International Journal For Multidisciplinary Research

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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 4 July-August 2024 Submit your research before last 3 days of August to publish your research paper in the issue of July-August.

Sleep Spindles using Electroencephalography signals

Author(s) Anchal Agrawal, Raghavendra Prasad
Country India
Abstract EEG stands for electroencephalography. It is a non-invasive neurophysiological technique that and amplify the tiny electrical signals produced by neurons. A medical imaging method called electroencephalography measures the electrical activity in the scalp that is produced by brain regions (Teplan, 2002). Short oscillations known as sleep spindles can be seen in the human electroencephalogram (EEG) when a person is sleepy or drowsy (Lüthi, 2014). Neither the topography nor the morphology of sleep spindles remains constant throughout the lifespan (Clawson et al., 2016). Sleep spindles frequency range is between 12 Hz and 14 Hz. This frequency was extended to 11 Hz to 16 Hz after the American Academy of Sleep Medicine (AASM) published a new version of their sleep scoring guidelines in 2002 [37,16,15,43,23] One of the two primary sleep cycles that comprise a full sleep cycle is called NREM (Non-Rapid Eye Movement), the other being REM (Rapid Eye Movement) sleep. There are three stages of NREM sleep: N1, N2, and N3 (Al-Salman et al., 2019). With a sensitivity ranging from 89.1% to 100%, deep learning techniques have been developed to detect sleep spindles using 11 to 30 adult sleep EEGs
Keywords Sleep Spindles, electroencephalography (EEG), Non Rapid Eye Movement( NREM)
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-29
Cite This Sleep Spindles using Electroencephalography signals - Anchal Agrawal, Raghavendra Prasad - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.18221
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.18221
Short DOI https://doi.org/gtsnwr

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