Analysis of the correlation between the human voice and brain activity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F24%3A50018066" target="_blank" >RIV/62690094:18450/24:50018066 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.tandfonline.com/doi/abs/10.1080/17455030.2021.1921313?journalCode=twrm20" target="_blank" >https://www.tandfonline.com/doi/abs/10.1080/17455030.2021.1921313?journalCode=twrm20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/17455030.2021.1921313" target="_blank" >10.1080/17455030.2021.1921313</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of the correlation between the human voice and brain activity

Popis výsledku v původním jazyce

In this paper, we investigated the coupling among the alterations of brain activity and the rhythmic pattern of voice. We benefited from complexity and information concepts and ran the analysis on EEG and voice (audio) signals using sample entropy and Shannon entropy. To change brain activity, we applied four different odors with different complexities on ten subjects (5 M, 5 F). Accordingly, subjects&apos; voice was changed, and therefore, we evaluated the changes in EEG versus voice signals by calculating their Shannon entropy and sample entropy. The obtained results showed that the variations of complexity (r = 0.8659) and the information content (r = 0.9423) of voice and EEG signals are strongly correlated. This method can be utilized to evaluate the coupling of other biosignals versus brain activity.

Název v anglickém jazyce

Analysis of the correlation between the human voice and brain activity

Popis výsledku anglicky

In this paper, we investigated the coupling among the alterations of brain activity and the rhythmic pattern of voice. We benefited from complexity and information concepts and ran the analysis on EEG and voice (audio) signals using sample entropy and Shannon entropy. To change brain activity, we applied four different odors with different complexities on ten subjects (5 M, 5 F). Accordingly, subjects&apos; voice was changed, and therefore, we evaluated the changes in EEG versus voice signals by calculating their Shannon entropy and sample entropy. The obtained results showed that the variations of complexity (r = 0.8659) and the information content (r = 0.9423) of voice and EEG signals are strongly correlated. This method can be utilized to evaluate the coupling of other biosignals versus brain activity.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Waves in Random and Complex Media

ISSN

1745-5030

e-ISSN

1745-5049

Svazek periodika

34

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

13

Strana od-do

915-927

Kód UT WoS článku

000646445900001

EID výsledku v databázi Scopus

2-s2.0-85105184923