Emerging role of brain-computer interface in orthopedic rehabilitation and motor function restoration_Chinese Journal of Reparative and Reconstructive Surgery

Authors：

DENG Qinwen ¹ , WU Kai ² , XIE Longhan ^3,4 , ZHANG Li ⁵ ,  WANG Huajun ¹ ,  ZHENG Xiaofei ¹

1. Department of Sports Medicine, the First Affiliated Hospital of Jinan University, Guangzhou Key Laboratory of Precision Orthopedics and Regenerative Medicine, Guangdong Key Laboratory of Speed Ability Research, Guangzhou Guangdong, 510632, P. R. China;
2. School of Biomedical Science and Engineering, South China University of Technology, Guangzhou Guangdong, 510641, P. R. China;
3. WU Xianming School of Intelligent Engineering, Guangzhou Guangdong, 511442, P. R. China;
4. South China University of Technology, LIZHI Intelligent Technology (Guangzhou) Co., Ltd., Guangzhou Guangdong, 511442, P. R. China;
5. Guangdong-Hong Kong-Macao Institute of Central Nervous System Regeneration, Jinan University, Guangzhou Guangdong, 510632, P. R. China;

Corresponding?author：

WANG Huajun, Email: whj323@126.com; ZHENG Xiaofei, Email: zhengxiaofei12@163.com

Keywords：

Brain-computer interface; anterior cruciate ligament reconstruction; stroke; spinal cord injury; orthopedic rehabilitation; motor function restoration

DOI：

10.7507/1002-1892.202602068

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Objective To review the research progress and application prospects of brain-computer interface (BCI) in orthopedic rehabilitation and motor function restoration. Methods Through literature analysis, the neurophysiological mechanisms of BCI in improving central motor drive deficits, technical paradigms, and clinical evidence in quadriceps inhibition after anterior cruciate ligament reconstruction and other orthopedic conditions were summarized, and the challenges in clinical translation were discussed. Results BCI decodes movement-related neural signals and establishes closed-loop feedback between central and peripheral systems, which can enhance corticospinal tract excitability, induce neuroplasticity, and alleviate postoperative muscle inhibition and dysfunction caused by insufficient central motor drive. Available evidence indicates that motor imagery-based BCI training can improve quadriceps voluntary activation rate and reduce muscle strength loss after surgery, showing potential intervention value in other orthopedic conditions. Conclusion BCI holds promise as an important adjunct to conventional orthopedic rehabilitation, particularly for patients with central motor drive deficits. However, its clinical translation still faces challenges including insufficient mechanistic evidence, high patient heterogeneity, and lack of standardized training protocols, which represent key directions for future research.

Citation： DENG Qinwen, WU Kai, XIE Longhan, ZHANG Li, WANG Huajun, ZHENG Xiaofei. Emerging role of brain-computer interface in orthopedic rehabilitation and motor function restoration. Chinese Journal of Reparative and Reconstructive Surgery, 2026, 40(8): 1314-1319. doi: 10.7507/1002-1892.202602068 Copy

1.	Zarzycki R, Morton SM, Charalambous CC, et al. Corticospinal and intracortical excitability differ between athletes early after ACLR and matched controls[J]. J Orthop Res, 2018, 36(11): 2941-2948.
2.	Sherman DA, Beausejour JP, Koohestani M, et al. Quadriceps motor unit properties following ACL reconstruction are associated with corticospinal excitability and motor cortex activations[J]. J Appl Physiol (1985), 2025, 138(4): 1011-1023.
3.	Sherman DA, Rush J, Stock MS, et al. Neural drive and motor unit characteristics after anterior cruciate ligament reconstruction: implications for quadriceps weakness[J/OL]. PeerJ, 2023, 11: e16261. doi: 10.7717/peerj.16261.
4.	Héroux ME, Tremblay F. Corticomotor excitability associated with unilateral knee dysfunction secondary to anterior cruciate ligament injury[J]. Knee Surg Sports Traumatol Arthrosc, 2006, 14(9): 823-833.
5.	Grooms DR, Page SJ, Nichols-Larsen DS, et al. Neuroplasticity associated with anterior cruciate ligament reconstruction[J]. J Orthop Sports Phys Ther, 2017, 47(3): 180-189.
6.	Patel HH, Berlinberg EJ, Nwachukwu B, et al. Quadriceps weakness is associated with neuroplastic changes within specific corticospinal pathways and brain areas after anterior cruciate ligament reconstruction: Theoretical utility of motor imagery-based brain-computer interface technology for rehabilitation[J/OL]. Arthrosc Sports Med Rehabil, 2022, 5(1): e207-e216.
7.	Kapreli E, Athanasopoulos S. The anterior cruciate ligament deficiency as a model of brain plasticity[J]. Med Hypotheses, 2006, 67(3): 645-650.
8.	Needle AR, Lepley AS, Grooms DR. Central nervous system adaptation after ligamentous injury: a summary of theories, evidence, and clinical interpretation[J]. Sports Med, 2017, 47(7): 1271-1288.
9.	Neige C, Ciechelski V, Lebon F. The recruitment of indirect waves within primary motor cortex during motor imagery: A directional transcranial magnetic stimulation study[J]. Eur J Neurosci, 2022, 56(12): 6187-6200.
10.	Sengupta P, Lakshminarayanan K. Motor imagery of finger movements: Effects on cortical and muscle activities[J/OL]. Behav Brain Res, 2024, 471: 115100. doi: 10.1016/j.bbr.2024.115100.
11.	Chung E, Park SI, Jang YY, et al. Effects of brain-computer interface-based functional electrical stimulation on balance and gait function in patients with stroke: preliminary results[J]. J Phys Ther Sci, 2015, 27(2): 513-516.
12.	Mrachacz-Kersting N, Jiang N, Stevenson AJ, et al. Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface[J]. J Neurophysiol, 2016, 115(3): 1410-1421.
13.	Chung E, Lee BH, Hwang S. Therapeutic effects of brain-computer interface-controlled functional electrical stimulation training on balance and gait performance for stroke: A pilot randomized controlled trial[J/OL]. Medicine (Baltimore), 2020, 99(51): e22612. doi: 10.1097/MD.0000000000022612.
14.	Stefan K, Kunesch E, Benecke R, et al. Mechanisms of enhancement of human motor cortex excitability induced by interventional paired associative stimulation[J]. J Physiol, 2002, 543(Pt 2): 699-708.
15.	Lebon F, Guillot A, Collet C. Increased muscle activation following motor imagery during the rehabilitation of the anterior cruciate ligament[J]. Appl Psychophysiol Biofeedback, 2012, 37(1): 45-51.
16.	Paravlic AH, Maffulli N, Kova? S, et al. Home-based motor imagery intervention improves functional performance following total knee arthroplasty in the short term: a randomized controlled trial[J/OL]. J Orthop Surg Res, 2020, 15(1): 451. doi: 10.1186/s13018-020-01964-4.
17.	Li R, Du J, Yang K, et al. Effectiveness of motor imagery for improving functional performance after total knee arthroplasty: a systematic review with meta-analysis[J/OL]. J Orthop Surg Res, 2022, 17(1): 65. doi: 10.1186/s13018-022-02946-4.
18.	Yu F, Rao Z, Chen N, et al. ArmBCIsys: Robot arm BCI system with time-frequency network for multiobject grasping[J]. IEEE Trans Neural Netw Learn Syst, 2025, 36(10): 18327-18341.
19.	Romeni S, Losanno E, Emedoli D, et al. High-frequency epidural electrical stimulation reduces spasticity and facilitates walking recovery in patients with spinal cord injury[J/OL]. Sci Transl Med, 2025, 17(780): eadp9607. doi: 10.1126/scitranslmed.adp9607.
20.	Chhabra HS, Kalidindi KKV, Garg N, et al. Spinal epidural electrical stimulation for the recovery of motor function in lower limbs after spinal cord injury: A pilot study[J]. J Spinal Cord Med, 2026, 49(4): 692-703.
21.	劉文慧, 孫文婷, 胡耐翀, 等. 神經電刺激調控技術在脊髓損傷后康復治療中的應用及效應機制[J]. 康復學報, 2024, 34(6): 633-640.
22.	Liao W, Li J, Zhang X, et al. Motor imagery brain-computer interface rehabilitation system enhances upper limb performance and improves brain activity in stroke patients: A clinical study[J/OL]. Front Hum Neurosci, 2023, 17: 1117670. doi: 10.3389/fnhum.2023.1117670.
23.	Wang A, Tian X, Jiang D, et al. Rehabilitation with brain-computer interface and upper limb motor function in ischemic stroke: A randomized controlled trial[J]. Med, 2024, 5(6): 559-569.
24.	Liu X, Zhang W, Li W, et al. Effects of motor imagery based brain-computer interface on upper limb function and attention in stroke patients with hemiplegia: a randomized controlled trial[J/OL]. BMC Neurol, 2023, 23(1): 136. doi: 10.1186/s12883-023-03150-5.
25.	Liu M, Ushiba J. Brain-machine interface (BMI)-based neurorehabilitation for post-stroke upper limb paralysis[J]. Keio J Med, 2022, 71(4): 82-92.
26.	Wu B. A brain-computer-interface driven forearm exoskeleton with adaptive neuroregulation-based feedback for stroke rehabilitation[J]. Alexandria Engineering Journal, 2025, 131: 199-208.
27.	Zhang Y, Gao Y, Zhou J, et al. Advances in brain-computer interface controlled functional electrical stimulation for upper limb recovery after stroke[J/OL]. Brain Res Bull, 2025, 226: 111354. doi: 10.1016/j.brainresbull.2025.111354.
28.	Zanette G, Manganotti P, Fiaschi A, et al. Modulation of motor cortex excitability after upper limb immobilization[J]. Clin Neurophysiol, 2004, 115(6): 1264-1275.
29.	Parker RS, Lewis GN, Rice DA, et al. Is motor cortical excitability altered in people with chronic pain? A systematic review and meta-analysis[J]. Brain Stimul, 2016, 9(4): 488-500.
30.	Kuner R, Flor H. Structural plasticity and reorganisation in chronic pain[J/OL]. Nat Rev Neurosci, 2017, 18(2): 113. doi: 10.1038/nrn.2017.5.
31.	Langer N, H?nggi J, Müller NA, et al. Effects of limb immobilization on brain plasticity[J]. Neurology, 2012, 78(3): 182-188.
32.	Schabrun SM, Hodges PW. Muscle pain differentially modulates short interval intracortical inhibition and intracortical facilitation in primary motor cortex[J]. J Pain, 2012, 13(2): 187-194.
33.	Liepert J, Tegenthoff M, Malin JP. Changes of cortical motor area size during immobilization[J]. Electroencephalogr Clin Neurophysiol, 1995, 97(6): 382-386.
34.	Levett JJ, Elkaim LM, Niazi F, et al. Invasive brain computer interface for motor restoration in spinal cord injury: A systematic review[J]. Neuromodulation, 2024, 27(4): 597-603.
35.	Chen J, Xia Y, Zhou X, et al. fNIRS-EEG BCIs for motor rehabilitation: A review[J/OL]. Bioengineering (Basel), 2023, 10(12): 1393. doi: 10.3390/bioengineering10121393.
36.	AlQahtani NJ, Al-Naib I, Althobaiti M. Recent progress on smart lower prosthetic limbs: a comprehensive review on using EEG and fNIRS devices in rehabilitation[J/OL]. Front Bioeng Biotechnol, 2024, 12: 1454262. doi: 10.3389/fbioe.2024.1454262.
37.	de Seta V, Romeni S. Multimodal closed-loop strategies for gait recovery after spinal cord injury and stroke via the integration of robotics and neuromodulation [J/OL]. Front Neurosci, 2025, 19: 1569148. doi: 10.3389/fnins.2025.1569148.
38.	Williams C, Anik FI, Hasan MM, et al. Advancing brain-computer interface closed-loop systems for neurorehabilitation: Systematic review of AI and machine learning innovations in biomedical engineering[J/OL]. JMIR Biomed Eng, 2025, 10: e72218. doi: 10.2196/72218.

1. Zarzycki R, Morton SM, Charalambous CC, et al. Corticospinal and intracortical excitability differ between athletes early after ACLR and matched controls[J]. J Orthop Res, 2018, 36(11): 2941-2948.
2. Sherman DA, Beausejour JP, Koohestani M, et al. Quadriceps motor unit properties following ACL reconstruction are associated with corticospinal excitability and motor cortex activations[J]. J Appl Physiol (1985), 2025, 138(4): 1011-1023.
3. Sherman DA, Rush J, Stock MS, et al. Neural drive and motor unit characteristics after anterior cruciate ligament reconstruction: implications for quadriceps weakness[J/OL]. PeerJ, 2023, 11: e16261. doi: 10.7717/peerj.16261.
4. Héroux ME, Tremblay F. Corticomotor excitability associated with unilateral knee dysfunction secondary to anterior cruciate ligament injury[J]. Knee Surg Sports Traumatol Arthrosc, 2006, 14(9): 823-833.
5. Grooms DR, Page SJ, Nichols-Larsen DS, et al. Neuroplasticity associated with anterior cruciate ligament reconstruction[J]. J Orthop Sports Phys Ther, 2017, 47(3): 180-189.
6. Patel HH, Berlinberg EJ, Nwachukwu B, et al. Quadriceps weakness is associated with neuroplastic changes within specific corticospinal pathways and brain areas after anterior cruciate ligament reconstruction: Theoretical utility of motor imagery-based brain-computer interface technology for rehabilitation[J/OL]. Arthrosc Sports Med Rehabil, 2022, 5(1): e207-e216.
7. Kapreli E, Athanasopoulos S. The anterior cruciate ligament deficiency as a model of brain plasticity[J]. Med Hypotheses, 2006, 67(3): 645-650.
8. Needle AR, Lepley AS, Grooms DR. Central nervous system adaptation after ligamentous injury: a summary of theories, evidence, and clinical interpretation[J]. Sports Med, 2017, 47(7): 1271-1288.
9. Neige C, Ciechelski V, Lebon F. The recruitment of indirect waves within primary motor cortex during motor imagery: A directional transcranial magnetic stimulation study[J]. Eur J Neurosci, 2022, 56(12): 6187-6200.
10. Sengupta P, Lakshminarayanan K. Motor imagery of finger movements: Effects on cortical and muscle activities[J/OL]. Behav Brain Res, 2024, 471: 115100. doi: 10.1016/j.bbr.2024.115100.
11. Chung E, Park SI, Jang YY, et al. Effects of brain-computer interface-based functional electrical stimulation on balance and gait function in patients with stroke: preliminary results[J]. J Phys Ther Sci, 2015, 27(2): 513-516.
12. Mrachacz-Kersting N, Jiang N, Stevenson AJ, et al. Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface[J]. J Neurophysiol, 2016, 115(3): 1410-1421.
13. Chung E, Lee BH, Hwang S. Therapeutic effects of brain-computer interface-controlled functional electrical stimulation training on balance and gait performance for stroke: A pilot randomized controlled trial[J/OL]. Medicine (Baltimore), 2020, 99(51): e22612. doi: 10.1097/MD.0000000000022612.
14. Stefan K, Kunesch E, Benecke R, et al. Mechanisms of enhancement of human motor cortex excitability induced by interventional paired associative stimulation[J]. J Physiol, 2002, 543(Pt 2): 699-708.
15. Lebon F, Guillot A, Collet C. Increased muscle activation following motor imagery during the rehabilitation of the anterior cruciate ligament[J]. Appl Psychophysiol Biofeedback, 2012, 37(1): 45-51.
16. Paravlic AH, Maffulli N, Kova? S, et al. Home-based motor imagery intervention improves functional performance following total knee arthroplasty in the short term: a randomized controlled trial[J/OL]. J Orthop Surg Res, 2020, 15(1): 451. doi: 10.1186/s13018-020-01964-4.
17. Li R, Du J, Yang K, et al. Effectiveness of motor imagery for improving functional performance after total knee arthroplasty: a systematic review with meta-analysis[J/OL]. J Orthop Surg Res, 2022, 17(1): 65. doi: 10.1186/s13018-022-02946-4.
18. Yu F, Rao Z, Chen N, et al. ArmBCIsys: Robot arm BCI system with time-frequency network for multiobject grasping[J]. IEEE Trans Neural Netw Learn Syst, 2025, 36(10): 18327-18341.
19. Romeni S, Losanno E, Emedoli D, et al. High-frequency epidural electrical stimulation reduces spasticity and facilitates walking recovery in patients with spinal cord injury[J/OL]. Sci Transl Med, 2025, 17(780): eadp9607. doi: 10.1126/scitranslmed.adp9607.
20. Chhabra HS, Kalidindi KKV, Garg N, et al. Spinal epidural electrical stimulation for the recovery of motor function in lower limbs after spinal cord injury: A pilot study[J]. J Spinal Cord Med, 2026, 49(4): 692-703.
21. 劉文慧, 孫文婷, 胡耐翀, 等. 神經電刺激調控技術在脊髓損傷后康復治療中的應用及效應機制[J]. 康復學報, 2024, 34(6): 633-640.
22. Liao W, Li J, Zhang X, et al. Motor imagery brain-computer interface rehabilitation system enhances upper limb performance and improves brain activity in stroke patients: A clinical study[J/OL]. Front Hum Neurosci, 2023, 17: 1117670. doi: 10.3389/fnhum.2023.1117670.
23. Wang A, Tian X, Jiang D, et al. Rehabilitation with brain-computer interface and upper limb motor function in ischemic stroke: A randomized controlled trial[J]. Med, 2024, 5(6): 559-569.
24. Liu X, Zhang W, Li W, et al. Effects of motor imagery based brain-computer interface on upper limb function and attention in stroke patients with hemiplegia: a randomized controlled trial[J/OL]. BMC Neurol, 2023, 23(1): 136. doi: 10.1186/s12883-023-03150-5.
25. Liu M, Ushiba J. Brain-machine interface (BMI)-based neurorehabilitation for post-stroke upper limb paralysis[J]. Keio J Med, 2022, 71(4): 82-92.
26. Wu B. A brain-computer-interface driven forearm exoskeleton with adaptive neuroregulation-based feedback for stroke rehabilitation[J]. Alexandria Engineering Journal, 2025, 131: 199-208.
27. Zhang Y, Gao Y, Zhou J, et al. Advances in brain-computer interface controlled functional electrical stimulation for upper limb recovery after stroke[J/OL]. Brain Res Bull, 2025, 226: 111354. doi: 10.1016/j.brainresbull.2025.111354.
28. Zanette G, Manganotti P, Fiaschi A, et al. Modulation of motor cortex excitability after upper limb immobilization[J]. Clin Neurophysiol, 2004, 115(6): 1264-1275.
29. Parker RS, Lewis GN, Rice DA, et al. Is motor cortical excitability altered in people with chronic pain? A systematic review and meta-analysis[J]. Brain Stimul, 2016, 9(4): 488-500.
30. Kuner R, Flor H. Structural plasticity and reorganisation in chronic pain[J/OL]. Nat Rev Neurosci, 2017, 18(2): 113. doi: 10.1038/nrn.2017.5.
31. Langer N, H?nggi J, Müller NA, et al. Effects of limb immobilization on brain plasticity[J]. Neurology, 2012, 78(3): 182-188.
32. Schabrun SM, Hodges PW. Muscle pain differentially modulates short interval intracortical inhibition and intracortical facilitation in primary motor cortex[J]. J Pain, 2012, 13(2): 187-194.
33. Liepert J, Tegenthoff M, Malin JP. Changes of cortical motor area size during immobilization[J]. Electroencephalogr Clin Neurophysiol, 1995, 97(6): 382-386.
34. Levett JJ, Elkaim LM, Niazi F, et al. Invasive brain computer interface for motor restoration in spinal cord injury: A systematic review[J]. Neuromodulation, 2024, 27(4): 597-603.
35. Chen J, Xia Y, Zhou X, et al. fNIRS-EEG BCIs for motor rehabilitation: A review[J/OL]. Bioengineering (Basel), 2023, 10(12): 1393. doi: 10.3390/bioengineering10121393.
36. AlQahtani NJ, Al-Naib I, Althobaiti M. Recent progress on smart lower prosthetic limbs: a comprehensive review on using EEG and fNIRS devices in rehabilitation[J/OL]. Front Bioeng Biotechnol, 2024, 12: 1454262. doi: 10.3389/fbioe.2024.1454262.
37. de Seta V, Romeni S. Multimodal closed-loop strategies for gait recovery after spinal cord injury and stroke via the integration of robotics and neuromodulation [J/OL]. Front Neurosci, 2025, 19: 1569148. doi: 10.3389/fnins.2025.1569148.
38. Williams C, Anik FI, Hasan MM, et al. Advancing brain-computer interface closed-loop systems for neurorehabilitation: Systematic review of AI and machine learning innovations in biomedical engineering[J/OL]. JMIR Biomed Eng, 2025, 10: e72218. doi: 10.2196/72218.

Chinese Journal of Reparative and Reconstructive Surgery

Emerging role of brain-computer interface in orthopedic rehabilitation and motor function restoration

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content