Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation

The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained fr...

Full description

Bibliographic Details
Main Authors: Cheng-Hsuan Chen, Kuo-Kai Shyu, Cheng-Kai Lu, Chi-Wen Jao, Po-Lei Lee
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Brain Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3425/11/6/701
_version_ 1797532616353644544
author Cheng-Hsuan Chen
Kuo-Kai Shyu
Cheng-Kai Lu
Chi-Wen Jao
Po-Lei Lee
author_facet Cheng-Hsuan Chen
Kuo-Kai Shyu
Cheng-Kai Lu
Chi-Wen Jao
Po-Lei Lee
author_sort Cheng-Hsuan Chen
collection DOAJ
description The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.
first_indexed 2024-03-10T11:01:47Z
format Article
id doaj.art-bce511a6b46f45e3827e1762ff50f640
institution Directory Open Access Journal
issn 2076-3425
language English
last_indexed 2024-03-10T11:01:47Z
publishDate 2021-05-01
publisher MDPI AG
record_format Article
series Brain Sciences
spelling doaj.art-bce511a6b46f45e3827e1762ff50f6402023-11-21T21:27:07ZengMDPI AGBrain Sciences2076-34252021-05-0111670110.3390/brainsci11060701Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory StimulationCheng-Hsuan Chen0Kuo-Kai Shyu1Cheng-Kai Lu2Chi-Wen Jao3Po-Lei Lee4Department of Electrical Engineering, National Central University, No.300, Zhongda Rd., Zhongli District, Taoyuan City 32001, TaiwanDepartment of Electrical Engineering, National Central University, No.300, Zhongda Rd., Zhongli District, Taoyuan City 32001, TaiwanInstitute of Health & Analytics for Personalised Care, Universiti Teknologi PETRONAS, Seri Iskander 32610, Perak, MalaysiaInstitute of Biophotonics, National Yang-Ming University, No.155, Sec. 2, Linong Street, Taipei 11221, TaiwanDepartment of Electrical Engineering, National Central University, No.300, Zhongda Rd., Zhongli District, Taoyuan City 32001, TaiwanThe sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.https://www.mdpi.com/2076-3425/11/6/701functional near-infrared spectroscopyolfactionhemoglobin response functionsupport vector machineclassificationmachine learning technique
spellingShingle Cheng-Hsuan Chen
Kuo-Kai Shyu
Cheng-Kai Lu
Chi-Wen Jao
Po-Lei Lee
Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation
Brain Sciences
functional near-infrared spectroscopy
olfaction
hemoglobin response function
support vector machine
classification
machine learning technique
title Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation
title_full Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation
title_fullStr Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation
title_full_unstemmed Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation
title_short Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation
title_sort classification of prefrontal cortex activity based on functional near infrared spectroscopy data upon olfactory stimulation
topic functional near-infrared spectroscopy
olfaction
hemoglobin response function
support vector machine
classification
machine learning technique
url https://www.mdpi.com/2076-3425/11/6/701
work_keys_str_mv AT chenghsuanchen classificationofprefrontalcortexactivitybasedonfunctionalnearinfraredspectroscopydatauponolfactorystimulation
AT kuokaishyu classificationofprefrontalcortexactivitybasedonfunctionalnearinfraredspectroscopydatauponolfactorystimulation
AT chengkailu classificationofprefrontalcortexactivitybasedonfunctionalnearinfraredspectroscopydatauponolfactorystimulation
AT chiwenjao classificationofprefrontalcortexactivitybasedonfunctionalnearinfraredspectroscopydatauponolfactorystimulation
AT poleilee classificationofprefrontalcortexactivitybasedonfunctionalnearinfraredspectroscopydatauponolfactorystimulation