimotor rhythm desynchronization and motor-imagery BCI control [J]. Sci Rep, 2020, 10(1): 2087.
34	Lyukmanov R K, Aziatskaya G A, Mokienko O A, et al. Post-stroke rehabilitation training with a brain-computer interface: a clinical and neuropsychological study [J]. Zh Nevrol Psikhiatr Im S S Korsakova, 2018, 118(8): 43-51.
35	Shu X, Chen S, Yao L, et al. Fast recognition of BCI-inefficient users using physiological features from EEG signals: a screening study of stroke patients [J]. Front Neurosci, 2018, 12: 93.
36	Mane R, Chew E, Phua K S, et al. Prognostic and monitory EEG-biomarkers for BCI upper-limb stroke rehabilitation [J]. IEEE Trans Neural Syst Rehabil Eng, 2019, 27(8): 1654-1664.

项目		统计值
性别(n)	男性	17
性别(n)	女性	6
年龄(岁)		58.30±10.70
病程(月)		2.00(1.00, 5.00)
病变性质(n)	脑出血	7
病变性质(n)	脑梗死	16
病变部位(n)	部分前循环	20
病变部位(n)	后循环	3
是否使用肉毒毒素(n)	是	17
是否使用肉毒毒素(n)	否	6
是否伴失语(n)	是	4
是否伴失语(n)	否	19
损伤半球(n)	右侧	9
损伤半球(n)	左侧	14

项目	训练前	训练后	t/Z值	P值
MAS	1.000(1.00, 2.00)	1.000(1.00, 2.00)	1.732	0.083
FMA-UE总分	23.17±16.40	33.87±17.45	-5.180	< 0.001
FMA腕手分	4.00(0.00, 11.00)	10.00(4.00, 15.00)	3.628	< 0.001
FMA上臂分	11.00(3.00, 17.00)	21.00(9.00, 28.00)	3.748	< 0.001

组别	n	训练前	训练后	差值	t值^a	P值^a
非显效组	12	19.08±14.53	24.42±15.05	5.33±4.10	-4.509	0.001
显效组	11	27.64±17.82	44.18±14.02	16.55±11.18	-4.907	0.001
t值		-1.266	-3.250	3.138
P值		0.219	0.004	0.008

组别	n	训练前	训练后	差值	Z值^a	P值^a
非显效组	12	5.00(0.00, 10.75)	6.33±5.85	0.50(0.00, 2.00)	-2.271	0.023
显效组	11	3.00(0.00, 12.00)	14.82±6.40	8.00(5.00, 10.00)	-2.938	0.003
Z/t值		0.339	-3.322	4.112
P值		0.735	0.003	< 0.001

组别	n	训练前	训练后	差值	Z值^a	P值^a
非显效组	12	7.50(2.00, 16.75)	9.50(5.00, 22.00)	3.50(1.00, 5.80)	-2.763	0.006
显效组	11	13.00(3.00, 30.00)	23.00(16.00, 30.00)	6.00(0.00, 17.00)	-2.527	0.012
Z值		-1.139	2.349	1.175
P值		0.255	0.019	0.240

影响脑卒中患者脑机接口上肢训练效果的相关因素

Factors Related to Curative Effect of Brain-computer Interface Training on Upper Limb Paralysis after Stroke

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组别	n	训练前	训练后	Z值	P值
非显效组	12	2.00(1.25, 2.00)	2.00(1.10, 2.00)	1.414	1.000
显效组	11	1.00(0.00, 1.00)	1.00(0.00, 1.00)	0.157	0.317
Z值		2.677	2.968
P值		0.007	0.003

项目		非显效组(n = 12)	显效组(n = 11)	χ²/t/Z值	P值
性别(n)	男	11	6	9.167	0.069
	女	1	5
年龄(岁)		54.17±11.33	62.82±8.24	-2.077	0.050
病程(月)		3.50(1.10, 6.50)	1.00(1.00, 4.00)	1.305	0.192
病变性质(n)	脑出血	4	3	1.333	1.000
	脑梗死	8	8
病变部位(n)	部分前循环	11	9	0.409	0.590
	后循环	1	2
是否使用肉毒毒素(n)	是	6	11	0.000	0.014
	否	6	0
是否伴失语(n)	是	3	1	3.333	0.590
	否	9	10
损伤半球(n)	右侧	5	4	1.251	1.000
	左侧	7	7

项目	相关系数	训练后FMA-UE总分	训练后FMA-UE腕手分	训练后FMA-UE上臂分
性别	Eta值	0.312	0.302	0.284
	t值	1.474	1.425	-1.487
	P值	0.155	0.169	0.152
病变性质	Eta值	0.014	0.212	0.154
	t值	-0.059	-1.711	-0.104
	P值	0.561	0.102	0.918
病变部位	Eta值	0.362	0.340	0.340
	t值	1.759	1.642	-1.734
	P值	0.087	0.121	0.083
是否使用肉毒毒素	Eta值	0.201	0.143	0.218
	t值	0.928	0.657	1.019
	P值	0.364	0.518	0.320
是否伴失语	Eta值	0.453	0.314	0.506
	t值	2.332	1.498	2.767
	P值	0.030	0.149	0.012
损伤半球	Eta值	0.103	0.152	0.047
	t值	-0.437	-0.714	-0.066
	P值	0.667	0.483	0.948
年龄	r值	-0.065	0.070	-0.123
	P值	0.767	0.750	0.576
病程	r值	0.117	0.088	0.207
	P值	0.596	0.690	0.343
训练前MAS评分	r值	-0.409	-0.521	-0.319
	P值	0.052	0.011	0.138
训练前FMA-UE总分	r值	0.831	0.727	0.804
	P值	< 0.001	< 0.001	< 0.001
训练前FMA腕手分	r值	0.685	0.725	0.613
	P值	< 0.001	< 0.001	0.002
训练前FMA上臂分	r值	0.807	0.663	0.806
	P值	< 0.001	0.001	< 0.001

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