A review of functional electrical stimulation based on brain-computer interface_Journal of Biomedical Engineering

Authors：

WANG Yao ¹ , LI Yuhan ¹ , CUI Hongyan ² , LI Meng ² ,  CHEN Xiaogang ²

1. School of Life Sciences, Tianjin Polytechnic University, Tianjin 300387, P. R. China;
2. Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300192, P. R. China;

Corresponding author：

CHEN Xiaogang, Email: chenxg@bme.cams.cn

Keywords：

Brain-computer interface; Functional electrical stimulation; Electroencephalogram; Neurorehabilitation

DOI：

10.7507/1001-5515.202311036

Video：

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Individuals with motor dysfunction caused by damage to the central nervous system are unable to transmit voluntary movement commands to their muscles, resulting in a reduced ability to control their limbs. However, traditional rehabilitation methods have problems such as long treatment cycles and high labor costs. Functional electrical stimulation (FES) based on brain-computer interface (BCI) connects the patient’s intentions with muscle contraction, and helps to promote the reconstruction of nerve function by recognizing nerve signals and stimulating the moving muscle group with electrical impulses to produce muscle convulsions or limb movements. It is an effective treatment for sequelae of neurological diseases such as stroke and spinal cord injury. This article reviewed the current research status of BCI-based FES from three aspects: BCI paradigms, FES parameters and rehabilitation efficacy, and looked forward to the future development trend of this technology, in order to improve the understanding of BCI-based FES.

Citation： WANG Yao, LI Yuhan, CUI Hongyan, LI Meng, CHEN Xiaogang. A review of functional electrical stimulation based on brain-computer interface. Journal of Biomedical Engineering, 2024, 41(4): 650-655. doi: 10.7507/1001-5515.202311036 Copy

1.	Deng W, Yang M, Shu X, et al. Respiratory training combined with core training improves lower limb function in patients with ischemic stroke. Am J Transl Res, 2023, 15(3): 1880-1888.
2.	丁原全, 唐迪, 丁愉, 等. 针灸在中风后手功能障碍康复中的临床治疗进展. 中国疗养医学, 2023, 32(7): 691-694.
3.	宋美璇, 赵春艳, 李刚, 等. 脑卒中后运动功能恢复预测模型的研究进展. 上海护理, 2023, 23(12): 60-64.
4.	李秀丽, 冀京雷, 杜晓敏, 等. 镜像疗法联合功能性电刺激治疗脑卒中患者上肢运动功能障碍临床研究. 康复学报, 2023, 33(4): 353-358.
5.	苏栋楠. 基于EEG的精准手部中风电刺激功能康复仪研究. 洛阳: 河南科技大学, 2022.
6.	Zhang S, Chen Y, Zhang L, et al. Study on robot grasping system of SSVEP-BCI based on augmented reality stimulus. Tsinghua Sci Technol, 2022, 28(2): 322-329.
7.	Nojima I, Sugata H, Takeuchi H, et al. Brain–computer interface training based on brain activity can induce motor recovery in patients with stroke: A meta-analysis. Neurorehabil Neural Repair, 2022, 36(2): 83-96.
8.	Bhattacharyya S, Clerc M, Hayashibe M. Augmenting motor imagery learning for brain–computer interfacing using electrical stimulation as feedback. IEEE Trans Med Robot Bionics, 2019, 1(4): 247-255.
9.	Ren S, Wang W, Hou Z-G, et al. Enhanced motor imagery based brain-computer interface via FES and VR for lower limbs. IEEE Trans Neural Syst Rehabil Eng, 2020, 28(8): 1846-1855.
10.	Sousa A S, Moreira J, Silva C, et al. Usability of functional electrical stimulation in upper limb rehabilitation in post-stroke patients: a narrative review. Sensors (Basel), 2022, 22(4): 1409.
11.	Ni L, Yao Z, Zhao Y, et al. Electrical stimulation therapy for peripheral nerve injury. Front Neurol, 2023, 14: 1081458.
12.	郑应康, 王东岩, 刘洋, 等. 功能性电刺激在脑卒中后上肢康复中的应用及研究进展. 中国康复医学杂志, 2022, 37(8): 1121-1125.
13.	Tai P, Ding P, Wang F, et al. Brain-computer interface paradigms and neural coding. Front Neurosci, 2024, 17: 1345961.
14.	Yao L, Zhang D, Huang G, et al. Using SSVEP based brain-computer interface to control functional electrical stimulation training system// 2011 IEEE 5th International Conference on Cybernetics and Intelligent Systems (CIS). Qingdao: IEEE, 2011: 323-328.
15.	Son J E, Choi H, Lim H, et al. Development of a flickering action video based steady state visual evoked potential triggered brain computer interface-functional electrical stimulation for a rehabilitative action observation game. Technol Health Care, 2020, 28(S1): 509-519.
16.	Choi I, Bond K, Nam C S. A hybrid BCI-controlled FES system for hand-wrist motor function// 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Budapest: IEEE, 2016: 002324-002328.
17.	Wang Z, Cao C, Chen L, et al. Multimodal neural response and effect assessment during a BCI-based neurofeedback training after stroke. Front Neurosci, 2022, 16: 884420.
18.	Jadavji Z, Kirton A, Metzler M J, et al. BCI-activated electrical stimulation in children with perinatal stroke and hemiparesis: A pilot study. Front Hum Neurosci, 2023, 17: 1006242.
19.	Zhou L, Zhu Q, Wu B, et al. A comparison of directed functional connectivity among fist-related brain activities during movement imagery, movement execution, and movement observation. Brain Res, 2022, 1777: 147769.
20.	Peng Y, Wong C M, Wang Z, et al. Fatigue detection in SSVEP-BCIs based on wavelet entropy of EEG. IEEE Access, 2021, 9: 114905-114913.
21.	Orban M, Elsamanty M, Guo K, et al. A review of brain activity and EEG-based brain–computer interfaces for rehabilitation application. Bioengineering (Basel), 2022, 9(12): 768.
22.	Zulauf-Czaja A, Al-Taleb M K, Purcell M, et al. On the way home: a BCI-FES hand therapy self-managed by sub-acute SCI participants and their caregivers: a usability study. J Neuroeng Rehabil, 2021, 18(1): 44.
23.	Remsik A B, van Kan P L, Gloe S, et al. BCI-FES with multimodal feedback for motor recovery poststroke. Front Hum Neurosci, 2022, 16: 725715.
24.	Milosevic M, Nakanishi T, Sasaki A, et al. Cortical re-organization after traumatic brain injury elicited using functional electrical stimulation therapy: A case report. Front Neurosci, 2021, 15: 693861.
25.	Sartori L G, de Souza R B, Campos D P, et al. Ineffective voluntary motor improvement through non-invasive BCI-FES with static magnetic field in complete spinal cord injury: A pilot study. Global Transl Med, 2024, 3(1): 2285.
26.	李欣然, 李瑞青. 神经肌肉电刺激在脑卒中后运动障碍中的研究进展. 中山大学学报(医学科学版), 2024, 45(2): 180-189.
27.	杨琪, 蔡云朗. 电刺激技术及其临床应用的研究进展. 东南大学学报(医学版), 2023, 42(5): 794-799.
28.	Blazevich A J, Collins D F, Millet G Y, et al. Enhancing adaptations to neuromuscular electrical stimulation training interventions. Exerc Sport Sci Rev, 2021, 49(4): 244-252.
29.	苏栋楠, 尚鹏, 胡志刚, 等. 可穿戴上肢功能性电刺激仪的设计与实验. 电子技术应用, 2022, 48(6): 92-97.
30.	Carson R G, Buick A R. Neuromuscular electrical stimulation-promoted plasticity of the human brain. J Physiol, 2021, 599(9): 2375-2399.
31.	Cantillo-Negrete J, Carino-Escobar R I, Leyva-Martinez I, et al. Upper limb recovery in cervical spinal cord injury after a brain-computer interface controlled functional electrical stimulation intervention. J Med Biol Eng, 2023, 43(5): 522-531.
32.	Chen S, Fu J, Ji Y, et al. A 4-year follow-up of brain-computer interface on upper limb motor recovery of aging post-stroke patients. Arch Phys Med Rehabil, 2024, 105(4): e32-e33.
33.	Lo Y T, Lim M J R, Kok C Y, et al. Neural interface-based motor neuroprosthesis in post-stroke upper limb neurorehabilitation: An individual patient data meta-analysis. Arch Phys Med Rehabil, 2024: S0003-9993(24) 00910-9.
34.	Mane R, Wu Z, Wang D. Poststroke motor, cognitive and speech rehabilitation with brain–computer interface: a perspective review. Stroke Vasc Neurol, 2022, 7(6): 541-579.
35.	Biasiucci A, Leeb R, Iturrate I, et al. Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke. Nat Commun, 2018, 9(1): 2421.
36.	Kumari R, Dybus A, Purcell M, et al. Motor priming to enhance the effect of physical therapy in people with spinal cord injury. J Spinal Cord Med, 2024: 1-15.
37.	Jovanovic L I, Kapadia N, Lo L, et al. Restoration of upper limb function after chronic severe hemiplegia: a case report on the feasibility of a brain-computer interface-triggered functional electrical stimulation therapy. Am J Phys Med Rehabil, 2020, 99(3): e35-e40.
38.	Lee S-H, Kim S S, Lee B-H. Action observation training and brain-computer interface controlled functional electrical stimulation enhance upper extremity performance and cortical activation in patients with stroke: a randomized controlled trial. Physiother Theory Pract, 2022, 38(9): 1126-1134.
39.	Chung E, Lee B-H, 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. Medicine (Baltimore), 2020, 99(51): e22612.
40.	Zhang R, Wang C, He S, et al. An adaptive brain-computer interface to enhance motor recovery after stroke. IEEE Trans Neural Syst Rehabil Eng, 2023, 31: 2268-2278.

1. Deng W, Yang M, Shu X, et al. Respiratory training combined with core training improves lower limb function in patients with ischemic stroke. Am J Transl Res, 2023, 15(3): 1880-1888.
2. 丁原全, 唐迪, 丁愉, 等. 针灸在中风后手功能障碍康复中的临床治疗进展. 中国疗养医学, 2023, 32(7): 691-694.
3. 宋美璇, 赵春艳, 李刚, 等. 脑卒中后运动功能恢复预测模型的研究进展. 上海护理, 2023, 23(12): 60-64.
4. 李秀丽, 冀京雷, 杜晓敏, 等. 镜像疗法联合功能性电刺激治疗脑卒中患者上肢运动功能障碍临床研究. 康复学报, 2023, 33(4): 353-358.
5. 苏栋楠. 基于EEG的精准手部中风电刺激功能康复仪研究. 洛阳: 河南科技大学, 2022.
6. Zhang S, Chen Y, Zhang L, et al. Study on robot grasping system of SSVEP-BCI based on augmented reality stimulus. Tsinghua Sci Technol, 2022, 28(2): 322-329.
7. Nojima I, Sugata H, Takeuchi H, et al. Brain–computer interface training based on brain activity can induce motor recovery in patients with stroke: A meta-analysis. Neurorehabil Neural Repair, 2022, 36(2): 83-96.
8. Bhattacharyya S, Clerc M, Hayashibe M. Augmenting motor imagery learning for brain–computer interfacing using electrical stimulation as feedback. IEEE Trans Med Robot Bionics, 2019, 1(4): 247-255.
9. Ren S, Wang W, Hou Z-G, et al. Enhanced motor imagery based brain-computer interface via FES and VR for lower limbs. IEEE Trans Neural Syst Rehabil Eng, 2020, 28(8): 1846-1855.
10. Sousa A S, Moreira J, Silva C, et al. Usability of functional electrical stimulation in upper limb rehabilitation in post-stroke patients: a narrative review. Sensors (Basel), 2022, 22(4): 1409.
11. Ni L, Yao Z, Zhao Y, et al. Electrical stimulation therapy for peripheral nerve injury. Front Neurol, 2023, 14: 1081458.
12. 郑应康, 王东岩, 刘洋, 等. 功能性电刺激在脑卒中后上肢康复中的应用及研究进展. 中国康复医学杂志, 2022, 37(8): 1121-1125.
13. Tai P, Ding P, Wang F, et al. Brain-computer interface paradigms and neural coding. Front Neurosci, 2024, 17: 1345961.
14. Yao L, Zhang D, Huang G, et al. Using SSVEP based brain-computer interface to control functional electrical stimulation training system// 2011 IEEE 5th International Conference on Cybernetics and Intelligent Systems (CIS). Qingdao: IEEE, 2011: 323-328.
15. Son J E, Choi H, Lim H, et al. Development of a flickering action video based steady state visual evoked potential triggered brain computer interface-functional electrical stimulation for a rehabilitative action observation game. Technol Health Care, 2020, 28(S1): 509-519.
16. Choi I, Bond K, Nam C S. A hybrid BCI-controlled FES system for hand-wrist motor function// 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Budapest: IEEE, 2016: 002324-002328.
17. Wang Z, Cao C, Chen L, et al. Multimodal neural response and effect assessment during a BCI-based neurofeedback training after stroke. Front Neurosci, 2022, 16: 884420.
18. Jadavji Z, Kirton A, Metzler M J, et al. BCI-activated electrical stimulation in children with perinatal stroke and hemiparesis: A pilot study. Front Hum Neurosci, 2023, 17: 1006242.
19. Zhou L, Zhu Q, Wu B, et al. A comparison of directed functional connectivity among fist-related brain activities during movement imagery, movement execution, and movement observation. Brain Res, 2022, 1777: 147769.
20. Peng Y, Wong C M, Wang Z, et al. Fatigue detection in SSVEP-BCIs based on wavelet entropy of EEG. IEEE Access, 2021, 9: 114905-114913.
21. Orban M, Elsamanty M, Guo K, et al. A review of brain activity and EEG-based brain–computer interfaces for rehabilitation application. Bioengineering (Basel), 2022, 9(12): 768.
22. Zulauf-Czaja A, Al-Taleb M K, Purcell M, et al. On the way home: a BCI-FES hand therapy self-managed by sub-acute SCI participants and their caregivers: a usability study. J Neuroeng Rehabil, 2021, 18(1): 44.
23. Remsik A B, van Kan P L, Gloe S, et al. BCI-FES with multimodal feedback for motor recovery poststroke. Front Hum Neurosci, 2022, 16: 725715.
24. Milosevic M, Nakanishi T, Sasaki A, et al. Cortical re-organization after traumatic brain injury elicited using functional electrical stimulation therapy: A case report. Front Neurosci, 2021, 15: 693861.
25. Sartori L G, de Souza R B, Campos D P, et al. Ineffective voluntary motor improvement through non-invasive BCI-FES with static magnetic field in complete spinal cord injury: A pilot study. Global Transl Med, 2024, 3(1): 2285.
26. 李欣然, 李瑞青. 神经肌肉电刺激在脑卒中后运动障碍中的研究进展. 中山大学学报(医学科学版), 2024, 45(2): 180-189.
27. 杨琪, 蔡云朗. 电刺激技术及其临床应用的研究进展. 东南大学学报(医学版), 2023, 42(5): 794-799.
28. Blazevich A J, Collins D F, Millet G Y, et al. Enhancing adaptations to neuromuscular electrical stimulation training interventions. Exerc Sport Sci Rev, 2021, 49(4): 244-252.
29. 苏栋楠, 尚鹏, 胡志刚, 等. 可穿戴上肢功能性电刺激仪的设计与实验. 电子技术应用, 2022, 48(6): 92-97.
30. Carson R G, Buick A R. Neuromuscular electrical stimulation-promoted plasticity of the human brain. J Physiol, 2021, 599(9): 2375-2399.
31. Cantillo-Negrete J, Carino-Escobar R I, Leyva-Martinez I, et al. Upper limb recovery in cervical spinal cord injury after a brain-computer interface controlled functional electrical stimulation intervention. J Med Biol Eng, 2023, 43(5): 522-531.
32. Chen S, Fu J, Ji Y, et al. A 4-year follow-up of brain-computer interface on upper limb motor recovery of aging post-stroke patients. Arch Phys Med Rehabil, 2024, 105(4): e32-e33.
33. Lo Y T, Lim M J R, Kok C Y, et al. Neural interface-based motor neuroprosthesis in post-stroke upper limb neurorehabilitation: An individual patient data meta-analysis. Arch Phys Med Rehabil, 2024: S0003-9993(24) 00910-9.
34. Mane R, Wu Z, Wang D. Poststroke motor, cognitive and speech rehabilitation with brain–computer interface: a perspective review. Stroke Vasc Neurol, 2022, 7(6): 541-579.
35. Biasiucci A, Leeb R, Iturrate I, et al. Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke. Nat Commun, 2018, 9(1): 2421.
36. Kumari R, Dybus A, Purcell M, et al. Motor priming to enhance the effect of physical therapy in people with spinal cord injury. J Spinal Cord Med, 2024: 1-15.
37. Jovanovic L I, Kapadia N, Lo L, et al. Restoration of upper limb function after chronic severe hemiplegia: a case report on the feasibility of a brain-computer interface-triggered functional electrical stimulation therapy. Am J Phys Med Rehabil, 2020, 99(3): e35-e40.
38. Lee S-H, Kim S S, Lee B-H. Action observation training and brain-computer interface controlled functional electrical stimulation enhance upper extremity performance and cortical activation in patients with stroke: a randomized controlled trial. Physiother Theory Pract, 2022, 38(9): 1126-1134.
39. Chung E, Lee B-H, 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. Medicine (Baltimore), 2020, 99(51): e22612.
40. Zhang R, Wang C, He S, et al. An adaptive brain-computer interface to enhance motor recovery after stroke. IEEE Trans Neural Syst Rehabil Eng, 2023, 31: 2268-2278.

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A review of functional electrical stimulation based on brain-computer interface

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