Tek Elektrotlu Cihaz ile EEG Sinyallerinden Duygu Tanima

Mehmet Ali Sarikaya; Gokhan Ince

doi:10.1109/SIU.2017.7960390

Tek Elektrotlu Cihaz ile EEG Sinyallerinden Duygu Tanima

Translated title of the contribution: Emotion recognition from EEG signals through one electrode device

Mehmet Ali Sarikaya^*, Gokhan Ince

^*Corresponding author for this work

Department of Computer Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

17 Citations (Scopus)

Abstract

In recent years, researchers have concentrated on the development of ElectroEncephaloGraphy (EEG) based Brain-Computer Interfaces (BCI) to increase the quality of life using medical applications. BCIs can also be used for marketing, gaming, and entertainment to provide users with a more personalized experience. Both medical and non-medical applications require the ability to interpret the user's multimedia-induced perception and emotional experience. This paper presents a novel method to detect human emotion with a single-channel commercial BCI device. The proposed EEG-based emotion recognition system was tested on human test subjects using a deep learning neural network and an accuracy above 87% was achieved.

Translated title of the contribution	Emotion recognition from EEG signals through one electrode device
Original language	Turkish
Title of host publication	2017 25th Signal Processing and Communications Applications Conference, SIU 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509064946
DOIs	https://doi.org/10.1109/SIU.2017.7960390
Publication status	Published - 27 Jun 2017
Event	25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey Duration: 15 May 2017 → 18 May 2017

Publication series

Name	2017 25th Signal Processing and Communications Applications Conference, SIU 2017

Conference

Conference	25th Signal Processing and Communications Applications Conference, SIU 2017
Country/Territory	Turkey
City	Antalya
Period	15/05/17 → 18/05/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Access to Document

10.1109/SIU.2017.7960390

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Sarikaya, M. A., & Ince, G. (2017). Tek Elektrotlu Cihaz ile EEG Sinyallerinden Duygu Tanima. In 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 Article 7960390 (2017 25th Signal Processing and Communications Applications Conference, SIU 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2017.7960390

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title = "Tek Elektrotlu Cihaz ile EEG Sinyallerinden Duygu Tanima",

abstract = "In recent years, researchers have concentrated on the development of ElectroEncephaloGraphy (EEG) based Brain-Computer Interfaces (BCI) to increase the quality of life using medical applications. BCIs can also be used for marketing, gaming, and entertainment to provide users with a more personalized experience. Both medical and non-medical applications require the ability to interpret the user's multimedia-induced perception and emotional experience. This paper presents a novel method to detect human emotion with a single-channel commercial BCI device. The proposed EEG-based emotion recognition system was tested on human test subjects using a deep learning neural network and an accuracy above 87\% was achieved.",

keywords = "Brain-Computer Interfaces, Deep Learning Neural Networks, EEG, Emotion Recognition",

author = "Sarikaya, \{Mehmet Ali\} and Gokhan Ince",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 25th Signal Processing and Communications Applications Conference, SIU 2017 ; Conference date: 15-05-2017 Through 18-05-2017",

year = "2017",

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doi = "10.1109/SIU.2017.7960390",

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Sarikaya, MA & Ince, G 2017, Tek Elektrotlu Cihaz ile EEG Sinyallerinden Duygu Tanima. in 2017 25th Signal Processing and Communications Applications Conference, SIU 2017., 7960390, 2017 25th Signal Processing and Communications Applications Conference, SIU 2017, Institute of Electrical and Electronics Engineers Inc., 25th Signal Processing and Communications Applications Conference, SIU 2017, Antalya, Turkey, 15/05/17. https://doi.org/10.1109/SIU.2017.7960390

Tek Elektrotlu Cihaz ile EEG Sinyallerinden Duygu Tanima. / Sarikaya, Mehmet Ali; Ince, Gokhan.
2017 25th Signal Processing and Communications Applications Conference, SIU 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7960390 (2017 25th Signal Processing and Communications Applications Conference, SIU 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Tek Elektrotlu Cihaz ile EEG Sinyallerinden Duygu Tanima

AU - Sarikaya, Mehmet Ali

AU - Ince, Gokhan

PY - 2017/6/27

Y1 - 2017/6/27

N2 - In recent years, researchers have concentrated on the development of ElectroEncephaloGraphy (EEG) based Brain-Computer Interfaces (BCI) to increase the quality of life using medical applications. BCIs can also be used for marketing, gaming, and entertainment to provide users with a more personalized experience. Both medical and non-medical applications require the ability to interpret the user's multimedia-induced perception and emotional experience. This paper presents a novel method to detect human emotion with a single-channel commercial BCI device. The proposed EEG-based emotion recognition system was tested on human test subjects using a deep learning neural network and an accuracy above 87% was achieved.

AB - In recent years, researchers have concentrated on the development of ElectroEncephaloGraphy (EEG) based Brain-Computer Interfaces (BCI) to increase the quality of life using medical applications. BCIs can also be used for marketing, gaming, and entertainment to provide users with a more personalized experience. Both medical and non-medical applications require the ability to interpret the user's multimedia-induced perception and emotional experience. This paper presents a novel method to detect human emotion with a single-channel commercial BCI device. The proposed EEG-based emotion recognition system was tested on human test subjects using a deep learning neural network and an accuracy above 87% was achieved.

KW - Brain-Computer Interfaces

KW - Deep Learning Neural Networks

KW - EEG

KW - Emotion Recognition

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U2 - 10.1109/SIU.2017.7960390

DO - 10.1109/SIU.2017.7960390

M3 - Konferans katkısı

AN - SCOPUS:85026302539

T3 - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017

BT - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th Signal Processing and Communications Applications Conference, SIU 2017

Y2 - 15 May 2017 through 18 May 2017

ER -

Tek Elektrotlu Cihaz ile EEG Sinyallerinden Duygu Tanima

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