脑机接口技术在脊髓损伤治疗领域的文献计量分析

doi:10.3969/j.issn.1006-9771.2026.03.008

摘要/Abstract

摘要：

目的分析脑机接口技术在脊髓损伤治疗领域的研究热点和发展趋势。

方法检索 Web of Science核心合集数据库建库至2025年7月收录的脑机接口技术在脊髓损伤治疗领域的相关文献，采用CiteSpace、VOSviewer、Tableau Desktop等工具进行可视化分析。

结果共纳入437篇文献，年发文量整体呈现逐渐增长趋势。发文量最多的国家是美国，发文量最多的机构是Graz University of Technology，发文量最多的作者是Gernot R Mueller-Putz，被引频次最多的作者是Jonathan R Wolpaw；brain-computer interface和artificial intelligence是领域内的高频关键词和突现词。形成神经科学和康复医学、生物医学工程、计算机科学和人工智能、神经生理学、材料科学等五大核心学科交叉融合的研究特点。

结论脑机接口技术在脊髓损伤治疗领域研究持续加速，技术融合成为核心趋势。

关键词: 脊髓损伤, 脑机接口, 文献计量学

Abstract:

Objective To analyze the research hotspots and development trends of brain-computer interface (BCI) in the treatment for spinal cord injury (SCI).

Methods Relevant literatures on BCI applied in SCI treatment, published from the inception of the Web of Science Core Collection to July, 2025, were retrieved. Visualization analysis was performed using CiteSpace, VOSviewer and Tableau Desktop.

Results A total of 437 literatures were included, and the annual number of publications showed an overall increasing trend. The United States ranked first in the number of publications; Graz University of Technology was the institution with the highest number of publication; Gernot R Mueller-Putz was the most productive author, while Jonathan R Wolpaw was the most cited author. Brain-computer interface and artificial intelligence were identified as the high-frequency and bursting keywords in this field. The researches were characterized by the cross-integration of five core disciplines: neuroscience and rehabilitation medicine, biomedical engineering, computer science and artificial intelligence, neurophysiology, and materials science.

Conclusion Researches on BCI in SCI treatment are accelerating continuously, and technological integration is becoming the core trend.

Key words: spinal cord injury, brain-computer interface, bibliometrics

中图分类号:

R651.2

孙奎, 黄海伦, 刘永皑, 高恒. 脑机接口技术在脊髓损伤治疗领域的文献计量分析[J]. 《中国康复理论与实践》, 2026, 32(3): 317-328.

SUN Kui, HUANG Hailun, LIU Yongai, GAO Heng. Brain-computer interface technology in treatment for spinal cord injury: a bibliometric analysis[J]. Chinese Journal of Rehabilitation Theory and Practice, 2026, 32(3): 317-328.

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参考文献 42

[1]	HU X, XU W, REN Y, et al. Spinal cord injury: molecular mechanisms and therapeutic interventions[J]. Signal Transduct Target Ther, 2023, 8(1): 245.
[2]	LI C, WU Z, ZHOU L, et al. Temporal and spatial cellular and molecular pathological alterations with single-cell resolution in the adult spinal cord after injury[J]. Signal Transduct Target Ther, 2022, 7(1): 65.
[3]	LU Y, SHANG Z, ZHANG W, et al. Global incidence and characteristics of spinal cord injury since 2000-2021: a systematic review and meta-analysis[J]. BMC Med, 2024, 22(1): 285. doi: 10.1186/s12916-024-03514-9 pmid: 38972971
[4]	ROWALD A, KOMI S, DEMESMAEKER R, et al. Activity-dependent spinal cord neuromodulation rapidly restores trunk and leg motor functions after complete paralysis[J]. Nat Med, 2022, 28(2): 260-271. doi: 10.1038/s41591-021-01663-5 pmid: 35132264
[5]	IZZY S. Traumatic spinal cord injury[J]. Continuum (Minneap Minn), 2024, 30(1): 53-72. doi: 10.1212/CON.0000000000001392 pmid: 38330472
[6]	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. doi: 10.1186/s12883-020-01826-w pmid: 32593293
[7]	GAO X, WANG Y, CHEN X, et al. Interface, interaction, and intelligence in generalized brain-computer interfaces[J]. Trends Cogn Sci, 2021, 25(8): 671-684. doi: 10.1016/j.tics.2021.04.003 pmid: 34116918
[8]	GANZER P D, COLACHIS S C T, SCHWEMMER M A, et al. Restoring the sense of touch using a sensorimotor demultiplexing neural interface[J]. Cell, 2020, 181(4): 763-773.e12. doi: S0092-8674(20)30347-0 pmid: 32330415
[9]	HIRSCH J E. Does the H index have predictive power?[J]. Proc Natl Acad Sci U S A, 2007, 104(49): 19193-19198. doi: 10.1073/pnas.0707962104
[10]	ARRUDA H, SILVA E R, LESSA M, et al. VOSviewer and bibliometrix[J]. J Med Libr Assoc, 2022, 110(3): 392-395. doi: 10.5195/jmla.2022.1434 pmid: 36589296
[11]	VAN ECK N J, WALTMAN L. Citation-based clustering of publications using CitNetExplorer and VOSviewer[J]. Scientometrics, 2017, 111(2): 1053-1070. doi: 10.1007/s11192-017-2300-7 pmid: 28490825
[12]	CHEN C, HU Z, LIU S, et al. Emerging trends in regenerative medicine: a scientometric analysis in CiteSpace[J]. Expert Opin Biol Ther, 2012, 12(5): 593-608. doi: 10.1517/14712598.2012.674507 pmid: 22443895
[13]	KHALIL G M, GOTWAY CRAWFORD C A. A bibliometric analysis of U.S.-based research on the Behavioral Risk Factor Surveillance System[J]. Am J Prev Med, 2015, 48(1): 50-57. doi: 10.1016/j.amepre.2014.08.021 pmid: 25442231
[14]	WOLPAW J R, BIRBAUMER N, MCFARLAND D J, et al. Brain-computer interfaces for communication and control[J]. Clin Neurophysiol, 2002, 113(6): 767-791. doi: 10.1016/s1388-2457(02)00057-3 pmid: 12048038
[15]	HOCHBERG L R, SERRUYA M D, FRIEHS G M, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia[J]. Nature, 2006, 442(7099): 164-171. doi: 10.1038/nature04970
[16]	LOTTE F, CONGEDO M, LECUYER A, et al. A review of classification algorithms for EEG-based brain-computer interfaces[J]. J Neural Eng, 2007, 4(2): R1-R13.
[17]	NICOLAS-ALONSO L F, GOMEZ-GIL J J. Brain computer interfaces: a review[J]. Sensors, 2012, 12(2): 1211-1279. doi: 10.3390/s120201211
[18]	WOLPAW J R, MCFARLAND D J. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans[J]. Proc Natl Acad Sci U S A, 2004, 101(51): 17849-17854. doi: 10.1073/pnas.0403504101
[19]	AJIBOYE A B, WILLETT F R, YOUNG D R, et al. Restoration of reaching and grasping movements through brain-controlled muscle stimulation in a person with tetraplegia: a proof-of-concept demonstration[J]. Lancet, 2017, 389(10081): 1821-1830. doi: S0140-6736(17)30601-3 pmid: 28363483
[20]	MIDDENDORF M, MCMILLAN G, CALHOUN G, et al. Brain-computer interfaces based on the steady-state visual-evoked response[J]. IEEE Trans Rehabil Eng, 2000, 8(2): 211-214. doi: 10.1109/86.847819 pmid: 10896190
[21]	BIRBAUMER N. Breaking the silence: brain-computer interfaces (BCI) for communication and motor control[J]. Psychophysiology, 2006, 43(6): 517-532. doi: 10.1111/j.1469-8986.2006.00456.x pmid: 17076808
[22]	MÜLLER-PUTZ G R, PFURTSCHELLER G. Control of an electrical prosthesis with an SSVEP-based BCI[J]. IEEE Trans Biomed Eng, 2008, 55(1): 361-364. doi: 10.1109/TBME.2007.897815
[23]	SITARAM R, ZHANG H, GUAN C, et al. Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface[J]. NeuroImage, 2007, 34(4): 1416-1427. pmid: 17196832
[24]	ZHANG Q, XIAO Y, LIU Y, et al. Visualizing the intellectual structure and evolution of carbon neutrality research: a bibliometric analysis[J]. Environ Sci Pollut Res Int, 2023, 30(30): 75838-75862. doi: 10.1007/s11356-023-26082-6
[25]	MCFARLAND D J, WOLPAW J R. Brain-computer interfaces for communication and control[J]. Commun ACM, 2011, 54(5): 60-66. pmid: 21984822
[26]	INSAUSTI-DELGADO A, LOPEZ-LARRAZ E, NISHIMURA Y, et al. Non-invasive brain-spine interface: continuous control of trans-spinal magnetic stimulation using EEG[J]. Front Bioeng Biotechnol, 2022, 10: 975037. doi: 10.3389/fbioe.2022.975037
[27]	RUBIN D B, AJIBOYE A B, BAREFOOT L, et al. Interim safety profile from the feasibility study of the BrainGate neural interface system[J]. Neurology, 2023, 100(11): e1177-e1192. doi: 10.1212/WNL.0000000000201707 pmid: 36639237
[28]	MULLER-PUTZ G R, RUPP R, OFNER P, et al. Applying intuitive EEG-controlled grasp neuroprostheses in individuals with spinal cord injury: preliminary results from the MoreGrasp clinical feasibility study[J]. Annu Int Conf IEEE Eng Med Biol Soc, 2019: 5949-5955.
[29]	TOWNSEND G, GRAIMANN B, PFURTSCHELLER G. Continuous EEG classification during motor imagery: simulation of an asynchronous BCI[J]. IEEE Trans Neural Syst Rehabil Eng, 2004, 12(2): 258-265. doi: 10.1109/TNSRE.7333
[30]	IKEGAYA N, MALLELA A N, WARNKE P C, et al. A novel robot-assisted method for implanting intracortical sensorimotor devices for brain-computer interface studies: principles, surgical techniques, and challenges[J]. J Neurosurg, 2025, 142(5): 1280-1288. doi: 10.3171/2024.7.JNS241296
[31]	TIAN Y, YIN J, WANG C, et al. An ultraflexible electrode array for large-scale chronic recording in the nonhuman primate brain[J]. Adv Sci (Weinh), 2023, 10(33): e2302333.
[32]	BU Y, HARRINGTON D L, LEE R R, et al. Magnetoencephalogram-based brain-computer interface for hand-gesture decoding using deep learning[J]. Cereb Cortex, 2023, 33(14): 8942-8955. doi: 10.1093/cercor/bhad173 pmid: 37183188
[33]	DONOGHUE J P, NURMIKKO A, BLACK M, et al. Assistive technology and robotic control using motor cortex ensemble-based neural interface systems in humans with tetraplegia[J]. J Physiol, 2007, 579(Pt 3): 603-611. doi: 10.1113/jphysiol.2006.127209
[34]	LORACH H, GALVEZ A, SPAGNOLO V, et al. Walking naturally after spinal cord injury using a brain-spine interface[J]. Nature, 2023, 618(7963): 126-133. doi: 10.1038/s41586-023-06094-5
[35]	SHIFERAW B T, JIN M Y, PATEL M, et al. Deep brain stimulation and brain-spine interface for functional restoration in spinal cord injury[J]. Biomedicines, 2025, 13(3): 1-18. doi: 10.3390/biomedicines13010001
[36]	WANG X, WU S, YANG H, et al. Intravascular delivery of an ultraflexible neural electrode array for recordings of cortical spiking activity[J]. Nat Commun, 2024, 15(1): 9442. doi: 10.1038/s41467-024-53720-5 pmid: 39487147
[37]	FLESHER S N, DOWNEY J E, WEISS J M, et al. A brain-computer interface that evokes tactile sensations improves robotic arm control[J]. Science, 2021, 372(6544): 831-836. doi: 10.1126/science.abd0380 pmid: 34016775
[38]	CHO N, SQUAIR J W, AURELI V, et al. Hypothalamic deep brain stimulation augments walking after spinal cord injury[J]. Nat Med, 2024, 30(12): 3676-3686. doi: 10.1038/s41591-024-03306-x pmid: 39623087
[39]	BRUNNER I, LUNDQUIST C B, PEDERSEN A R, et al. Brain computer interface training with motor imagery and functional electrical stimulation for patients with severe upper limb paresis after stroke: a randomized controlled pilot trial[J]. J Neuroeng Rehabil, 2024, 21(1): 10. doi: 10.1186/s12984-024-01304-1 pmid: 38245782
[40]	MIAO Z, ZHAO M, ZHANG X, et al. LMDA-Net: a lightweight multi-dimensional attention network for general EEG-based brain-computer interfaces and interpretability[J]. NeuroImage, 2023, 276: 120209. doi: 10.1016/j.neuroimage.2023.120209
[41]	NADDAF M, DREW L. Second brain implant by Elon Musk's Neuralink: Will it fare better than the first?[J]. Nature, 2024, 632(8025): 481-482. doi: 10.1038/d41586-024-02368-8
[42]	MITCHELL P, LEE S C M, YOO P E, et al. Assessment of safety of a fully implanted endovascular brain-computer interface for severe paralysis in 4 patients: the Stentrode with thought-controlled digital switch (SWITCH) study[J]. JAMA Neurol, 2023, 80(3): 270-278. doi: 10.1001/jamaneurol.2022.4847 pmid: 36622685

期刊	发文量/n	总被引次数	篇均被引次数	影响因子	JCR分区
IEEE Transactions on Neural Systems and Rehabilitation Engineering	28	1776	63	5.2	Q1
Journal of Neural Engineering	26	2492	96	3.8	Q2
Frontiers in Neuroscience	25	784	31	3.2	Q2
Frontiers in Human Neuroscience	20	389	19	2.7	Q3
Journal of Neuroengineering and Rehabilitation	15	592	39	5.2	Q1
IEEE Transactions on Bio-Medical Engineering	15	1703	114	4.5	Q2
Sensors	11	1864	169	3.5	Q2
Biomedical Engineering-Biomedizinische Technik	9	19	2	1.8	Q4
Psychophysiology	7	451	64	2.8	Q3
Clinical Neurophysiology	6	5727	955	3.6	Q1

文献	期刊	引用次数
Wolpaw等^[14](2002)	Clinical Neurophysiology	5458
Hochberg等^[15](2006)	Nature	2358
Lotte等^[16](2007)	Journal of Neural Engineering	1787
Nicolas-Alonso等^[17](2012)	Sensors-basel	1419
Wolpaw等^[18](2004)	Proceedings of the National Academy of Sciences of the United States of America	1048
Ajiboye等^[19](2017)	Lancet	551
Middendorf等^[20](2000)	IEEE Transactions on Rehabilitation Engineering	500
Birbaumer^[21](2006)	Psychophysiology	450
Müller-Putz等^[22](2008)	IEEE Transactions on Rehabilitation Engineering	426
Sitaram等^[23](2007)	NeuroImage	421