Evaluation of Brain Signal Analysis for Subjective Aesthetic-Appreciation Using Type-2 Fuzzy Sets

被引:0
作者
Das, Madhuparna [1 ]
Debnath, Chandrima [1 ]
Laha, Mousumi [1 ]
Konar, Amit [1 ]
机构
[1] Jadavpur Univ, Elect & Telecommun Engn Dept, Kolkata, India
来源
2020 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS SIGNAL PROCESSING AND NETWORKING (WISPNET) | 2020年
关键词
Aesthetic Appreciation; Electroencephalography (EEG); Type-2 Fuzzy Set; General Type-2 Fuzzy Sets (GT2FS); LOGIC SYSTEMS; EEG-ANALYSIS; EXTRACTION;
D O I
10.1109/wispnet48689.2020.9198628
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The paper presents a notable methodology for automatic classification of aesthetic appraisal levels of various individuals using Electroencephalographic (EEG) signals. A set of visual stimuli containing different facial expressions with varying geometric shapes are utilized for classifying the aesthetic appreciation levels of subjects for three classes: High, Medium, and Low. The brain signals are captured by the EEG system and then fed to the e-LORETA software to determine the highly active brain regions involved to assess the aesthetic appreciation levels. Experiment undertaken infers the activation level of Frontal and Temporal lobes are highly increased for lower aesthetic appreciation otherwise the above mention lobes are less active for high aesthetic appreciation. This work also employs a unique general type-2 fuzzy scheme to categories the intra- and inter-session variation in brain signals due to temporal fluctuation of active brain regions. The proposed classifier produces supercilious classification accuracy with respect to other primitive classifiers. Moreover, a statistical analysis also confirms the superiority of the proposed GT2FS classifier over its competitors. Hence, the proposed method can be effectively utilized to measure subjective aesthetic appreciation quality, of healthy and psychologically disordered people.
引用
收藏
页码:154 / 158
页数:5
相关论文
共 27 条
[1]  
[Anonymous], PERFORMANCE COMP DIF
[2]   Imagination and the aesthetic appreciation of nature [J].
Brady, E .
JOURNAL OF AESTHETICS AND ART CRITICISM, 1998, 56 (02) :139-147
[3]   Resting-State EEG Source Localization and Functional Connectivity in Schizophrenia-Like Psychosis of Epilepsy [J].
Canuet, Leonides ;
Ishii, Ryouhei ;
Pascual-Marqui, Roberto D. ;
Iwase, Masao ;
Kurimoto, Ryu ;
Aoki, Yasunori ;
Ikeda, Shunichiro ;
Takahashi, Hidetoshi ;
Nakahachi, Takayuki ;
Takeda, Masatoshi .
PLOS ONE, 2011, 6 (11)
[4]   The neural foundations of aesthetic appreciation [J].
Cela-Conde, Camilo J. ;
Agnati, Luigi ;
Huston, Joseph P. ;
Mora, Francisco ;
Nadal, Marcos .
PROGRESS IN NEUROBIOLOGY, 2011, 94 (01) :39-48
[5]   Evaluating Aesthetic Experience through Personal-Appearance Styles: A Behavioral and Electrophysiological Study [J].
Cheung, Mei-chun ;
Law, Derry ;
Yip, Joanne .
PLOS ONE, 2014, 9 (12)
[6]   Aesthetic preference recognition of 3D shapes using EEG [J].
Chew, Lin Hou ;
Teo, Jason ;
Mountstephens, James .
COGNITIVE NEURODYNAMICS, 2016, 10 (02) :165-173
[7]  
Chowdhury M. M. H., 2012, International Journal of Computer Science Issues (IJCSI), V9, P327
[8]   Using event related potentials to investigate visual aesthetic perception of product appearance [J].
Ding, Yi ;
Guo, Fu ;
Hu, Mingcai ;
Cao, Yaqin .
HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES, 2017, 27 (05) :223-232
[9]   General and Interval Type-2 Fuzzy Face-Space Approach to Emotion Recognition [J].
Halder, Anisha ;
Konar, Amit ;
Mandal, Rajshree ;
Chakraborty, Aruna ;
Bhowmik, Pavel ;
Pal, Nikhil R. ;
Nagar, Atulya K. .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2013, 43 (03) :587-605
[10]   Comparative analysis of spectral approaches to feature extraction for EEG-based motor imagery classification [J].
Herman, Pawel ;
Prasad, Girijesh ;
McGinnity, Thomas Martin ;
Coyle, Damien .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2008, 16 (04) :317-326