PMID- 27066153
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20160412
LR  - 20201001
IS  - 1871-4080 (Print)
IS  - 1871-4099 (Electronic)
IS  - 1871-4080 (Linking)
VI  - 10
IP  - 2
DP  - 2016 Apr
TI  - Aesthetic preference recognition of 3D shapes using EEG.
PG  - 165-73
LID - 10.1007/s11571-015-9363-z [doi]
AB  - Recognition and identification of aesthetic preference is indispensable in 
      industrial design. Humans tend to pursue products with aesthetic values and make 
      buying decisions based on their aesthetic preferences. The existence of 
      neuromarketing is to understand consumer responses toward marketing stimuli by 
      using imaging techniques and recognition of physiological parameters. Numerous 
      studies have been done to understand the relationship between human, art and 
      aesthetics. In this paper, we present a novel preference-based measurement of 
      user aesthetics using electroencephalogram (EEG) signals for virtual 3D shapes 
      with motion. The 3D shapes are designed to appear like bracelets, which is 
      generated by using the Gielis superformula. EEG signals were collected by using a 
      medical grade device, the B-Alert X10 from advance brain monitoring, with a 
      sampling frequency of 256 Hz and resolution of 16 bits. The signals obtained when 
      viewing 3D bracelet shapes were decomposed into alpha, beta, theta, gamma and 
      delta rhythm by using time-frequency analysis, then classified into two classes, 
      namely like and dislike by using support vector machines and K-nearest neighbors 
      (KNN) classifiers respectively. Classification accuracy of up to 80 % was 
      obtained by using KNN with the alpha, theta and delta rhythms as the features 
      extracted from frontal channels, Fz, F3 and F4 to classify two classes, like and 
      dislike.
FAU - Chew, Lin Hou
AU  - Chew LH
AUID- ORCID: 0000-0003-0131-9534
AD  - Faculty of Computing and Informatics, Universiti Malaysia Sabah, UMS Road, 88400 
      Kota Kinabalu, Malaysia.
FAU - Teo, Jason
AU  - Teo J
AD  - Faculty of Computing and Informatics, Universiti Malaysia Sabah, UMS Road, 88400 
      Kota Kinabalu, Malaysia.
FAU - Mountstephens, James
AU  - Mountstephens J
AD  - Faculty of Computing and Informatics, Universiti Malaysia Sabah, UMS Road, 88400 
      Kota Kinabalu, Malaysia.
LA  - eng
PT  - Journal Article
DEP - 20151104
PL  - Netherlands
TA  - Cogn Neurodyn
JT  - Cognitive neurodynamics
JID - 101306907
PMC - PMC4805684
OTO - NOTNLM
OT  - 3-Dimensional (3D) shape preference
OT  - Aesthetic design
OT  - Brain-computer interface (BCI)
OT  - Electroencephalogram (EEG)
OT  - K-nearest neighbors (KNN)
OT  - Neuro-aesthetics
OT  - Support vector machines (SVM)
EDAT- 2016/04/12 06:00
MHDA- 2016/04/12 06:01
PMCR- 2017/04/01
CRDT- 2016/04/12 06:00
PHST- 2015/05/14 00:00 [received]
PHST- 2015/10/09 00:00 [revised]
PHST- 2015/10/22 00:00 [accepted]
PHST- 2016/04/12 06:00 [entrez]
PHST- 2016/04/12 06:00 [pubmed]
PHST- 2016/04/12 06:01 [medline]
PHST- 2017/04/01 00:00 [pmc-release]
AID - 9363 [pii]
AID - 10.1007/s11571-015-9363-z [doi]
PST - ppublish
SO  - Cogn Neurodyn. 2016 Apr;10(2):165-73. doi: 10.1007/s11571-015-9363-z. Epub 2015 
      Nov 4.