Authors : Harsha S. Krishna; Salama Pulikkal

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://tinyurl.com/2vmz78km

Scribd : https://tinyurl.com/y6d976uw

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG1536

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The brain-computer interface technology allows the human brain to control external devices directly without using the brain’s output channels or peripheral nerves. It helps individuals with motor impairments to use mechanical and external devices to communicate with the outside world. Non-invasive BCIs allow communication between the human brain and external devices without the need for surgeries or invasive procedures. Methods like EEG, MEG, fMRI, and fNIRS are used. EEG enables the acquisition of electrical activity along the scalp by measuring voltage fluctuations and neurotransmission activity in the brain. The electrodes are attached to a cap-like device and are placed on the scalp to record the electrical current generated by the brain. Unlike MEG, which necessitates specially constructed rooms, EEG is portable. Lab-grade EEG is expensive but cheaper than other forms of BCI. MEG uses magnetometers to measure magnetic fields produced by electric currents occurring naturally in the brain. MEG is better than EEG at measuring high-frequency activity. MEG signals are less distorted by the skull layer. FMRI records blood oxygen level-dependent (BOLD) signals with high spatial resolution across the entire brain. It does this by tracking the hemodynamic response, which is the increase in blood flow to active brain areas. It does this using the principle of nuclear magnetic resonance, where hydrogen atoms in water molecules in the blood emit signals when subjected to a strong magnetic field. It has an advantage over EEG due to its superior spatial specificity and resolution. FNIRS measures the blood flow and oxygenation in the blood associated with neural activity. It gains insight into the brain's hemodynamic response, which is essential for understanding neural functioning during BCI tasks.

Keywords : Brain-Computer Interface; Non-Inasive; EEG; MEG; Fmri; Fnirs;

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