TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Brainwave-based Mood Classification Using Regularized Common Spatial Pattern Filter |
| 영문제목(English Title) |
Brainwave-based Mood Classification Using Regularized Common Spatial Pattern Filter |
| 저자(Author) |
Saim Shin
Sei-Jin Jang
Donghyun Lee
Unsang Park
Ji-Hwan Kim
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| 원문수록처(Citation) |
VOL 10 NO. 02 PP. 0807 ~ 0824 (2016. 02) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
In this paper, a method of mood classification based on user brainwaves is proposed for real-time application in commercial services. Unlike conventional mood analyzing systems, the proposed method focuses on classifying real-time user moods by analyzing the user’s brainwaves. Applying brainwave-related research in commercial services requires two elements - robust performance and comfortable fit of.
This paper proposes a filter based on Regularized Common Spatial Patterns (RCSP) and presents its use in the implementation of mood classification for a music service via a wireless consumer electroencephalography (EEG) device that has only 14 pins. Despite the use of fewer pins, the proposed system demonstrates approximately 10% point higher accuracy in mood classification, using the same dataset, compared to one of the best EEG-based mood-classification systems using a skullcap with 32 pins (EU FP7 PetaMedia project). This paper confirms the commercial viability of brainwave-based mood-classification technology.
To analyze the improvements of the system, the changes of feature variations after applying RCSP filters and performance variations between users are also investigated. Furthermore, as a prototype service, this paper introduces a mood-based music list management system called MyMusicShuffler based on the proposed mood-classification method.
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| 키워드(Keyword) |
Mood classification
Electroencephalography(EEG)
Regularized Common Spatial Patterns
Spatial filter
mood-based music services
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| 파일첨부 |
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