Applications and prospects of electroencephalography technology in neurorehabilitation assessment and treatment_Journal of Biomedical Engineering

Authors：

HE Weizhong ¹ , WANG Dengyu ² , MENG Qiangfan ¹ , HE Feng ^1,3 ,  XU Minpeng ^1,3 , MING Dong ^1,3

1. Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, P. R. China;
2. School of Medicine, Tsinghua University, Beijing 100084, P. R. China;
3. Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin 300072, P. R. China;

Corresponding author：

Keywords：

Electroencephalography; Neurorehabilitation; Multimodal Integration; Assessment; Treatment

DOI：

10.7507/1001-5515.202404046

Video：

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Abstract Full text Figures/Tables Video References Cited by

With the high incidence of neurological diseases such as stroke and mental illness, rehabilitation treatments for neurological disorders have received widespread attention. Electroencephalography (EEG) technology, despite its excellent temporal resolution, has historically been limited in application due to its insufficient spatial resolution, and is mainly confined to preoperative assessment, intraoperative monitoring, and epilepsy detection. However, traditional constraints of EEG technology are being overcome with the popularization of EEG technology with high-density over 64-lead, the application of innovative analysis techniques and the integration of multimodal techniques, which are significantly broadening its applications in clinical settings. These advancements have not only reinforced the irreplaceable role of EEG technology in neurorehabilitation assessment, but also expanded its therapeutic potential through its combined use with technologies such as transcranial magnetic stimulation, transcranial electrical stimulation and brain-computer interfaces. This article reviewed the applications, advancements, and future prospects of EEG technology in neurorehabilitation assessment and treatment. Advancements in technology and interdisciplinary collaboration are expected to drive new applications and innovations in EEG technology within the neurorehabilitation field, providing patients with more precise and personalized rehabilitation strategies.

Citation： HE Weizhong, WANG Dengyu, MENG Qiangfan, HE Feng, XU Minpeng, MING Dong. Applications and prospects of electroencephalography technology in neurorehabilitation assessment and treatment. Journal of Biomedical Engineering, 2024, 41(6): 1271-1278, 1285. doi: 10.7507/1001-5515.202404046 Copy

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3.	Rossi Sebastiano D, Varotto G, Sattin D, et al. EEG assessment in patients with disorders of consciousness: aims, advantages, limits, and pitfalls. Front Neurol, 2021, 12: 649849..
4.	Seeber M, Cantonas L M, Hoevels M, et al. Subcortical electrophysiological activity is detectable with high-density EEG source imaging. Nat Commun, 2019, 10: 753..
5.	Coquelet N, De Tiège X, Destoky F, et al. Comparing MEG and high-density EEG for intrinsic functional connectivity mapping. Neuroimage, 2020, 210: 116556..
6.	Värbu K, Muhammad N, Muhammad Y. Past, present, and future of EEG-based BCI applications. Sensors, 2022, 22(9): 3331..
7.	Warbrick T. Simultaneous EEG-fMRI: What have we learned and what does the future hold?. Sensors, 2022, 22(6): 2262..
8.	Fernandez L, Biabani M, Do M, et al. Assessing cerebellar-cortical connectivity using concurrent TMS-EEG: a feasibility study. J Neurophysiol, 2021, 125(5): 1768-1787..
9.	Banoub M, Tetzlaff J E, Schubert A. Pharmacologic and physiologic influences affecting sensory evoked potentials: implications for perioperative monitoring. Anesthesiology, 2003, 99(3): 716-737..
10.	Roche D, Mahon P. Depth of anesthesia monitoring. Anesthesiol Clin, 2021, 39(3): 477-492..
11.	Wutzl B, Golaszewski S M, Leibnitz K, et al. Narrative review: quantitative EEG in disorders of consciousness. Brain Sci, 2021, 11(6): 697..
12.	Dehaene S, Changeux J P. Experimental and theoretical approaches to conscious processing. Neuron, 2011, 70(2): 200-227..
13.	Faugeras F, Rohaut B, Weiss N, et al. Event related potentials elicited by violations of auditory regularities in patients with impaired consciousness. Neuropsychologia, 2012, 50(3): 403-418..
14.	Bekinschtein T A, Dehaene S, Rohaut B, et al. Neural signature of the conscious processing of auditory regularities. Proc Natl Acad Sci U S A, 2009, 106(5): 1672-1677..
15.	Liu Y, Li Z, Bai Y. Frontal and parietal lobes play crucial roles in understanding the disorder of consciousness: a perspective from electroencephalogram studies. Front Neurosci, 2023, 16: 1024278..
16.	Gui P, Jiang Y, Zang D, et al. Assessing the depth of language processing in patients with disorders of consciousness. Nat Neurosci, 2020, 23(6): 761-770..
17.	Niso G, Tjepkema-Cloostermans M C, Lenders M W P M, et al. Modulation of the somatosensory evoked potential by attention and spinal cord stimulation. Front Neurol, 2021, 12: 694310..
18.	Massimini M, Ferrarelli F, Huber R, et al. Breakdown of cortical effective connectivity during sleep. Science, 2005, 309(5744): 2228-2232..
19.	Sarasso S, Rosanova M, Casali A G, et al. Quantifying cortical EEG responses to TMS in (un)consciousness. Clin EEG Neurosci, 2014, 45(1): 40-49..
20.	Casali A G, Gosseries O, Rosanova M, et al. A theoretically based index of consciousness independent of sensory processing and behavior. Sci Transl Med, 2013, 5(198): 198ra105..
21.	Kondziella D, Bender A, Diserens K, et al. European Academy of Neurology guideline on the diagnosis of coma and other disorders of consciousness. Eur J Neurol, 2020, 27(5): 741-756..
22.	Bareham C A, Roberts N, Allanson J, et al. Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness. Neuroimage: Clinical, 2020, 28: 102372..
23.	Birbaumer N, Ghanayim N, Hinterberger T, et al. A spelling device for the paralysed. Nature, 1999, 398: 297-298 ..
24.	Vansteensel M J, Pels E G M, Bleichner M G, et al. Fully implanted brain-computer interface in a locked-in patient with ALS. N Engl J Med, 2016, 375(21): 2060-2066..
25.	Fiani B, Reardon T, Ayres B, et al. An examination of prospective uses and future directions of neuralink: the brain-machine interface. Cureus, 2021, 13(3): e14192..
26.	Biasiucci A, Leeb R, Iturrate I, et al. Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke. Nat Commun, 2018, 9: 2421..
27.	Lorach H, Galvez A, Spagnolo V, et al. Walking naturally after spinal cord injury using a brain-spine interface. Nature, 2023, 618: 126-133..
28.	Zhang Z, Dai J. Fully implantable wireless brain-computer interface for humans: advancing toward the future. The Innovation, 2024, 5(3): 100595..
29.	Ming D, Yuan D, Li Y, et al. Neuroprosthesis system for lower limbs action based on functional electrical stimulation//2011 International Conference on Electrical and Control Engineering, Yichang, China: IEEE, 2011: 4583-4586..
30.	Iyer K K, Angwin A J, Van Hees S, et al. Alterations to dual stream connectivity predicts response to aphasia therapy following stroke. Cortex, 2020, 125: 30-43..
31.	Gennari G, Marti S, Palu M, et al. Orthogonal neural codes for speech in the infant brain. Proc Natl Acad Sci U S A, 2021, 118(31): e2020410118..
32.	Anumanchipalli G K, Chartier J, Chang E F. Speech synthesis from neural decoding of spoken sentences. Nature, 2019, 568: 493-498..
33.	杨文阳, 张文瑄. 基于脑电信号的注意力水平评价研究进展. 生物医学工程学杂志, 2023, 40(4): 820-828..
34.	刘毅, 李振阳, 危志伟, 等. 基于神经网络的阿尔茨海默病脑电诊断应用现状. 生物医学工程学杂志, 2022, 39(6): 1233-1239, 1246..
35.	Wang C M, Wang Z B, Xie B J, et al. Binaural processing deficit and cognitive impairment in alzheimer's disease. Alzheimers Dement, 2022, 18(6): 1085-1099..
36.	章浩伟, 许哲, 苑成梅, 等. 基于单通道脑电信号的自动睡眠分期模型研究. 生物医学工程学杂志, 2023, 40(3): 458-464, 473..
37.	Stephan A M, Lecci S, Cataldi J, et al. Conscious experiences and high-density EEG patterns predicting subjective sleep depth. Curr Biol, 2021, 31(24): 5487-5500..
38.	Ferrarelli F, Tononi G. The thalamic reticular nucleus and schizophrenia. Schizophr Bull, 2011, 37(2): 306-315..
39.	Hathaway E, Morgan K, Carson M, et al. Transcranial electrical stimulation targeting limbic cortex increases the duration of human deep sleep. Sleep Med, 2021, 81: 350-357..
40.	Schreiner T, Lehmann M, Rasch B. Auditory feedback blocks memory benefits of cueing during sleep. Nat Commun, 2015, 6: 8729..
41.	Choi J, Kwon M, Jun S C. A systematic review of closed-loop feedback techniques in sleep studies-related issues and future directions. Sensors, 2020, 20(10): 2770..
42.	McConnell B V, Kaplan R I, Teale P D, et al. Feasibility of home-based automated transcranial electrical stimulation during slow wave sleep. Brain Stimul, 2019, 12(3): 813-815..
43.	Shelley A M, Ward P B, Catts S V, et al. Mismatch negativity: an index of preattentive processing deficit in schizophrenia. Biol Psychiat, 1991, 30(10): 1059-1062..
44.	Boutros N N, Korzyukov O, Jansen B, et al. Sensory gating deficits during the mid latency phase of information processing in medicated schizophrenia patients. Psychiat Res, 2004, 126(3): 203-215..
45.	Ford J M, Mathalon D H, Kalba S, et al. N1 and P300 abnormalities in patients with schizophrenia, epilepsy, and epilepsy with schizophrenia-like features. Biol Psychiat, 2001, 49(10): 848-860..
46.	Alexopoulos G S, Murphy C F, Gunning-Dixon F M, et al. Event-related potentials in an emotional go/no-go task and remission of geriatric depression. Neuroreport, 2007, 18(3): 217-221..
47.	Gabard-Durnam L J, Wilkinson C, Kapur K, et al. Longitudinal EEG power in the first postnatal year differentiates autism outcomes. Nat Commun, 2019, 10: 4188..
48.	Wang E, Sun L, Sun M, et al. Attentional selection and suppression in children with attention-deficit/hyperactivity disorder. Biol Psychiatry Cogn Neurosci Neuroimaging, 2016, 1(4): 372-380..
49.	Zhao D, Zhang M, Tian W, et al. Neurophysiological correlate of incubation of craving in individuals with methamphetamine use disorder. Mol Psychiatry, 2021, 26(11): 6198-6208..
50.	Tian W, Zhao D, Ding J, et al. An electroencephalographic signature predicts craving for methamphetamine. Cell Rep Med, 2024, 5(1): 101347..
51.	Frey V N, Thomschewski A, Langthaler P B, et al. Connectivity analysis during rubber hand illusion-a pilot TMS-EEG study in a patient with SCI. Neural Plast, 2021, 2021: 6695530..
52.	Keser Z, Buchl S C, Seven N A, et al. Electroencephalogram (EEG) with or without transcranial magnetic stimulation (TMS) as biomarkers for post-stroke recovery: a narrative review. Front Neurol, 2022, 13: 827866..
53.	Parmigiani S, Mikulan E, Russo S, et al. Simultaneous stereo-EEG and high-density scalp EEG recordings to study the effects of intracerebral stimulation parameters. Brain Stimul, 2022, 15(3): 664-675..
54.	Schiff N D, Giacino J T, Butson C R, et al. Thalamic deep brain stimulation in traumatic brain injury: a phase 1, randomized feasibility study. Nat Med, 2023, 29(12): 3162-3174..
55.	Seas A, Noor M S, Choi K S, et al. Subcallosal cingulate deep brain stimulation evokes two distinct cortical responses via differential white matter activation. Proc Natl Acad Sci U S A, 2024, 121(14): e2314918121..
56.	Renda E, Karmali S A, Yordanova I, et al. Effect of transcranial direct current stimulation on an individual’s ability to learn to control a brain-computer interface. McGill Journal of Medicine, 2019, 17(1). DOI: 10.26443/mjm.v17i1.129..
57.	Metzger S L, Littlejohn K T, Silva A B, et al. A high-performance neuroprosthesis for speech decoding and avatar control. Nature, 2023, 620: 1037-1046..
58.	Liu Y, Zhao Z, Xu M, et al. Decoding and synthesizing tonal language speech from brain activity. Sci Adv, 2023, 9(23): eadh0478..
59.	Hassan M, Wendling F. Electroencephalography source connectivity: aiming for high resolution of brain networks in time and space. IEEE Signal Processing Magazine, 2018, 35(3): 81-96..

1. 陈意, 高强. 脑卒中运动功能障碍康复的研究进展. 华西医学, 2022, 37(5): 757-764..
2. Cohen M X. Where does EEG come from and what does it mean?. Trends Neurosci, 2017, 40(4): 208-218..
3. Rossi Sebastiano D, Varotto G, Sattin D, et al. EEG assessment in patients with disorders of consciousness: aims, advantages, limits, and pitfalls. Front Neurol, 2021, 12: 649849..
4. Seeber M, Cantonas L M, Hoevels M, et al. Subcortical electrophysiological activity is detectable with high-density EEG source imaging. Nat Commun, 2019, 10: 753..
5. Coquelet N, De Tiège X, Destoky F, et al. Comparing MEG and high-density EEG for intrinsic functional connectivity mapping. Neuroimage, 2020, 210: 116556..
6. Värbu K, Muhammad N, Muhammad Y. Past, present, and future of EEG-based BCI applications. Sensors, 2022, 22(9): 3331..
7. Warbrick T. Simultaneous EEG-fMRI: What have we learned and what does the future hold?. Sensors, 2022, 22(6): 2262..
8. Fernandez L, Biabani M, Do M, et al. Assessing cerebellar-cortical connectivity using concurrent TMS-EEG: a feasibility study. J Neurophysiol, 2021, 125(5): 1768-1787..
9. Banoub M, Tetzlaff J E, Schubert A. Pharmacologic and physiologic influences affecting sensory evoked potentials: implications for perioperative monitoring. Anesthesiology, 2003, 99(3): 716-737..
10. Roche D, Mahon P. Depth of anesthesia monitoring. Anesthesiol Clin, 2021, 39(3): 477-492..
11. Wutzl B, Golaszewski S M, Leibnitz K, et al. Narrative review: quantitative EEG in disorders of consciousness. Brain Sci, 2021, 11(6): 697..
12. Dehaene S, Changeux J P. Experimental and theoretical approaches to conscious processing. Neuron, 2011, 70(2): 200-227..
13. Faugeras F, Rohaut B, Weiss N, et al. Event related potentials elicited by violations of auditory regularities in patients with impaired consciousness. Neuropsychologia, 2012, 50(3): 403-418..
14. Bekinschtein T A, Dehaene S, Rohaut B, et al. Neural signature of the conscious processing of auditory regularities. Proc Natl Acad Sci U S A, 2009, 106(5): 1672-1677..
15. Liu Y, Li Z, Bai Y. Frontal and parietal lobes play crucial roles in understanding the disorder of consciousness: a perspective from electroencephalogram studies. Front Neurosci, 2023, 16: 1024278..
16. Gui P, Jiang Y, Zang D, et al. Assessing the depth of language processing in patients with disorders of consciousness. Nat Neurosci, 2020, 23(6): 761-770..
17. Niso G, Tjepkema-Cloostermans M C, Lenders M W P M, et al. Modulation of the somatosensory evoked potential by attention and spinal cord stimulation. Front Neurol, 2021, 12: 694310..
18. Massimini M, Ferrarelli F, Huber R, et al. Breakdown of cortical effective connectivity during sleep. Science, 2005, 309(5744): 2228-2232..
19. Sarasso S, Rosanova M, Casali A G, et al. Quantifying cortical EEG responses to TMS in (un)consciousness. Clin EEG Neurosci, 2014, 45(1): 40-49..
20. Casali A G, Gosseries O, Rosanova M, et al. A theoretically based index of consciousness independent of sensory processing and behavior. Sci Transl Med, 2013, 5(198): 198ra105..
21. Kondziella D, Bender A, Diserens K, et al. European Academy of Neurology guideline on the diagnosis of coma and other disorders of consciousness. Eur J Neurol, 2020, 27(5): 741-756..
22. Bareham C A, Roberts N, Allanson J, et al. Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness. Neuroimage: Clinical, 2020, 28: 102372..
23. Birbaumer N, Ghanayim N, Hinterberger T, et al. A spelling device for the paralysed. Nature, 1999, 398: 297-298 ..
24. Vansteensel M J, Pels E G M, Bleichner M G, et al. Fully implanted brain-computer interface in a locked-in patient with ALS. N Engl J Med, 2016, 375(21): 2060-2066..
25. Fiani B, Reardon T, Ayres B, et al. An examination of prospective uses and future directions of neuralink: the brain-machine interface. Cureus, 2021, 13(3): e14192..
26. Biasiucci A, Leeb R, Iturrate I, et al. Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke. Nat Commun, 2018, 9: 2421..
27. Lorach H, Galvez A, Spagnolo V, et al. Walking naturally after spinal cord injury using a brain-spine interface. Nature, 2023, 618: 126-133..
28. Zhang Z, Dai J. Fully implantable wireless brain-computer interface for humans: advancing toward the future. The Innovation, 2024, 5(3): 100595..
29. Ming D, Yuan D, Li Y, et al. Neuroprosthesis system for lower limbs action based on functional electrical stimulation//2011 International Conference on Electrical and Control Engineering, Yichang, China: IEEE, 2011: 4583-4586..
30. Iyer K K, Angwin A J, Van Hees S, et al. Alterations to dual stream connectivity predicts response to aphasia therapy following stroke. Cortex, 2020, 125: 30-43..
31. Gennari G, Marti S, Palu M, et al. Orthogonal neural codes for speech in the infant brain. Proc Natl Acad Sci U S A, 2021, 118(31): e2020410118..
32. Anumanchipalli G K, Chartier J, Chang E F. Speech synthesis from neural decoding of spoken sentences. Nature, 2019, 568: 493-498..
33. 杨文阳, 张文瑄. 基于脑电信号的注意力水平评价研究进展. 生物医学工程学杂志, 2023, 40(4): 820-828..
34. 刘毅, 李振阳, 危志伟, 等. 基于神经网络的阿尔茨海默病脑电诊断应用现状. 生物医学工程学杂志, 2022, 39(6): 1233-1239, 1246..
35. Wang C M, Wang Z B, Xie B J, et al. Binaural processing deficit and cognitive impairment in alzheimer's disease. Alzheimers Dement, 2022, 18(6): 1085-1099..
36. 章浩伟, 许哲, 苑成梅, 等. 基于单通道脑电信号的自动睡眠分期模型研究. 生物医学工程学杂志, 2023, 40(3): 458-464, 473..
37. Stephan A M, Lecci S, Cataldi J, et al. Conscious experiences and high-density EEG patterns predicting subjective sleep depth. Curr Biol, 2021, 31(24): 5487-5500..
38. Ferrarelli F, Tononi G. The thalamic reticular nucleus and schizophrenia. Schizophr Bull, 2011, 37(2): 306-315..
39. Hathaway E, Morgan K, Carson M, et al. Transcranial electrical stimulation targeting limbic cortex increases the duration of human deep sleep. Sleep Med, 2021, 81: 350-357..
40. Schreiner T, Lehmann M, Rasch B. Auditory feedback blocks memory benefits of cueing during sleep. Nat Commun, 2015, 6: 8729..
41. Choi J, Kwon M, Jun S C. A systematic review of closed-loop feedback techniques in sleep studies-related issues and future directions. Sensors, 2020, 20(10): 2770..
42. McConnell B V, Kaplan R I, Teale P D, et al. Feasibility of home-based automated transcranial electrical stimulation during slow wave sleep. Brain Stimul, 2019, 12(3): 813-815..
43. Shelley A M, Ward P B, Catts S V, et al. Mismatch negativity: an index of preattentive processing deficit in schizophrenia. Biol Psychiat, 1991, 30(10): 1059-1062..
44. Boutros N N, Korzyukov O, Jansen B, et al. Sensory gating deficits during the mid latency phase of information processing in medicated schizophrenia patients. Psychiat Res, 2004, 126(3): 203-215..
45. Ford J M, Mathalon D H, Kalba S, et al. N1 and P300 abnormalities in patients with schizophrenia, epilepsy, and epilepsy with schizophrenia-like features. Biol Psychiat, 2001, 49(10): 848-860..
46. Alexopoulos G S, Murphy C F, Gunning-Dixon F M, et al. Event-related potentials in an emotional go/no-go task and remission of geriatric depression. Neuroreport, 2007, 18(3): 217-221..
47. Gabard-Durnam L J, Wilkinson C, Kapur K, et al. Longitudinal EEG power in the first postnatal year differentiates autism outcomes. Nat Commun, 2019, 10: 4188..
48. Wang E, Sun L, Sun M, et al. Attentional selection and suppression in children with attention-deficit/hyperactivity disorder. Biol Psychiatry Cogn Neurosci Neuroimaging, 2016, 1(4): 372-380..
49. Zhao D, Zhang M, Tian W, et al. Neurophysiological correlate of incubation of craving in individuals with methamphetamine use disorder. Mol Psychiatry, 2021, 26(11): 6198-6208..
50. Tian W, Zhao D, Ding J, et al. An electroencephalographic signature predicts craving for methamphetamine. Cell Rep Med, 2024, 5(1): 101347..
51. Frey V N, Thomschewski A, Langthaler P B, et al. Connectivity analysis during rubber hand illusion-a pilot TMS-EEG study in a patient with SCI. Neural Plast, 2021, 2021: 6695530..
52. Keser Z, Buchl S C, Seven N A, et al. Electroencephalogram (EEG) with or without transcranial magnetic stimulation (TMS) as biomarkers for post-stroke recovery: a narrative review. Front Neurol, 2022, 13: 827866..
53. Parmigiani S, Mikulan E, Russo S, et al. Simultaneous stereo-EEG and high-density scalp EEG recordings to study the effects of intracerebral stimulation parameters. Brain Stimul, 2022, 15(3): 664-675..
54. Schiff N D, Giacino J T, Butson C R, et al. Thalamic deep brain stimulation in traumatic brain injury: a phase 1, randomized feasibility study. Nat Med, 2023, 29(12): 3162-3174..
55. Seas A, Noor M S, Choi K S, et al. Subcallosal cingulate deep brain stimulation evokes two distinct cortical responses via differential white matter activation. Proc Natl Acad Sci U S A, 2024, 121(14): e2314918121..
56. Renda E, Karmali S A, Yordanova I, et al. Effect of transcranial direct current stimulation on an individual’s ability to learn to control a brain-computer interface. McGill Journal of Medicine, 2019, 17(1). DOI: 10.26443/mjm.v17i1.129..
57. Metzger S L, Littlejohn K T, Silva A B, et al. A high-performance neuroprosthesis for speech decoding and avatar control. Nature, 2023, 620: 1037-1046..
58. Liu Y, Zhao Z, Xu M, et al. Decoding and synthesizing tonal language speech from brain activity. Sci Adv, 2023, 9(23): eadh0478..
59. Hassan M, Wendling F. Electroencephalography source connectivity: aiming for high resolution of brain networks in time and space. IEEE Signal Processing Magazine, 2018, 35(3): 81-96..

Journal of Biomedical Engineering

Applications and prospects of electroencephalography technology in neurorehabilitation assessment and treatment

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