Wireless EAR EEG Signal Analysis with Stationary Wavelet Transform for Co Channel Interference in Schizophrenia Diagnosis

Nithya, V.; Ramesh, G. P.

doi:10.1007/978-3-030-32644-9_27

Cited by 5 publications

(1 citation statement)

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“…For instance, wireless EEGs were used for hyper-scanning two pianists performing a piano duet ( Zamm et al, 2020 ); and wireless systems were used to simultaneously collect physiological activity (e.g., electrocardiogram, facial muscle electromyogram, respiration, heart rates) from whole audiences (∼40 participants per concert) attending live string quintet performances ( Czepiel et al, 2021 ; Merrill et al, 2021 ; Tschacher et al, 2021 ). In particular, the feasibility of a wireless in-ear EEG system has drawn considerable attention ( Looney et al, 2014 ; Bleichner and Emkes, 2020 ; Nithya and Ramesh, 2020 ). A built-in EEG system in everyday devices (e.g., wireless in-ear headphones) might open a new possibility of collecting neural data from millions of people while they listen to their favorite music in their day-to-day lives.…”

Section: Challenges and Perspectivesmentioning

confidence: 99%

On the encoding of natural music in computational models and human brains

Kim

2022

Front. Neurosci.

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This article discusses recent developments and advances in the neuroscience of music to understand the nature of musical emotion. In particular, it highlights how system identification techniques and computational models of music have advanced our understanding of how the human brain processes the textures and structures of music and how the processed information evokes emotions. Musical models relate physical properties of stimuli to internal representations called features, and predictive models relate features to neural or behavioral responses and test their predictions against independent unseen data. The new frameworks do not require orthogonalized stimuli in controlled experiments to establish reproducible knowledge, which has opened up a new wave of naturalistic neuroscience. The current review focuses on how this trend has transformed the domain of the neuroscience of music.

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