PERSON IDENTIFICATION USING FUNCTIONAL NEAR- INFRARED SPECTROSCOPY SIGNALS USING A FULLY CONNECTED DEEP NEURAL NETWORK

Ozge MERCANOGLU SINCAN; Hacer YALIM KELES; Yagmur KIR; Adnan KUSMAN; Bora BASKAK

Makale detayları

PERSON IDENTIFICATION USING FUNCTIONAL NEAR- INFRARED SPECTROSCOPY SIGNALS USING A FULLY CONNECTED DEEP NEURAL NETWORK

Yazarlar:

Ozge MERCANOGLU SINCAN | Hacer YALIM KELES | Yagmur KIR | Adnan KUSMAN | Bora BASKAK

Yayıncı:

Ankara University

Dergi:

Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 2017 Vol.59 Issue 2, pp.55-68

Belge Tipi:

Makale

Yayın Tarihi:

12/2017

Belge Dili:

İngilizce

Document ID (Org No.):

2000911038

Sıklık:

İki Yıllık

eISSN:

2618-6462

Özet:

 

In this study, we investigate the suitability of
functional near-infrared spectroscopy signals (fNIRS) for person identification
using data visualization and machine learning algorithms. We first applied two
linear dimension reduction algorithms: Principle Component Analysis (PCA) and
Singular Value Decomposition (SVD) in order to reduce the dimensionality of the
fNIRS data. We then inspected the clustering of samples in a 2d space using a
nonlinear projection algorithm. We observed with the SVD projection that the
data integrity associated with each person is high in the reduced space. In the
light of these observations, we implemented a random forest algorithm as a
baseline model and a fully connected deep neural network (FCDNN) as the primary
model to identify person from their brain signals. We obtained %85.16 accuracy
with our FCDNN model using SVD reduction. Our results are in parallel with the
neuroscience researches, which state that brain signals of each person are
unique and can be used to identify a person.

Makale detayları

PERSON IDENTIFICATION USING FUNCTIONAL NEAR- INFRARED SPECTROSCOPY SIGNALS USING A FULLY CONNECTED DEEP NEURAL NETWORK

Yazarlar: Ozge MERCANOGLU SINCAN | Hacer YALIM KELES | Yagmur KIR | Adnan KUSMAN | Bora BASKAK

Yayıncı: Ankara University

Dergi: Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 2017 Vol.59 Issue 2, pp.55-68

Belge Tipi: Makale

Yayın Tarihi: 12/2017

Belge Dili: İngilizce

Document ID (Org No.): 2000911038

Sıklık: İki Yıllık

eISSN: 2618-6462

Sayı

Yazarlar:

Ozge MERCANOGLU SINCAN | Hacer YALIM KELES | Yagmur KIR | Adnan KUSMAN | Bora BASKAK

Yayıncı:

Ankara University

Dergi:

Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 2017 Vol.59 Issue 2, pp.55-68

Belge Tipi:

Makale

Yayın Tarihi:

12/2017

Belge Dili:

İngilizce

Document ID (Org No.):

2000911038

Sıklık:

İki Yıllık

eISSN:

2618-6462