Review Article

, 20 Oct 2026 | 10.62346/ijbsip_v13_q2_26_01
Year : 2026 | Volume: 13 | Issue: 2 | Pages : 1-6

The Intersection of EEG Technology and Brain-Computer Interfaces in Medicine: A Review

  • 1Anna University, Chennai, Department of ECE, K. Ramakrishnan college of engineering, Tamilnadu, IN
  • 2Anna University, Chennai, Students, Department of ECE, K. Ramakrishnan college of Engineering, Tamilnadu, IN
  • 3Anna University, Chennai, Students, Department of ECE, K. Ramakrishnan college of Engineering, Tamilnadu, IN
  • 4Anna University, Chennai, Students, Department of ECE, K. Ramakrishnan college of Engineering, Tamilnadu, IN
  • 5Anna University, Chennai, Students, Department of ECE, K. Ramakrishnan college of Engineering, Tamilnadu, IN
Brain-computer interfaces (BCIs) that read electroencephalography (EEG) give people a way to control external devices with brain activity alone and without surgery. Over the past two decades the most active medical use of this idea has been stroke rehabilitation, where a BCI can reward a patient for imagining or attempting a movement that the paralysed limb cannot yet perform. This paper reviews the field with that application in mind. We describe how an EEG-based BCI is built, from signal acquisition and artifact removal to feature extraction and classification, and we compare the three training approaches used most often after stroke: motor imagery, movement attempt and sensorimotor-rhythm neurofeedback. We then summarise other clinical uses, including communication for people who are locked in, detection of awareness in disorders of consciousness, and EEG- based seizure detection. Controlled studies and meta-analyses suggest that BCI-assisted therapy can improve upper-limb function, but the trials are small and the benefit differs a great deal from one person to the next. we conclude with the practical hurdles to clinical implementation and the pathways that appear most promising: hybrid systems, adaptive decoders and home training.

Conclusion

It was decades later, however, before EEG BCIs became testable in a clinical setting and stroke rehabilitation is where most of the results are now emerging. The principle of motor imagery training, attempts at movement and sensorimotor rhythm training is identical to what is seen in the laboratory: the brain activity needs to be coupled with the appropriate feedback, and in controlled experiments, it can be useful to certain patients in improving their upper limb functions. There is little evidence thus far, but: the trials have been small, the outcomes can vary depending on the patient and there has been no conclusive evidence about the extent of the BCI's contribution to the outcome. It will all depend on developing user-friendly devices, adaptive decoders and accurate reporting of the trials. In such a scenario, BCIs could well become a regular part of rehabilitation and speech therapy.

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Keywords: Brain-computer interface, electroencephalography, stroke rehabilitation, motor imagery, neuroplasticity, neurofeedback, assistive technology

Citation: Bala Kumar A*,Bala Kumar A ( 2026), The Intersection of EEG Technology and Brain-Computer Interfaces in Medicine: A Review. , 13(2): 1-6

Received: 10/06/2026; Accepted: 30/06/2026;
Published: 30/06/2026

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*Correspondence: Bala Kumar A, balakumar2712@gmail.com


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