A nature-inspired biomarker for mental concentration using a single-channel EEG

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10245016" target="_blank" >RIV/61989100:27240/20:10245016 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007%2Fs00521-019-04574-2" target="_blank" >https://link.springer.com/article/10.1007%2Fs00521-019-04574-2</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00521-019-04574-2" target="_blank" >10.1007/s00521-019-04574-2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A nature-inspired biomarker for mental concentration using a single-channel EEG

Popis výsledku v původním jazyce

We developed a system for measuring the attentional process during the performance of specific activities. The proposed biomarker device is able to estimate the mental concentration using a single-channel EEG. The system captures the EEG signal and several brain waves located in the left orbitofrontal brain region. Furthermore, we extended the input features of the system applying spectrum analysis. We applied two well-known evolutionary algorithms for selecting the best combination of input features: simulated annealing and geometric particle swarm optimization. Besides, we solved the binary classification problem (concentration vs. relaxation) using support vector machines and neural networks. Support vector machines are among the most common instruments for solving binary classification problems. On the other hand, we selected to study a family of neural networks named echo state networks, because the model is ideal for embedded systems and has shown good accuracy in real-world applications. The training and execution are fast, robust, and reliable. The developed system is autonomous, portable, reliable, non-invasive and has a low economic cost. Besides, it can be easily adjusted for each person and for each problem. (C) 2019, Springer-Verlag London Ltd., part of Springer Nature.

Název v anglickém jazyce

A nature-inspired biomarker for mental concentration using a single-channel EEG

Popis výsledku anglicky

We developed a system for measuring the attentional process during the performance of specific activities. The proposed biomarker device is able to estimate the mental concentration using a single-channel EEG. The system captures the EEG signal and several brain waves located in the left orbitofrontal brain region. Furthermore, we extended the input features of the system applying spectrum analysis. We applied two well-known evolutionary algorithms for selecting the best combination of input features: simulated annealing and geometric particle swarm optimization. Besides, we solved the binary classification problem (concentration vs. relaxation) using support vector machines and neural networks. Support vector machines are among the most common instruments for solving binary classification problems. On the other hand, we selected to study a family of neural networks named echo state networks, because the model is ideal for embedded systems and has shown good accuracy in real-world applications. The training and execution are fast, robust, and reliable. The developed system is autonomous, portable, reliable, non-invasive and has a low economic cost. Besides, it can be easily adjusted for each person and for each problem. (C) 2019, Springer-Verlag London Ltd., part of Springer Nature.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

Neural Computing and Applications

ISSN

0941-0643

e-ISSN

—

Svazek periodika

32

Číslo periodika v rámci svazku

12

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

16

Strana od-do

7941-7956

Kód UT WoS článku

000493504900001

EID výsledku v databázi Scopus

2-s2.0-85074711492