Treffer: Brain-Computer Interfaces in Spinal Cord Injury: A Promising Therapeutic Strategy.
Title:
Brain-Computer Interfaces in Spinal Cord Injury: A Promising Therapeutic Strategy.
Authors:
Li S; Department of Spine Surgery, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China., Gao S; Department of Spine Surgery, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China., Hu Y; Department of Spine Surgery, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China., Xu J; Department of Operating Room, First Affiliated Hospital of Xinjiang Medical University, Urmuqi, Xinjiang Uygur Autonomous Region, China., Sheng W; Department of Spine Surgery, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China.
Source:
The European journal of neuroscience [Eur J Neurosci] 2025 Jul; Vol. 62 (1), pp. e70183.
Publication Type:
Journal Article; Review
Language:
English
Journal Info:
Publisher: Wiley-Blackwell Country of Publication: France NLM ID: 8918110 Publication Model: Print Cited Medium: Internet ISSN: 1460-9568 (Electronic) Linking ISSN: 0953816X NLM ISO Abbreviation: Eur J Neurosci Subsets: MEDLINE
Imprint Name(s):
Publication: : Oxford : Wiley-Blackwell
Original Publication: Oxford, UK : Published on behalf of the European Neuroscience Association by Oxford University Press, c1989-
Original Publication: Oxford, UK : Published on behalf of the European Neuroscience Association by Oxford University Press, c1989-
MeSH Terms:
References:
Ajiboye, A. B., F. R. Willett, D. R. Young, et al. 2017. “Restoration of Reaching and Grasping Movements Through Brain‐Controlled Muscle Stimulation in a Person With Tetraplegia: A Proof‐Of‐Concept Demonstration.” Lancet 389, no. 10081: 1821–1830. https://doi.org/10.1016/s0140‐6736(17)30601‐3.
Al‐Taleb, M. K. H., M. Purcell, M. Fraser, N. Petric‐Gray, and A. Vuckovic. 2019. “Home Used, Patient Self‐Managed, Brain‐Computer Interface for the Management of Central Neuropathic Pain Post Spinal Cord Injury: Usability Study.” Journal of Neuroengineering and Rehabilitation 16, no. 1: 128. https://doi.org/10.1186/s12984‐019‐0588‐7.
Ardaillon, H., S. Ribault, C. Herault, et al. 2024. “Striking the Balance: Embracing Technology While Upholding Humanistic Principles in Neurorehabilitation.” Neurorehabilitation and Neural Repair 38, no. 9: 705–710. https://doi.org/10.1177/15459683241265887.
Awuah, W. A., A. Ahluwalia, K. Darko, et al. 2024. “Bridging Minds and Machines: The Recent Advances of Brain‐Computer Interfaces in Neurological and Neurosurgical Applications.” World Neurosurgery 189: 138–153. https://doi.org/10.1016/j.wneu.2024.05.104.
Barnova, K., M. Mikolasova, R. V. Kahankova, et al. 2023. “Implementation of Artificial Intelligence and Machine Learning‐Based Methods in Brain‐Computer Interaction.” Computers in Biology and Medicine 163: 107135. https://doi.org/10.1016/j.compbiomed.2023.107135.
Benabid, A. L., T. Costecalde, A. Eliseyev, et al. 2019. “An Exoskeleton Controlled by an Epidural Wireless Brain‐Machine Interface in a Tetraplegic Patient: A Proof‐Of‐Concept Demonstration.” Lancet Neurology 18, no. 12: 1112–1122. https://doi.org/10.1016/s1474‐4422(19)30321‐7.
Blanco‐Diaz, C. F., E. Serafini, T. Bastos‐Filho, A. Dantas, C. Santo, and D. Delisle‐Rodriguez. 2025. “A Gait Imagery‐Based Brain‐Computer Interface with Visual Feedback for Spinal Cord Injury Rehabilitation on Lokomat.” IEEE Transactions on Biomedical Engineering 72, no. 1: 102–111. https://doi.org/10.1109/tbme.2024.3440036.
Bockbrader, M., N. Annetta, D. Friedenberg, et al. 2019. “Clinically Significant Gains in Skillful Grasp Coordination by an Individual With Tetraplegia Using an Implanted Brain‐Computer Interface With Forearm Transcutaneous Muscle Stimulation.” Archives of Physical Medicine and Rehabilitation 100, no. 7: 1201–1217. https://doi.org/10.1016/j.apmr.2018.07.445.
Bonizzato, M., R. Guay Hottin, S. L. Côté, et al. 2023. “Autonomous Optimization of Neuroprosthetic Stimulation Parameters That Drive the Motor Cortex and Spinal Cord Outputs in Rats and Monkeys.” Cell Reports Medicine 4, no. 4: 101008. https://doi.org/10.1016/j.xcrm.2023.101008.
Brunner, I., C. B. Lundquist, A. R. Pedersen, E. G. Spaich, S. Dosen, and A. Savic. 2024. “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.” Journal of Neuroengineering and Rehabilitation 21, no. 1: 10. https://doi.org/10.1186/s12984‐024‐01304‐1.
Cajigas, I., K. C. Davis, B. Meschede‐Krasa, et al. 2021. “Implantable Brain‐Computer Interface for Neuroprosthetic‐Enabled Volitional Hand Grasp Restoration in Spinal Cord Injury.” Brain Communications 3, no. 4: fcab248. https://doi.org/10.1093/braincomms/fcab248.
Cajigas, I., K. C. Davis, N. W. Prins, et al. 2022. “Brain‐Computer Interface Control of Stepping From Invasive Electrocorticography Upper‐Limb Motor Imagery in a Patient With Quadriplegia.” Frontiers in Human Neuroscience 16: 1077416. https://doi.org/10.3389/fnhum.2022.1077416.
Calderone, A., D. Cardile, R. De Luca, A. Quartarone, F. Corallo, and R. S. Calabrò. 2024. “Cognitive, Behavioral and Psychiatric Symptoms in Patients with Spinal Cord Injury: A Scoping Review.” Frontiers in Psychiatry 15: 1369714. https://doi.org/10.3389/fpsyt.2024.1369714.
Canny, E., M. J. Vansteensel, S. M. A. van der Salm, G. R. Müller‐Putz, and J. Berezutskaya. 2023. “Boosting Brain‐Computer Interfaces With Functional Electrical Stimulation: Potential Applications in People With Locked‐In Syndrome.” Journal of Neuroengineering and Rehabilitation 20, no. 1: 157. https://doi.org/10.1186/s12984‐023‐01272‐y.
Chai, X., T. Cao, Q. He, et al. 2024. “Brain‐Computer Interface Digital Prescription for Neurological Disorders.” CNS Neuroscience & Therapeutics 30, no. 2: e14615. https://doi.org/10.1111/cns.14615.
Chandrasekaran, S., N. A. Bhagat, R. Ramdeo, et al. 2023. “Targeted Transcutaneous Spinal Cord Stimulation Promotes Persistent Recovery of Upper Limb Strength and Tactile Sensation in Spinal Cord Injury: A Pilot Study.” Frontiers in Neuroscience 17: 1210328. https://doi.org/10.3389/fnins.2023.1210328.
Colachis, S. C., M. A. Bockbrader, M. Zhang, et al. 2018. “Dexterous Control of Seven Functional Hand Movements Using Cortically‐Controlled Transcutaneous Muscle Stimulation in a Person With Tetraplegia.” Frontiers in Neuroscience 12: 208. https://doi.org/10.3389/fnins.2018.00208.
Colachis, S. C., C. F. Dunlap, N. V. Annetta, S. M. Tamrakar, M. A. Bockbrader, and D. A. Friedenberg. 2021. “Long‐Term Intracortical Microelectrode Array Performance in a Human: A 5 Year Retrospective Analysis.” Journal of Neural Engineering 18, no. 4: 0460d7. https://doi.org/10.1088/1741‐2552/ac1add.
Colucci, A., M. Vermehren, A. Cavallo, et al. 2022. “Brain‐Computer Interface‐Controlled Exoskeletons in Clinical Neurorehabilitation: Ready or Not?” Neurorehabilitation and Neural Repair 36, no. 12: 747–756. https://doi.org/10.1177/15459683221138751.
Cuellar, C., L. Lehto, R. Islam, S. Mangia, S. Michaeli, and I. Lavrov. 2024. “Selective Activation of the Spinal Cord with Epidural Electrical Stimulation.” Brain Sciences 14, no. 7: 650. https://doi.org/10.3390/brainsci14070650.
Cui, Z., Y. Li, S. Huang, et al. 2022. “BCI System With Lower‐Limb Robot Improves Rehabilitation in Spinal Cord Injury Patients Through Short‐Term Training: A Pilot Study.” Cognitive Neurodynamics 16, no. 6: 1283–1301. https://doi.org/10.1007/s11571‐022‐09801‐6.
Davis, K. C., B. Meschede‐Krasa, I. Cajigas, et al. 2022. “Design‐Development of an at‐Home Modular Brain‐Computer Interface (BCI) Platform in a Case Study of Cervical Spinal Cord Injury.” Journal of Neuroengineering and Rehabilitation 19, no. 1: 53. https://doi.org/10.1186/s12984‐022‐01026‐2.
Di Gregorio, F., M. Steinhauser, M. E. Maier, J. F. Thayer, and S. Battaglia. 2024. “Error‐Related Cardiac Deceleration: Functional Interplay Between Error‐Related Brain Activity and Autonomic Nervous System in Performance Monitoring.” Neuroscience & Biobehavioral Reviews 157: 105542. https://doi.org/10.1016/j.neubiorev.2024.105542.
Dorrian, R. M., C. F. Berryman, A. Lauto, and A. V. Leonard. 2023. “Electrical Stimulation for the Treatment of Spinal Cord Injuries: A Review of the Cellular and Molecular Mechanisms That Drive Functional Improvements.” Frontiers in Cellular Neuroscience 17: 1095259. https://doi.org/10.3389/fncel.2023.1095259.
Dunkelberger, N., S. A. Carlson, J. Berning, E. M. Schearer, and M. K. O'Malley. 2024. “Multi Degree of Freedom Hybrid FES and Robotic Control of the Upper Limb.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 32: 956–966. https://doi.org/10.1109/tnsre.2024.3364517.
Edelman, B. J., S. Zhang, G. Schalk, et al. 2024. “Non‐invasive Brain‐Computer Interfaces: State of the Art and Trends.” IEEE Reviews in Biomedical Engineering 18: 26–49. https://doi.org/10.1109/rbme.2024.3449790.
Even‐Chen, N., S. D. Stavisky, C. Pandarinath, et al. 2018. “Feasibility of Automatic Error Detect‐and‐Undo System in Human Intracortical Brain‐Computer Interfaces.” IEEE Transactions on Biomedical Engineering 65, no. 8: 1771–1784. https://doi.org/10.1109/tbme.2017.2776204.
Ferrero, L., P. Soriano‐Segura, J. Navarro, et al. 2024. “Brain‐Machine Interface Based on Deep Learning to Control Asynchronously a Lower‐Limb Robotic Exoskeleton: A Case‐of‐Study.” Journal of Neuroengineering and Rehabilitation 21, no. 1: 48. https://doi.org/10.1186/s12984‐024‐01342‐9.
Flack, J. A., K. D. Sharma, and J. Y. Xie. 2022. “Delving Into the Recent Advancements of Spinal Cord Injury Treatment: A Review of Recent Progress.” Neural Regeneration Research 17, no. 2: 283–291. https://doi.org/10.4103/1673‐5374.317961.
Ganzer, P. D., S. C. Colachis, M. A. Schwemmer, et al. 2020. “Restoring the Sense of Touch Using a Sensorimotor Demultiplexing Neural Interface.” Cell 181, no. 4: 763–773.e712. https://doi.org/10.1016/j.cell.2020.03.054.
Greiner, N., B. Barra, G. Schiavone, et al. 2021. “Recruitment of Upper‐Limb Motoneurons With Epidural Electrical Stimulation of the Cervical Spinal Cord.” Nature Communications 12, no. 1: 435. https://doi.org/10.1038/s41467‐020‐20703‐1.
Grijalva‐Otero, I., and E. Doncel‐Pérez. 2024. “Traumatic Human Spinal Cord Injury: Are Single Treatments Enough to Solve the Problem?” Archives of Medical Research 55, no. 1: 102935. https://doi.org/10.1016/j.arcmed.2023.102935.
Guan, S., H. Tian, Y. Yang, et al. 2023. “Self‐Assembled Ultraflexible Probes for Long‐Term Neural Recordings and Neuromodulation.” Nature Protocols 18, no. 6: 1712–1744. https://doi.org/10.1038/s41596‐023‐00824‐9.
Guerreiro Fernandes, F., M. Raemaekers, Z. Freudenburg, and N. Ramsey. 2024. “Considerations for Implanting Speech Brain Computer Interfaces Based on Functional Magnetic Resonance Imaging.” Journal of Neural Engineering 21, no. 3: 036005. https://doi.org/10.1088/1741‐2552/ad4178.
Guttmann‐Flury, E., X. Sheng, and X. Zhu. 2023. “Channel Selection From Source Localization: A Review of Four EEG‐Based Brain‐Computer Interfaces Paradigms.” Behavior Research Methods 55, no. 4: 1980–2003. https://doi.org/10.3758/s13428‐022‐01897‐2.
Habelt, B., C. Wirth, D. Afanasenkau, et al. 2021. “A Multimodal Neuroprosthetic Interface to Record, Modulate and Classify Electrophysiological Biomarkers Relevant to Neuropsychiatric Disorders.” Frontiers in Bioengineering and Biotechnology 9: 770274. https://doi.org/10.3389/fbioe.2021.770274.
Håkansson, S., M. Tuci, M. Bolliger, A. Curt, C. R. Jutzeler, and S. C. Brüningk. 2024. “Data‐Driven Prediction of Spinal Cord Injury Recovery: An Exploration of Current Status and Future Perspectives.” Experimental Neurology 380: 114913. https://doi.org/10.1016/j.expneurol.2024.114913.
Han, X., M. Zhang, L. Yan, et al. 2024. “Role of Dendritic Cells in Spinal Cord Injury.” CNS Neuroscience & Therapeutics 30, no. 3: e14593. https://doi.org/10.1111/cns.14593.
Herbert, C. 2023. “Analyzing and Computing Humans by Means of the Brain Using Brain‐Computer Interfaces—Understanding the User—Previous Evidence, Self‐relevance and the User's Self‐Concept as Potential Superordinate Human Factors of Relevance.” Frontiers in Human Neuroscience 17: 1286895. https://doi.org/10.3389/fnhum.2023.1286895.
Herring, E. Z., E. L. Graczyk, W. D. Memberg, et al. 2024. “Reconnecting the Hand and Arm to the Brain: Efficacy of Neural Interfaces for Sensorimotor Restoration After Tetraplegia.” Neurosurgery 94, no. 4: 864–874. https://doi.org/10.1227/neu.0000000000002769.
Hofmann, U. G., and T. Stieglitz. 2024. “Why Some BCI Should Still Be Called BMI.” Nature Communications 15, no. 1: 6207. https://doi.org/10.1038/s41467‐024‐50603‐7.
Hu, Z., Z. Zhou, and H. Lyu. 2025. “A Power‐and‐Area‐Efficient Channel‐Interleaved Neural Signal Processor for Wireless Brain‐Computer Interfaces with Unsupervised Spike Sorting.” IEEE Transactions on Biomedical Circuits and Systems 19, no. 1: 108–119. https://doi.org/10.1109/tbcas.2024.3395353.
Huang, C., N. Shi, Y. Miao, X. Chen, Y. Wang, and X. Gao. 2024. “Visual tracking brain‐computer interface.” iScience 27, no. 4: 109376. https://doi.org/10.1016/j.isci.2024.109376.
Huo, C., G. Xu, H. Xie, et al. 2024. “Functional Near‐Infrared Spectroscopy in Non‐Invasive Neuromodulation.” Neural Regeneration Research 19, no. 7: 1517–1522. https://doi.org/10.4103/1673‐5374.387970.
Jervis‐Rademeyer, H., K. Ong, A. Djuric, S. Munce, K. E. Musselman, and C. Marquez‐Chin. 2022. “Therapists' Perspectives on Using Brain–Computer Interface‐Triggered Functional Electrical Stimulation Therapy for Individuals Living with Upper Extremity Paralysis: A Qualitative Case Series Study.” Journal of Neuroengineering and Rehabilitation 19, no. 1: 127. https://doi.org/10.1186/s12984‐022‐01107‐2.
Jiang, H., R. Wang, Z. Zheng, et al. 2022. “Short Report: Surgery for Implantable Brain–Computer Interface Assisted by Robotic Navigation System.” Acta Neurochirurgica 164, no. 9: 2299–2302. https://doi.org/10.1007/s00701‐022‐05235‐5.
Jovanovic, L. I., M. R. Popovic, and C. Marquez‐Chin. 2022. “Characterizing the Stimulation Interference in Electroencephalographic Signals During Brain–Computer Interface‐Controlled Functional Electrical Stimulation Therapy.” Artificial Organs 46, no. 3: 398–411. https://doi.org/10.1111/aor.14059.
Keough, J. R., B. Irvine, D. Kelly, et al. 2024. “Fatigue in Children Using Motor Imagery and P300 Brain–Computer Interfaces.” Journal of Neuroengineering and Rehabilitation 21, no. 1: 61. https://doi.org/10.1186/s12984‐024‐01349‐2.
Keyl, P., M. Schneiders, C. Schuld, et al. 2018. “Differences in Characteristics of Error‐Related Potentials Between Individuals With Spinal Cord Injury and Age‐ and Sex‐Matched Able‐Bodied Controls.” Frontiers in Neurology 9: 1192. https://doi.org/10.3389/fneur.2018.01192.
Lazarou, I., S. Nikolopoulos, K. Georgiadis, V. P. Oikonomou, A. Mariakaki, and I. Kompatsiaris. 2022. “Exploring the Connection of Brain Computer Interfaces and Multimedia Use With the Social Integration of People With Various Motor Disabilities: A Questionnaire‐Based Usability Study.” Frontiers in Digital Health 4: 846963. https://doi.org/10.3389/fdgth.2022.846963.
Letourneau, S., E. T. Zewdie, Z. Jadavji, J. Andersen, L. M. Burkholder, and A. Kirton. 2020. “Clinician Awareness of Brain Computer Interfaces: A Canadian National Survey.” Journal of Neuroengineering and Rehabilitation 17, no. 1: 2. https://doi.org/10.1186/s12984‐019‐0624‐7.
Levett, J. J., L. M. Elkaim, F. Niazi, et al. 2024. “Invasive Brain Computer Interface for Motor Restoration in Spinal Cord Injury: A Systematic Review.” Neuromodulation 27, no. 4: 597–603. https://doi.org/10.1016/j.neurom.2023.10.006.
Li, H., M. Liu, X. Yu, et al. 2022. “Coherence Based Graph Convolution Network for Motor Imagery‐Induced EEG After Spinal Cord Injury.” Frontiers in Neuroscience 16: 1097660. https://doi.org/10.3389/fnins.2022.1097660.
Li, Y., Y. Hu, I. Pozzato, et al. 2024. “Efficacy of Interventions to Improve Cognitive Function in Adults With Spinal Cord Injury: A Systematic Review.” Journal of Neurotrauma 41: 2075–2088. https://doi.org/10.1089/neu.2024.0032.
Lin, S., J. Jiang, K. Huang, et al. 2023. “Advanced Electrode Technologies for Noninvasive Brain–Computer Interfaces.” ACS Nano 17, no. 24: 24487–24513. https://doi.org/10.1021/acsnano.3c06781.
Liu, J., R. Wang, Y. Yang, et al. 2024. “Convolutional Transformer‐Based Cross Subject Model for SSVEP‐Based BCI Classification.” IEEE Journal of Biomedical and Health Informatics 28: 6581–6593. https://doi.org/10.1109/jbhi.2024.3454158.
Liu, L., J. Li, R. Ouyang, et al. 2024. “Multimodal Brain‐Controlled System for Rehabilitation Training: Combining Asynchronous Online Brain‐Computer Interface and Exoskeleton.” Journal of Neuroscience Methods 406: 110132. https://doi.org/10.1016/j.jneumeth.2024.110132.
Lopes‐Dias, C., A. I. Sburlea, K. Breitegger, et al. 2021. “Online Asynchronous Detection of Error‐Related Potentials in Participants with a Spinal Cord Injury Using a Generic Classifier.” Journal of Neural Engineering 18, no. 4: 046022. https://doi.org/10.1088/1741‐2552/abd1eb.
Madigan, C. D., J. A. King, C. Taylor, et al. 2024. “A Systematic Review and Qualitative Synthesis of Weight Management Interventions for People With Spinal Cord Injury.” Obesity Reviews 25, no. 9: e13785. https://doi.org/10.1111/obr.13785.
McGeady, C., A. Vučković, Y. P. Zheng, and M. Alam. 2021. “EEG Monitoring Is Feasible and Reliable During Simultaneous Transcutaneous Electrical Spinal Cord Stimulation.” Sensors (Basel) 21, no. 19: 6593. https://doi.org/10.3390/s21196593.
Mirzabagherian, H., M. B. Menhaj, A. A. Suratgar, N. Talebi, M. R. Abbasi Sardari, and A. Sajedin. 2023. “Temporal‐Spatial Convolutional Residual Network for Decoding Attempted Movement Related EEG Signals of Subjects With Spinal Cord Injury.” Computers in Biology and Medicine 164: 107159. https://doi.org/10.1016/j.compbiomed.2023.107159.
Nakatani, S., N. Araki, T. Hoshino, O. Fukayama, and K. Mabuchi. 2021. “Brain‐Controlled Cycling System for Rehabilitation Following Paraplegia with Delay‐Time Prediction.” Journal of Neural Engineering 18, no. 1: 016022. https://doi.org/10.1088/1741‐2552/abd1bf.
Nann, M., N. Peekhaus, C. Angerhöfer, and S. R. Soekadar. 2020. “Feasibility and Safety of Bilateral Hybrid EEG/EOG Brain/Neural‐Machine Interaction.” Frontiers in Human Neuroscience 14: 580105. https://doi.org/10.3389/fnhum.2020.580105.
Naseer, N., I. K. Niazi, and H. Santosa. 2024. “Editorial: Signal Processing for Brain–Computer Interfaces—Special Issue.” Sensors (Basel) 24, no. 4: 1201. https://doi.org/10.3390/s24041201.
Neumann, W. J. 2024. “Cortical Brain Signals Improve Decoding of Movement and Tremor for Clinical Brain Computer Interfaces.” Clinical Neurophysiology 157: 143–145. https://doi.org/10.1016/j.clinph.2023.11.017.
Nicolelis, M. A. L., E. J. L. Alho, A. R. C. Donati, et al. 2022. “Training With Noninvasive Brain‐Machine Interface, Tactile Feedback, and Locomotion to Enhance Neurological Recovery in Individuals With Complete Paraplegia: A Randomized Pilot Study.” Scientific Reports 12, no. 1: 20545. https://doi.org/10.1038/s41598‐022‐24864‐5.
Ownsworth, T., H. Mols, J. O'Loghlen, et al. 2024. “Stigma Following Acquired Brain Injury and Spinal Cord Injury: Relationship to Psychological Distress and Community Integration in the First‐Year Post‐Discharge.” Disability and Rehabilitation 46, no. 9: 1796–1806. https://doi.org/10.1080/09638288.2023.2205173.
Oxley, T. J., N. L. Opie, S. E. John, et al. 2016. “Minimally Invasive Endovascular Stent‐Electrode Array for High‐Fidelity, Chronic Recordings of Cortical Neural Activity.” Nature Biotechnology 34, no. 3: 320–327. https://doi.org/10.1038/nbt.3428.
Pais‐Vieira, C., J. G. Figueiredo, A. Perrotta, et al. 2024. “Activation of a Rhythmic Lower Limb Movement Pattern During the Use of a Multimodal Brain–Computer Interface: A Case Study of a Clinically Complete Spinal Cord Injury.” Life (Basel) 14, no. 3: 396. https://doi.org/10.3390/life14030396.
Pais‐Vieira, C., P. Gaspar, D. Matos, et al. 2022. “Embodiment Comfort Levels During Motor Imagery Training Combined With Immersive Virtual Reality in a Spinal Cord Injury Patient.” Frontiers in Human Neuroscience 16: 909112. https://doi.org/10.3389/fnhum.2022.909112.
Pancholi, S., J. P. Wachs, and B. S. Duerstock. 2024. “Use of Artificial Intelligence Techniques to Assist Individuals with Physical Disabilities.” Annual Review of Biomedical Engineering 26, no. 1: 1–24. https://doi.org/10.1146/annurev‐bioeng‐082222‐012531.
Perna, A., G. N. Angotzi, L. Berdondini, and J. F. Ribeiro. 2023. “Advancing the Interfacing Performances of Chronically Implantable Neural Probes in the Era of CMOS Neuroelectronics.” Frontiers in Neuroscience 17: 1275908. https://doi.org/10.3389/fnins.2023.1275908.
Pfeffer, M. A., S. S. H. Ling, and J. K. W. Wong. 2024. “Exploring the Frontier: Transformer‐Based Models in EEG Signal Analysis for Brain–Computer Interfaces.” Computers in Biology and Medicine 178: 108705. https://doi.org/10.1016/j.compbiomed.2024.108705.
Rubin, D. B., A. B. Ajiboye, L. Barefoot, et al. 2023. “Interim Safety Profile From the Feasibility Study of the BrainGate Neural Interface System.” Neurology 100, no. 11: e1177–e1192. https://doi.org/10.1212/wnl.0000000000201707.
Rubin, D. B., T. Hosman, J. N. Kelemen, et al. 2022. “Learned Motor Patterns Are Replayed in Human Motor Cortex During Sleep.” Journal of Neuroscience 42, no. 25: 5007–5020. https://doi.org/10.1523/jneurosci.2074‐21.2022.
Samejima, S., A. Khorasani, V. Ranganathan, et al. 2021. “Brain–Computer‐Spinal Interface Restores Upper Limb Function After Spinal Cord Injury.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 29: 1233–1242. https://doi.org/10.1109/tnsre.2021.3090269.
Saway, B. F., C. Palmer, C. Hughes, et al. 2024. “The Evolution of Neuromodulation for Chronic Stroke: From Neuroplasticity Mechanisms to Brain‐Computer Interfaces.” Neurotherapeutics 21, no. 3: e00337. https://doi.org/10.1016/j.neurot.2024.e00337.
Shen, K., O. Chen, J. L. Edmunds, D. K. Piech, and M. M. Maharbiz. 2023. “Translational Opportunities and Challenges of Invasive Electrodes for Neural Interfaces.” Nature Biomedical Engineering 7, no. 4: 424–442. https://doi.org/10.1038/s41551‐023‐01021‐5.
Shen, X., T. Sun, Z. Li, and Y. Wu. 2023. “Generation of Locomotor‐Like Activity Using Monopolar Intraspinal Electrical Microstimulation in Rats.” Experimental and Therapeutic Medicine 26, no. 6: 560. https://doi.org/10.3892/etm.2023.12259.
Shokur, S., A. R. C. Donati, D. S. F. Campos, et al. 2018. “Training With Brain‐Machine Interfaces, Visuo‐Tactile Feedback and Assisted Locomotion Improves Sensorimotor, Visceral, and Psychological Signs in Chronic Paraplegic Patients.” PLoS ONE 13, no. 11: e0206464. https://doi.org/10.1371/journal.pone.0206464.
Sieghartsleitner, S., M. Sebastián‐Romagosa, W. Cho, et al. 2024. “Upper Extremity Training Followed by Lower Extremity Training with a Brain–Computer Interface Rehabilitation System.” Frontiers in Neuroscience 18: 1346607. https://doi.org/10.3389/fnins.2024.1346607.
Song, M., D. Gwon, S. C. Jun, and M. Ahn. 2024. “Signal Alignment for Cross‐Datasets in P300 Brain–Computer Interfaces.” Journal of Neural Engineering 21, no. 3: 036007. https://doi.org/10.1088/1741‐2552/ad430d.
Steele, A. G., G. A. Manson, P. J. Horner, D. G. Sayenko, and J. L. Contreras‐Vidal. 2022. “Effects of Transcutaneous Spinal Stimulation on Spatiotemporal Cortical Activation Patterns: A Proof‐Of‐Concept EEG Study.” Journal of Neural Engineering 19, no. 4: 046001. https://doi.org/10.1088/1741‐2552/ac7b4b.
Valencia, D., G. Leone, N. Keller, P. P. Mercier, and A. Alimohammad. 2023. “Power‐Efficientin Vivobrain‐Machine Interfaces via Brain‐State Estimation.” Journal of Neural Engineering 20, no. 1: 016032. https://doi.org/10.1088/1741‐2552/acb385.
Van de Wauw, C., L. Riecke, R. Goebel, A. Kaas, and B. Sorger. 2023. “Talking With Hands and Feet: Selective Somatosensory Attention and fMRI Enable Robust and Convenient Brain‐Based Communication.” NeuroImage 276: 120172. https://doi.org/10.1016/j.neuroimage.2023.120172.
Vansteensel, M. J., E. Klein, G. van Thiel, et al. 2023. “Towards Clinical Application of Implantable Brain–Computer Interfaces for People With Late‐Stage ALS: Medical and Ethical Considerations.” Journal of Neurology 270, no. 3: 1323–1336. https://doi.org/10.1007/s00415‐022‐11464‐6.
Várkuti, B., L. Halász, S. Hagh Gooie, et al. 2024. “Conversion of a Medical Implant Into a Versatile Computer–Brain Interface.” Brain Stimulation 17, no. 1: 39–48. https://doi.org/10.1016/j.brs.2023.12.011.
Vincent, C., F. S. Dumont, M. Rogers, et al. 2024. “Perspectives of Wheelchair Users with Chronic Spinal Cord Injury Following a Walking Program Using a Wearable Robotic Exoskeleton.” Disability and Rehabilitation 46: 1–9. https://doi.org/10.1080/09638288.2024.2317994.
Vorreuther, A., L. Bastian, A. Benitez Andonegui, et al. 2023. “It Takes Two (Seconds): Decreasing Encoding Time for Two‐Choice Functional Near‐Infrared Spectroscopy Brain‐Computer Interface Communication.” Neurophotonics 10, no. 4: 045005. https://doi.org/10.1117/1.NPh.10.4.045005.
Wan, C., M. Pei, K. Shi, et al. 2024. “Toward a Brain–Neuromorphics Interface.” Advanced Materials 36: e2311288. https://doi.org/10.1002/adma.202311288.
Wang, J., T. Wang, H. Liu, et al. 2023. “Flexible Electrodes for Brain–Computer Interface System.” Advanced Materials 35, no. 47: e2211012. https://doi.org/10.1002/adma.202211012.
Wang, R., and J. Bai. 2024. “Pharmacological Interventions Targeting the Microcirculation Following Traumatic Spinal Cord Injury.” Neural Regeneration Research 19, no. 1: 35–42. https://doi.org/10.4103/1673‐5374.375304.
Wang, T., G. Huang, Z. Yi, S. Dai, W. Zhuang, and S. Guo. 2024. “Advances in Extracellular Vesicle‐Based Combination Therapies for Spinal Cord Injury.” Neural Regeneration Research 19, no. 2: 369–374. https://doi.org/10.4103/1673‐5374.377413.
Wang, Y., X. Yang, X. Zhang, Y. Wang, and W. Pei. 2023. “Implantable Intracortical Microelectrodes: Reviewing the Present with a Focus on the Future.” Microsystems & Nanoengineering 9: 7. https://doi.org/10.1038/s41378‐022‐00451‐6.
Wang, Z., S. Li, J. Luo, J. Liu, and D. Wu. 2024. “Channel Reflection: Knowledge‐Driven Data Augmentation for EEG‐Based Brain–Computer Interfaces.” Neural Networks 176: 106351. https://doi.org/10.1016/j.neunet.2024.106351.
Webster, P. 2024. “The Future of Brain–Computer Interfaces in Medicine.” Nature Medicine 30, no. 6: 1508–1509. https://doi.org/10.1038/d41591‐024‐00031‐3.
Wen, D., Y. Fan, S. H. Hsu, et al. 2021. “Combining Brain–Computer Interface and Virtual Reality for Rehabilitation in Neurological Diseases: A Narrative Review.” Annals of Physical and Rehabilitation Medicine 64, no. 1: 101404. https://doi.org/10.1016/j.rehab.2020.03.015.
Willett, F. R., D. T. Avansino, L. R. Hochberg, J. M. Henderson, and K. V. Shenoy. 2021. “High‐Performance Brain‐to‐Text Communication via Handwriting.” Nature 593, no. 7858: 249–254. https://doi.org/10.1038/s41586‐021‐03506‐2.
Wu, H., S. Li, and D. Wu. 2024. “Motor Imagery Classification for Asynchronous EEG‐Based Brain–Computer Interfaces.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 32: 527–536. https://doi.org/10.1109/tnsre.2024.3356916.
Wu, X., B. Metcalfe, S. He, H. Tan, and D. Zhang. 2024. “A Review of Motor Brain–Computer Interfaces Using Intracranial Electroencephalography Based on Surface Electrodes and Depth Electrodes.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 32: 2408–2431. https://doi.org/10.1109/tnsre.2024.3421551.
Xu, F., J. Li, G. Dong, et al. 2022. “EEG Decoding Method Based on Multi‐Feature Information Fusion for Spinal Cord Injury.” Neural Networks 156: 135–151. https://doi.org/10.1016/j.neunet.2022.09.016.
Xu, F., C. Wang, X. Yu, et al. 2023. “One‐Dimensional Local Binary Pattern and Common Spatial Pattern Feature Fusion Brain Network for Central Neuropathic Pain.” International Journal of Neural Systems 33, no. 6: 2350030. https://doi.org/10.1142/s0129065723500302.
Xu, X., R. Liu, Y. Li, et al. 2024. “Spinal Cord Injury: From MicroRNAs to Exosomal MicroRNAs.” Molecular Neurobiology 61, no. 8: 5974–5991. https://doi.org/10.1007/s12035‐024‐03954‐7.
Yakovlev, L., N. Syrov, and A. Kaplan. 2023. “Investigating the Influence of Functional Electrical Stimulation on Motor Imagery Related μ‐Rhythm Suppression.” Frontiers in Neuroscience 17: 1202951. https://doi.org/10.3389/fnins.2023.1202951.
Yang, S. H., C. J. Huang, and J. S. Huang. 2024. “Increasing Robustness of Intracortical Brain–Computer Interfaces for Recording Condition Changes via Data Augmentation.” Computer Methods and Programs in Biomedicine 251: 108208. https://doi.org/10.1016/j.cmpb.2024.108208.
Yang, Y., S. Luo, W. Wang, X. Gao, X. Yao, and T. Wu. 2024. “From Bench to Bedside: Overview of Magnetoencephalography in Basic Principle, Signal Processing, Source Localization and Clinical Applications.” NeuroImage: Clinical 42: 103608. https://doi.org/10.1016/j.nicl.2024.103608.
Yeom, H. G., J. S. Kim, and C. K. Chung. 2023. “A Magnetoencephalography Dataset During Three‐Dimensional Reaching Movements for Brain–Computer Interfaces.” Scientific Data 10, no. 1: 552. https://doi.org/10.1038/s41597‐023‐02454‐y.
Yin, Z., B. Wan, G. Gong, and J. Yin. 2024. “ROS: Executioner of Regulating Cell Death in Spinal Cord Injury.” Frontiers in Immunology 15: 1330678. https://doi.org/10.3389/fimmu.2024.1330678.
Young, D., F. Willett, W. D. Memberg, et al. 2018. “Signal Processing Methods for Reducing Artifacts in Microelectrode Brain Recordings Caused by Functional Electrical Stimulation.” Journal of Neural Engineering 15, no. 2: 026014. https://doi.org/10.1088/1741‐2552/aa9ee8.
Zeller, S. L., A. Stein, I. Frid, et al. 2024. “Critical Care of Spinal Cord Injury.” Current Neurology and Neuroscience Reports 24: 355–363. https://doi.org/10.1007/s11910‐024‐01357‐8.
Zhang, H., L. Jiao, S. Yang, et al. 2024. “Brain–Computer Interfaces: The Innovative Key to Unlocking Neurological Conditions.” International Journal of Surgery 110, no. 9: 5745–5762. https://doi.org/10.1097/js9.0000000000002022.
Zhou, K., W. Wei, D. Yang, et al. 2024. “Dual Electrical Stimulation at Spinal‐Muscular Interface Reconstructs Spinal Sensorimotor Circuits After Spinal Cord Injury.” Nature Communications 15, no. 1: 619. https://doi.org/10.1038/s41467‐024‐44898‐9.
Ziai, Y., S. S. Zargarian, C. Rinoldi, et al. 2023. “Conducting Polymer‐Based Nanostructured Materials for Brain–Machine Interfaces.” Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology 15, no. 5: e1895. https://doi.org/10.1002/wnan.1895.
Zulauf‐Czaja, A., M. K. H. Al‐Taleb, M. Purcell, N. Petric‐Gray, J. Cloughley, and A. Vuckovic. 2021. “On the Way Home: A BCI‐FES Hand Therapy Self‐Managed by Sub‐Acute SCI Participants and Their Caregivers: A Usability Study.” Journal of Neuroengineering and Rehabilitation 18, no. 1: 44. https://doi.org/10.1186/s12984‐021‐00838‐y.
Al‐Taleb, M. K. H., M. Purcell, M. Fraser, N. Petric‐Gray, and A. Vuckovic. 2019. “Home Used, Patient Self‐Managed, Brain‐Computer Interface for the Management of Central Neuropathic Pain Post Spinal Cord Injury: Usability Study.” Journal of Neuroengineering and Rehabilitation 16, no. 1: 128. https://doi.org/10.1186/s12984‐019‐0588‐7.
Ardaillon, H., S. Ribault, C. Herault, et al. 2024. “Striking the Balance: Embracing Technology While Upholding Humanistic Principles in Neurorehabilitation.” Neurorehabilitation and Neural Repair 38, no. 9: 705–710. https://doi.org/10.1177/15459683241265887.
Awuah, W. A., A. Ahluwalia, K. Darko, et al. 2024. “Bridging Minds and Machines: The Recent Advances of Brain‐Computer Interfaces in Neurological and Neurosurgical Applications.” World Neurosurgery 189: 138–153. https://doi.org/10.1016/j.wneu.2024.05.104.
Barnova, K., M. Mikolasova, R. V. Kahankova, et al. 2023. “Implementation of Artificial Intelligence and Machine Learning‐Based Methods in Brain‐Computer Interaction.” Computers in Biology and Medicine 163: 107135. https://doi.org/10.1016/j.compbiomed.2023.107135.
Benabid, A. L., T. Costecalde, A. Eliseyev, et al. 2019. “An Exoskeleton Controlled by an Epidural Wireless Brain‐Machine Interface in a Tetraplegic Patient: A Proof‐Of‐Concept Demonstration.” Lancet Neurology 18, no. 12: 1112–1122. https://doi.org/10.1016/s1474‐4422(19)30321‐7.
Blanco‐Diaz, C. F., E. Serafini, T. Bastos‐Filho, A. Dantas, C. Santo, and D. Delisle‐Rodriguez. 2025. “A Gait Imagery‐Based Brain‐Computer Interface with Visual Feedback for Spinal Cord Injury Rehabilitation on Lokomat.” IEEE Transactions on Biomedical Engineering 72, no. 1: 102–111. https://doi.org/10.1109/tbme.2024.3440036.
Bockbrader, M., N. Annetta, D. Friedenberg, et al. 2019. “Clinically Significant Gains in Skillful Grasp Coordination by an Individual With Tetraplegia Using an Implanted Brain‐Computer Interface With Forearm Transcutaneous Muscle Stimulation.” Archives of Physical Medicine and Rehabilitation 100, no. 7: 1201–1217. https://doi.org/10.1016/j.apmr.2018.07.445.
Bonizzato, M., R. Guay Hottin, S. L. Côté, et al. 2023. “Autonomous Optimization of Neuroprosthetic Stimulation Parameters That Drive the Motor Cortex and Spinal Cord Outputs in Rats and Monkeys.” Cell Reports Medicine 4, no. 4: 101008. https://doi.org/10.1016/j.xcrm.2023.101008.
Brunner, I., C. B. Lundquist, A. R. Pedersen, E. G. Spaich, S. Dosen, and A. Savic. 2024. “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.” Journal of Neuroengineering and Rehabilitation 21, no. 1: 10. https://doi.org/10.1186/s12984‐024‐01304‐1.
Cajigas, I., K. C. Davis, B. Meschede‐Krasa, et al. 2021. “Implantable Brain‐Computer Interface for Neuroprosthetic‐Enabled Volitional Hand Grasp Restoration in Spinal Cord Injury.” Brain Communications 3, no. 4: fcab248. https://doi.org/10.1093/braincomms/fcab248.
Cajigas, I., K. C. Davis, N. W. Prins, et al. 2022. “Brain‐Computer Interface Control of Stepping From Invasive Electrocorticography Upper‐Limb Motor Imagery in a Patient With Quadriplegia.” Frontiers in Human Neuroscience 16: 1077416. https://doi.org/10.3389/fnhum.2022.1077416.
Calderone, A., D. Cardile, R. De Luca, A. Quartarone, F. Corallo, and R. S. Calabrò. 2024. “Cognitive, Behavioral and Psychiatric Symptoms in Patients with Spinal Cord Injury: A Scoping Review.” Frontiers in Psychiatry 15: 1369714. https://doi.org/10.3389/fpsyt.2024.1369714.
Canny, E., M. J. Vansteensel, S. M. A. van der Salm, G. R. Müller‐Putz, and J. Berezutskaya. 2023. “Boosting Brain‐Computer Interfaces With Functional Electrical Stimulation: Potential Applications in People With Locked‐In Syndrome.” Journal of Neuroengineering and Rehabilitation 20, no. 1: 157. https://doi.org/10.1186/s12984‐023‐01272‐y.
Chai, X., T. Cao, Q. He, et al. 2024. “Brain‐Computer Interface Digital Prescription for Neurological Disorders.” CNS Neuroscience & Therapeutics 30, no. 2: e14615. https://doi.org/10.1111/cns.14615.
Chandrasekaran, S., N. A. Bhagat, R. Ramdeo, et al. 2023. “Targeted Transcutaneous Spinal Cord Stimulation Promotes Persistent Recovery of Upper Limb Strength and Tactile Sensation in Spinal Cord Injury: A Pilot Study.” Frontiers in Neuroscience 17: 1210328. https://doi.org/10.3389/fnins.2023.1210328.
Colachis, S. C., M. A. Bockbrader, M. Zhang, et al. 2018. “Dexterous Control of Seven Functional Hand Movements Using Cortically‐Controlled Transcutaneous Muscle Stimulation in a Person With Tetraplegia.” Frontiers in Neuroscience 12: 208. https://doi.org/10.3389/fnins.2018.00208.
Colachis, S. C., C. F. Dunlap, N. V. Annetta, S. M. Tamrakar, M. A. Bockbrader, and D. A. Friedenberg. 2021. “Long‐Term Intracortical Microelectrode Array Performance in a Human: A 5 Year Retrospective Analysis.” Journal of Neural Engineering 18, no. 4: 0460d7. https://doi.org/10.1088/1741‐2552/ac1add.
Colucci, A., M. Vermehren, A. Cavallo, et al. 2022. “Brain‐Computer Interface‐Controlled Exoskeletons in Clinical Neurorehabilitation: Ready or Not?” Neurorehabilitation and Neural Repair 36, no. 12: 747–756. https://doi.org/10.1177/15459683221138751.
Cuellar, C., L. Lehto, R. Islam, S. Mangia, S. Michaeli, and I. Lavrov. 2024. “Selective Activation of the Spinal Cord with Epidural Electrical Stimulation.” Brain Sciences 14, no. 7: 650. https://doi.org/10.3390/brainsci14070650.
Cui, Z., Y. Li, S. Huang, et al. 2022. “BCI System With Lower‐Limb Robot Improves Rehabilitation in Spinal Cord Injury Patients Through Short‐Term Training: A Pilot Study.” Cognitive Neurodynamics 16, no. 6: 1283–1301. https://doi.org/10.1007/s11571‐022‐09801‐6.
Davis, K. C., B. Meschede‐Krasa, I. Cajigas, et al. 2022. “Design‐Development of an at‐Home Modular Brain‐Computer Interface (BCI) Platform in a Case Study of Cervical Spinal Cord Injury.” Journal of Neuroengineering and Rehabilitation 19, no. 1: 53. https://doi.org/10.1186/s12984‐022‐01026‐2.
Di Gregorio, F., M. Steinhauser, M. E. Maier, J. F. Thayer, and S. Battaglia. 2024. “Error‐Related Cardiac Deceleration: Functional Interplay Between Error‐Related Brain Activity and Autonomic Nervous System in Performance Monitoring.” Neuroscience & Biobehavioral Reviews 157: 105542. https://doi.org/10.1016/j.neubiorev.2024.105542.
Dorrian, R. M., C. F. Berryman, A. Lauto, and A. V. Leonard. 2023. “Electrical Stimulation for the Treatment of Spinal Cord Injuries: A Review of the Cellular and Molecular Mechanisms That Drive Functional Improvements.” Frontiers in Cellular Neuroscience 17: 1095259. https://doi.org/10.3389/fncel.2023.1095259.
Dunkelberger, N., S. A. Carlson, J. Berning, E. M. Schearer, and M. K. O'Malley. 2024. “Multi Degree of Freedom Hybrid FES and Robotic Control of the Upper Limb.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 32: 956–966. https://doi.org/10.1109/tnsre.2024.3364517.
Edelman, B. J., S. Zhang, G. Schalk, et al. 2024. “Non‐invasive Brain‐Computer Interfaces: State of the Art and Trends.” IEEE Reviews in Biomedical Engineering 18: 26–49. https://doi.org/10.1109/rbme.2024.3449790.
Even‐Chen, N., S. D. Stavisky, C. Pandarinath, et al. 2018. “Feasibility of Automatic Error Detect‐and‐Undo System in Human Intracortical Brain‐Computer Interfaces.” IEEE Transactions on Biomedical Engineering 65, no. 8: 1771–1784. https://doi.org/10.1109/tbme.2017.2776204.
Ferrero, L., P. Soriano‐Segura, J. Navarro, et al. 2024. “Brain‐Machine Interface Based on Deep Learning to Control Asynchronously a Lower‐Limb Robotic Exoskeleton: A Case‐of‐Study.” Journal of Neuroengineering and Rehabilitation 21, no. 1: 48. https://doi.org/10.1186/s12984‐024‐01342‐9.
Flack, J. A., K. D. Sharma, and J. Y. Xie. 2022. “Delving Into the Recent Advancements of Spinal Cord Injury Treatment: A Review of Recent Progress.” Neural Regeneration Research 17, no. 2: 283–291. https://doi.org/10.4103/1673‐5374.317961.
Ganzer, P. D., S. C. Colachis, M. A. Schwemmer, et al. 2020. “Restoring the Sense of Touch Using a Sensorimotor Demultiplexing Neural Interface.” Cell 181, no. 4: 763–773.e712. https://doi.org/10.1016/j.cell.2020.03.054.
Greiner, N., B. Barra, G. Schiavone, et al. 2021. “Recruitment of Upper‐Limb Motoneurons With Epidural Electrical Stimulation of the Cervical Spinal Cord.” Nature Communications 12, no. 1: 435. https://doi.org/10.1038/s41467‐020‐20703‐1.
Grijalva‐Otero, I., and E. Doncel‐Pérez. 2024. “Traumatic Human Spinal Cord Injury: Are Single Treatments Enough to Solve the Problem?” Archives of Medical Research 55, no. 1: 102935. https://doi.org/10.1016/j.arcmed.2023.102935.
Guan, S., H. Tian, Y. Yang, et al. 2023. “Self‐Assembled Ultraflexible Probes for Long‐Term Neural Recordings and Neuromodulation.” Nature Protocols 18, no. 6: 1712–1744. https://doi.org/10.1038/s41596‐023‐00824‐9.
Guerreiro Fernandes, F., M. Raemaekers, Z. Freudenburg, and N. Ramsey. 2024. “Considerations for Implanting Speech Brain Computer Interfaces Based on Functional Magnetic Resonance Imaging.” Journal of Neural Engineering 21, no. 3: 036005. https://doi.org/10.1088/1741‐2552/ad4178.
Guttmann‐Flury, E., X. Sheng, and X. Zhu. 2023. “Channel Selection From Source Localization: A Review of Four EEG‐Based Brain‐Computer Interfaces Paradigms.” Behavior Research Methods 55, no. 4: 1980–2003. https://doi.org/10.3758/s13428‐022‐01897‐2.
Habelt, B., C. Wirth, D. Afanasenkau, et al. 2021. “A Multimodal Neuroprosthetic Interface to Record, Modulate and Classify Electrophysiological Biomarkers Relevant to Neuropsychiatric Disorders.” Frontiers in Bioengineering and Biotechnology 9: 770274. https://doi.org/10.3389/fbioe.2021.770274.
Håkansson, S., M. Tuci, M. Bolliger, A. Curt, C. R. Jutzeler, and S. C. Brüningk. 2024. “Data‐Driven Prediction of Spinal Cord Injury Recovery: An Exploration of Current Status and Future Perspectives.” Experimental Neurology 380: 114913. https://doi.org/10.1016/j.expneurol.2024.114913.
Han, X., M. Zhang, L. Yan, et al. 2024. “Role of Dendritic Cells in Spinal Cord Injury.” CNS Neuroscience & Therapeutics 30, no. 3: e14593. https://doi.org/10.1111/cns.14593.
Herbert, C. 2023. “Analyzing and Computing Humans by Means of the Brain Using Brain‐Computer Interfaces—Understanding the User—Previous Evidence, Self‐relevance and the User's Self‐Concept as Potential Superordinate Human Factors of Relevance.” Frontiers in Human Neuroscience 17: 1286895. https://doi.org/10.3389/fnhum.2023.1286895.
Herring, E. Z., E. L. Graczyk, W. D. Memberg, et al. 2024. “Reconnecting the Hand and Arm to the Brain: Efficacy of Neural Interfaces for Sensorimotor Restoration After Tetraplegia.” Neurosurgery 94, no. 4: 864–874. https://doi.org/10.1227/neu.0000000000002769.
Hofmann, U. G., and T. Stieglitz. 2024. “Why Some BCI Should Still Be Called BMI.” Nature Communications 15, no. 1: 6207. https://doi.org/10.1038/s41467‐024‐50603‐7.
Hu, Z., Z. Zhou, and H. Lyu. 2025. “A Power‐and‐Area‐Efficient Channel‐Interleaved Neural Signal Processor for Wireless Brain‐Computer Interfaces with Unsupervised Spike Sorting.” IEEE Transactions on Biomedical Circuits and Systems 19, no. 1: 108–119. https://doi.org/10.1109/tbcas.2024.3395353.
Huang, C., N. Shi, Y. Miao, X. Chen, Y. Wang, and X. Gao. 2024. “Visual tracking brain‐computer interface.” iScience 27, no. 4: 109376. https://doi.org/10.1016/j.isci.2024.109376.
Huo, C., G. Xu, H. Xie, et al. 2024. “Functional Near‐Infrared Spectroscopy in Non‐Invasive Neuromodulation.” Neural Regeneration Research 19, no. 7: 1517–1522. https://doi.org/10.4103/1673‐5374.387970.
Jervis‐Rademeyer, H., K. Ong, A. Djuric, S. Munce, K. E. Musselman, and C. Marquez‐Chin. 2022. “Therapists' Perspectives on Using Brain–Computer Interface‐Triggered Functional Electrical Stimulation Therapy for Individuals Living with Upper Extremity Paralysis: A Qualitative Case Series Study.” Journal of Neuroengineering and Rehabilitation 19, no. 1: 127. https://doi.org/10.1186/s12984‐022‐01107‐2.
Jiang, H., R. Wang, Z. Zheng, et al. 2022. “Short Report: Surgery for Implantable Brain–Computer Interface Assisted by Robotic Navigation System.” Acta Neurochirurgica 164, no. 9: 2299–2302. https://doi.org/10.1007/s00701‐022‐05235‐5.
Jovanovic, L. I., M. R. Popovic, and C. Marquez‐Chin. 2022. “Characterizing the Stimulation Interference in Electroencephalographic Signals During Brain–Computer Interface‐Controlled Functional Electrical Stimulation Therapy.” Artificial Organs 46, no. 3: 398–411. https://doi.org/10.1111/aor.14059.
Keough, J. R., B. Irvine, D. Kelly, et al. 2024. “Fatigue in Children Using Motor Imagery and P300 Brain–Computer Interfaces.” Journal of Neuroengineering and Rehabilitation 21, no. 1: 61. https://doi.org/10.1186/s12984‐024‐01349‐2.
Keyl, P., M. Schneiders, C. Schuld, et al. 2018. “Differences in Characteristics of Error‐Related Potentials Between Individuals With Spinal Cord Injury and Age‐ and Sex‐Matched Able‐Bodied Controls.” Frontiers in Neurology 9: 1192. https://doi.org/10.3389/fneur.2018.01192.
Lazarou, I., S. Nikolopoulos, K. Georgiadis, V. P. Oikonomou, A. Mariakaki, and I. Kompatsiaris. 2022. “Exploring the Connection of Brain Computer Interfaces and Multimedia Use With the Social Integration of People With Various Motor Disabilities: A Questionnaire‐Based Usability Study.” Frontiers in Digital Health 4: 846963. https://doi.org/10.3389/fdgth.2022.846963.
Letourneau, S., E. T. Zewdie, Z. Jadavji, J. Andersen, L. M. Burkholder, and A. Kirton. 2020. “Clinician Awareness of Brain Computer Interfaces: A Canadian National Survey.” Journal of Neuroengineering and Rehabilitation 17, no. 1: 2. https://doi.org/10.1186/s12984‐019‐0624‐7.
Levett, J. J., L. M. Elkaim, F. Niazi, et al. 2024. “Invasive Brain Computer Interface for Motor Restoration in Spinal Cord Injury: A Systematic Review.” Neuromodulation 27, no. 4: 597–603. https://doi.org/10.1016/j.neurom.2023.10.006.
Li, H., M. Liu, X. Yu, et al. 2022. “Coherence Based Graph Convolution Network for Motor Imagery‐Induced EEG After Spinal Cord Injury.” Frontiers in Neuroscience 16: 1097660. https://doi.org/10.3389/fnins.2022.1097660.
Li, Y., Y. Hu, I. Pozzato, et al. 2024. “Efficacy of Interventions to Improve Cognitive Function in Adults With Spinal Cord Injury: A Systematic Review.” Journal of Neurotrauma 41: 2075–2088. https://doi.org/10.1089/neu.2024.0032.
Lin, S., J. Jiang, K. Huang, et al. 2023. “Advanced Electrode Technologies for Noninvasive Brain–Computer Interfaces.” ACS Nano 17, no. 24: 24487–24513. https://doi.org/10.1021/acsnano.3c06781.
Liu, J., R. Wang, Y. Yang, et al. 2024. “Convolutional Transformer‐Based Cross Subject Model for SSVEP‐Based BCI Classification.” IEEE Journal of Biomedical and Health Informatics 28: 6581–6593. https://doi.org/10.1109/jbhi.2024.3454158.
Liu, L., J. Li, R. Ouyang, et al. 2024. “Multimodal Brain‐Controlled System for Rehabilitation Training: Combining Asynchronous Online Brain‐Computer Interface and Exoskeleton.” Journal of Neuroscience Methods 406: 110132. https://doi.org/10.1016/j.jneumeth.2024.110132.
Lopes‐Dias, C., A. I. Sburlea, K. Breitegger, et al. 2021. “Online Asynchronous Detection of Error‐Related Potentials in Participants with a Spinal Cord Injury Using a Generic Classifier.” Journal of Neural Engineering 18, no. 4: 046022. https://doi.org/10.1088/1741‐2552/abd1eb.
Madigan, C. D., J. A. King, C. Taylor, et al. 2024. “A Systematic Review and Qualitative Synthesis of Weight Management Interventions for People With Spinal Cord Injury.” Obesity Reviews 25, no. 9: e13785. https://doi.org/10.1111/obr.13785.
McGeady, C., A. Vučković, Y. P. Zheng, and M. Alam. 2021. “EEG Monitoring Is Feasible and Reliable During Simultaneous Transcutaneous Electrical Spinal Cord Stimulation.” Sensors (Basel) 21, no. 19: 6593. https://doi.org/10.3390/s21196593.
Mirzabagherian, H., M. B. Menhaj, A. A. Suratgar, N. Talebi, M. R. Abbasi Sardari, and A. Sajedin. 2023. “Temporal‐Spatial Convolutional Residual Network for Decoding Attempted Movement Related EEG Signals of Subjects With Spinal Cord Injury.” Computers in Biology and Medicine 164: 107159. https://doi.org/10.1016/j.compbiomed.2023.107159.
Nakatani, S., N. Araki, T. Hoshino, O. Fukayama, and K. Mabuchi. 2021. “Brain‐Controlled Cycling System for Rehabilitation Following Paraplegia with Delay‐Time Prediction.” Journal of Neural Engineering 18, no. 1: 016022. https://doi.org/10.1088/1741‐2552/abd1bf.
Nann, M., N. Peekhaus, C. Angerhöfer, and S. R. Soekadar. 2020. “Feasibility and Safety of Bilateral Hybrid EEG/EOG Brain/Neural‐Machine Interaction.” Frontiers in Human Neuroscience 14: 580105. https://doi.org/10.3389/fnhum.2020.580105.
Naseer, N., I. K. Niazi, and H. Santosa. 2024. “Editorial: Signal Processing for Brain–Computer Interfaces—Special Issue.” Sensors (Basel) 24, no. 4: 1201. https://doi.org/10.3390/s24041201.
Neumann, W. J. 2024. “Cortical Brain Signals Improve Decoding of Movement and Tremor for Clinical Brain Computer Interfaces.” Clinical Neurophysiology 157: 143–145. https://doi.org/10.1016/j.clinph.2023.11.017.
Nicolelis, M. A. L., E. J. L. Alho, A. R. C. Donati, et al. 2022. “Training With Noninvasive Brain‐Machine Interface, Tactile Feedback, and Locomotion to Enhance Neurological Recovery in Individuals With Complete Paraplegia: A Randomized Pilot Study.” Scientific Reports 12, no. 1: 20545. https://doi.org/10.1038/s41598‐022‐24864‐5.
Ownsworth, T., H. Mols, J. O'Loghlen, et al. 2024. “Stigma Following Acquired Brain Injury and Spinal Cord Injury: Relationship to Psychological Distress and Community Integration in the First‐Year Post‐Discharge.” Disability and Rehabilitation 46, no. 9: 1796–1806. https://doi.org/10.1080/09638288.2023.2205173.
Oxley, T. J., N. L. Opie, S. E. John, et al. 2016. “Minimally Invasive Endovascular Stent‐Electrode Array for High‐Fidelity, Chronic Recordings of Cortical Neural Activity.” Nature Biotechnology 34, no. 3: 320–327. https://doi.org/10.1038/nbt.3428.
Pais‐Vieira, C., J. G. Figueiredo, A. Perrotta, et al. 2024. “Activation of a Rhythmic Lower Limb Movement Pattern During the Use of a Multimodal Brain–Computer Interface: A Case Study of a Clinically Complete Spinal Cord Injury.” Life (Basel) 14, no. 3: 396. https://doi.org/10.3390/life14030396.
Pais‐Vieira, C., P. Gaspar, D. Matos, et al. 2022. “Embodiment Comfort Levels During Motor Imagery Training Combined With Immersive Virtual Reality in a Spinal Cord Injury Patient.” Frontiers in Human Neuroscience 16: 909112. https://doi.org/10.3389/fnhum.2022.909112.
Pancholi, S., J. P. Wachs, and B. S. Duerstock. 2024. “Use of Artificial Intelligence Techniques to Assist Individuals with Physical Disabilities.” Annual Review of Biomedical Engineering 26, no. 1: 1–24. https://doi.org/10.1146/annurev‐bioeng‐082222‐012531.
Perna, A., G. N. Angotzi, L. Berdondini, and J. F. Ribeiro. 2023. “Advancing the Interfacing Performances of Chronically Implantable Neural Probes in the Era of CMOS Neuroelectronics.” Frontiers in Neuroscience 17: 1275908. https://doi.org/10.3389/fnins.2023.1275908.
Pfeffer, M. A., S. S. H. Ling, and J. K. W. Wong. 2024. “Exploring the Frontier: Transformer‐Based Models in EEG Signal Analysis for Brain–Computer Interfaces.” Computers in Biology and Medicine 178: 108705. https://doi.org/10.1016/j.compbiomed.2024.108705.
Rubin, D. B., A. B. Ajiboye, L. Barefoot, et al. 2023. “Interim Safety Profile From the Feasibility Study of the BrainGate Neural Interface System.” Neurology 100, no. 11: e1177–e1192. https://doi.org/10.1212/wnl.0000000000201707.
Rubin, D. B., T. Hosman, J. N. Kelemen, et al. 2022. “Learned Motor Patterns Are Replayed in Human Motor Cortex During Sleep.” Journal of Neuroscience 42, no. 25: 5007–5020. https://doi.org/10.1523/jneurosci.2074‐21.2022.
Samejima, S., A. Khorasani, V. Ranganathan, et al. 2021. “Brain–Computer‐Spinal Interface Restores Upper Limb Function After Spinal Cord Injury.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 29: 1233–1242. https://doi.org/10.1109/tnsre.2021.3090269.
Saway, B. F., C. Palmer, C. Hughes, et al. 2024. “The Evolution of Neuromodulation for Chronic Stroke: From Neuroplasticity Mechanisms to Brain‐Computer Interfaces.” Neurotherapeutics 21, no. 3: e00337. https://doi.org/10.1016/j.neurot.2024.e00337.
Shen, K., O. Chen, J. L. Edmunds, D. K. Piech, and M. M. Maharbiz. 2023. “Translational Opportunities and Challenges of Invasive Electrodes for Neural Interfaces.” Nature Biomedical Engineering 7, no. 4: 424–442. https://doi.org/10.1038/s41551‐023‐01021‐5.
Shen, X., T. Sun, Z. Li, and Y. Wu. 2023. “Generation of Locomotor‐Like Activity Using Monopolar Intraspinal Electrical Microstimulation in Rats.” Experimental and Therapeutic Medicine 26, no. 6: 560. https://doi.org/10.3892/etm.2023.12259.
Shokur, S., A. R. C. Donati, D. S. F. Campos, et al. 2018. “Training With Brain‐Machine Interfaces, Visuo‐Tactile Feedback and Assisted Locomotion Improves Sensorimotor, Visceral, and Psychological Signs in Chronic Paraplegic Patients.” PLoS ONE 13, no. 11: e0206464. https://doi.org/10.1371/journal.pone.0206464.
Sieghartsleitner, S., M. Sebastián‐Romagosa, W. Cho, et al. 2024. “Upper Extremity Training Followed by Lower Extremity Training with a Brain–Computer Interface Rehabilitation System.” Frontiers in Neuroscience 18: 1346607. https://doi.org/10.3389/fnins.2024.1346607.
Song, M., D. Gwon, S. C. Jun, and M. Ahn. 2024. “Signal Alignment for Cross‐Datasets in P300 Brain–Computer Interfaces.” Journal of Neural Engineering 21, no. 3: 036007. https://doi.org/10.1088/1741‐2552/ad430d.
Steele, A. G., G. A. Manson, P. J. Horner, D. G. Sayenko, and J. L. Contreras‐Vidal. 2022. “Effects of Transcutaneous Spinal Stimulation on Spatiotemporal Cortical Activation Patterns: A Proof‐Of‐Concept EEG Study.” Journal of Neural Engineering 19, no. 4: 046001. https://doi.org/10.1088/1741‐2552/ac7b4b.
Valencia, D., G. Leone, N. Keller, P. P. Mercier, and A. Alimohammad. 2023. “Power‐Efficientin Vivobrain‐Machine Interfaces via Brain‐State Estimation.” Journal of Neural Engineering 20, no. 1: 016032. https://doi.org/10.1088/1741‐2552/acb385.
Van de Wauw, C., L. Riecke, R. Goebel, A. Kaas, and B. Sorger. 2023. “Talking With Hands and Feet: Selective Somatosensory Attention and fMRI Enable Robust and Convenient Brain‐Based Communication.” NeuroImage 276: 120172. https://doi.org/10.1016/j.neuroimage.2023.120172.
Vansteensel, M. J., E. Klein, G. van Thiel, et al. 2023. “Towards Clinical Application of Implantable Brain–Computer Interfaces for People With Late‐Stage ALS: Medical and Ethical Considerations.” Journal of Neurology 270, no. 3: 1323–1336. https://doi.org/10.1007/s00415‐022‐11464‐6.
Várkuti, B., L. Halász, S. Hagh Gooie, et al. 2024. “Conversion of a Medical Implant Into a Versatile Computer–Brain Interface.” Brain Stimulation 17, no. 1: 39–48. https://doi.org/10.1016/j.brs.2023.12.011.
Vincent, C., F. S. Dumont, M. Rogers, et al. 2024. “Perspectives of Wheelchair Users with Chronic Spinal Cord Injury Following a Walking Program Using a Wearable Robotic Exoskeleton.” Disability and Rehabilitation 46: 1–9. https://doi.org/10.1080/09638288.2024.2317994.
Vorreuther, A., L. Bastian, A. Benitez Andonegui, et al. 2023. “It Takes Two (Seconds): Decreasing Encoding Time for Two‐Choice Functional Near‐Infrared Spectroscopy Brain‐Computer Interface Communication.” Neurophotonics 10, no. 4: 045005. https://doi.org/10.1117/1.NPh.10.4.045005.
Wan, C., M. Pei, K. Shi, et al. 2024. “Toward a Brain–Neuromorphics Interface.” Advanced Materials 36: e2311288. https://doi.org/10.1002/adma.202311288.
Wang, J., T. Wang, H. Liu, et al. 2023. “Flexible Electrodes for Brain–Computer Interface System.” Advanced Materials 35, no. 47: e2211012. https://doi.org/10.1002/adma.202211012.
Wang, R., and J. Bai. 2024. “Pharmacological Interventions Targeting the Microcirculation Following Traumatic Spinal Cord Injury.” Neural Regeneration Research 19, no. 1: 35–42. https://doi.org/10.4103/1673‐5374.375304.
Wang, T., G. Huang, Z. Yi, S. Dai, W. Zhuang, and S. Guo. 2024. “Advances in Extracellular Vesicle‐Based Combination Therapies for Spinal Cord Injury.” Neural Regeneration Research 19, no. 2: 369–374. https://doi.org/10.4103/1673‐5374.377413.
Wang, Y., X. Yang, X. Zhang, Y. Wang, and W. Pei. 2023. “Implantable Intracortical Microelectrodes: Reviewing the Present with a Focus on the Future.” Microsystems & Nanoengineering 9: 7. https://doi.org/10.1038/s41378‐022‐00451‐6.
Wang, Z., S. Li, J. Luo, J. Liu, and D. Wu. 2024. “Channel Reflection: Knowledge‐Driven Data Augmentation for EEG‐Based Brain–Computer Interfaces.” Neural Networks 176: 106351. https://doi.org/10.1016/j.neunet.2024.106351.
Webster, P. 2024. “The Future of Brain–Computer Interfaces in Medicine.” Nature Medicine 30, no. 6: 1508–1509. https://doi.org/10.1038/d41591‐024‐00031‐3.
Wen, D., Y. Fan, S. H. Hsu, et al. 2021. “Combining Brain–Computer Interface and Virtual Reality for Rehabilitation in Neurological Diseases: A Narrative Review.” Annals of Physical and Rehabilitation Medicine 64, no. 1: 101404. https://doi.org/10.1016/j.rehab.2020.03.015.
Willett, F. R., D. T. Avansino, L. R. Hochberg, J. M. Henderson, and K. V. Shenoy. 2021. “High‐Performance Brain‐to‐Text Communication via Handwriting.” Nature 593, no. 7858: 249–254. https://doi.org/10.1038/s41586‐021‐03506‐2.
Wu, H., S. Li, and D. Wu. 2024. “Motor Imagery Classification for Asynchronous EEG‐Based Brain–Computer Interfaces.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 32: 527–536. https://doi.org/10.1109/tnsre.2024.3356916.
Wu, X., B. Metcalfe, S. He, H. Tan, and D. Zhang. 2024. “A Review of Motor Brain–Computer Interfaces Using Intracranial Electroencephalography Based on Surface Electrodes and Depth Electrodes.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 32: 2408–2431. https://doi.org/10.1109/tnsre.2024.3421551.
Xu, F., J. Li, G. Dong, et al. 2022. “EEG Decoding Method Based on Multi‐Feature Information Fusion for Spinal Cord Injury.” Neural Networks 156: 135–151. https://doi.org/10.1016/j.neunet.2022.09.016.
Xu, F., C. Wang, X. Yu, et al. 2023. “One‐Dimensional Local Binary Pattern and Common Spatial Pattern Feature Fusion Brain Network for Central Neuropathic Pain.” International Journal of Neural Systems 33, no. 6: 2350030. https://doi.org/10.1142/s0129065723500302.
Xu, X., R. Liu, Y. Li, et al. 2024. “Spinal Cord Injury: From MicroRNAs to Exosomal MicroRNAs.” Molecular Neurobiology 61, no. 8: 5974–5991. https://doi.org/10.1007/s12035‐024‐03954‐7.
Yakovlev, L., N. Syrov, and A. Kaplan. 2023. “Investigating the Influence of Functional Electrical Stimulation on Motor Imagery Related μ‐Rhythm Suppression.” Frontiers in Neuroscience 17: 1202951. https://doi.org/10.3389/fnins.2023.1202951.
Yang, S. H., C. J. Huang, and J. S. Huang. 2024. “Increasing Robustness of Intracortical Brain–Computer Interfaces for Recording Condition Changes via Data Augmentation.” Computer Methods and Programs in Biomedicine 251: 108208. https://doi.org/10.1016/j.cmpb.2024.108208.
Yang, Y., S. Luo, W. Wang, X. Gao, X. Yao, and T. Wu. 2024. “From Bench to Bedside: Overview of Magnetoencephalography in Basic Principle, Signal Processing, Source Localization and Clinical Applications.” NeuroImage: Clinical 42: 103608. https://doi.org/10.1016/j.nicl.2024.103608.
Yeom, H. G., J. S. Kim, and C. K. Chung. 2023. “A Magnetoencephalography Dataset During Three‐Dimensional Reaching Movements for Brain–Computer Interfaces.” Scientific Data 10, no. 1: 552. https://doi.org/10.1038/s41597‐023‐02454‐y.
Yin, Z., B. Wan, G. Gong, and J. Yin. 2024. “ROS: Executioner of Regulating Cell Death in Spinal Cord Injury.” Frontiers in Immunology 15: 1330678. https://doi.org/10.3389/fimmu.2024.1330678.
Young, D., F. Willett, W. D. Memberg, et al. 2018. “Signal Processing Methods for Reducing Artifacts in Microelectrode Brain Recordings Caused by Functional Electrical Stimulation.” Journal of Neural Engineering 15, no. 2: 026014. https://doi.org/10.1088/1741‐2552/aa9ee8.
Zeller, S. L., A. Stein, I. Frid, et al. 2024. “Critical Care of Spinal Cord Injury.” Current Neurology and Neuroscience Reports 24: 355–363. https://doi.org/10.1007/s11910‐024‐01357‐8.
Zhang, H., L. Jiao, S. Yang, et al. 2024. “Brain–Computer Interfaces: The Innovative Key to Unlocking Neurological Conditions.” International Journal of Surgery 110, no. 9: 5745–5762. https://doi.org/10.1097/js9.0000000000002022.
Zhou, K., W. Wei, D. Yang, et al. 2024. “Dual Electrical Stimulation at Spinal‐Muscular Interface Reconstructs Spinal Sensorimotor Circuits After Spinal Cord Injury.” Nature Communications 15, no. 1: 619. https://doi.org/10.1038/s41467‐024‐44898‐9.
Ziai, Y., S. S. Zargarian, C. Rinoldi, et al. 2023. “Conducting Polymer‐Based Nanostructured Materials for Brain–Machine Interfaces.” Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology 15, no. 5: e1895. https://doi.org/10.1002/wnan.1895.
Zulauf‐Czaja, A., M. K. H. Al‐Taleb, M. Purcell, N. Petric‐Gray, J. Cloughley, and A. Vuckovic. 2021. “On the Way Home: A BCI‐FES Hand Therapy Self‐Managed by Sub‐Acute SCI Participants and Their Caregivers: A Usability Study.” Journal of Neuroengineering and Rehabilitation 18, no. 1: 44. https://doi.org/10.1186/s12984‐021‐00838‐y.
Grant Information:
2023TSYCLJ0031 Program of Technological Leading Talent of Tianshan Talent; 2023YFY-QKMS-06 Youth Foundation of Research and Development; 2021D01D18 Key Program of Natural Science Foundation of Xinjiang Uygur Autonomous Region; 82360257 National Natural Science Foundation of China
Contributed Indexing:
Keywords: brain–computer interfaces; motor function; neurorehabilitation; spinal cord injury
Entry Date(s):
Date Created: 20250708 Date Completed: 20250708 Latest Revision: 20250708
Update Code:
20250708
DOI:
10.1111/ejn.70183
PMID:
40624803
Database:
MEDLINE
Weitere Informationen
The current treatment regimen for spinal cord injury (SCI), a neurological disorder with a high incidence of disability, is based on early surgical decompression and administration of pharmacological agents. However, the efficacy of such an approach remains limited, and most patients have sensory and functional deficits below the level of injury, which seriously affects their quality of life. This necessitates further exploration into effective treatment modalities. In recent years, considerable advancements have been made in developing and utilizing brain-computer interfaces (BCI), which facilitate neurorehabilitation and enhance motor function by transforming brain signals into diverse forms of output commands. BCI-assisted systems provide alternative means of rehabilitative exercise or limb movement in patients with SCI, including electrical stimulation and exoskeleton robots. BCI shows great potential in the rehabilitation of patients with SCI. This review summarizes the current research status and limitations of BCI for SCI to provide novel insights into the concept of multimodal rehabilitation and treatment of SCI and facilitate BCI's future development.
(© 2025 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)