scholarly journals Analyses of the cortical hemodynamic responses related to postural control during sensory conflict using near-infrared spectroscopy (NIRS)

2020 ◽  
Vol 79 (3) ◽  
pp. 189-197
Author(s):  
Hiromasa Takakura
Keyword(s):  
Infrared Spectroscopy ◽  
Postural Control ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Hemodynamic Responses ◽  
Sensory Conflict

scholarly journals Hemodynamic Responses of Rat Brain Measured by Near-infrared Spectroscopy During Various Whisker Stimulations

2009 ◽  
Vol 13 (1) ◽  
pp. 166-170 ◽  
Author(s):  
Seung-Duk Lee ◽  
Dalk-Won Koh ◽  
Ki-Woon Kwon ◽  
Hyun-Joo Lee ◽  
Yiran Lang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Rat Brain ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Hemodynamic Responses

scholarly journals Decoding Three Different Preference Levels of Consumers Using Convolutional Neural Network: A Functional Near-Infrared Spectroscopy Study

2021 ◽  
Vol 14 ◽  
Author(s):  
Kunqiang Qing ◽  
Ruisen Huang ◽  
Keum-Shik Hong
Keyword(s):  
Neural Network ◽  
Infrared Spectroscopy ◽  
Convolutional Neural Network ◽  
Near Infrared Spectroscopy ◽  
Classification Accuracy ◽  
Near Infrared ◽  
Classification Performance ◽  
Hemodynamic Responses ◽  
Functional Near Infrared Spectroscopy ◽  
Cerebral Hemodynamic

This study decodes consumers' preference levels using a convolutional neural network (CNN) in neuromarketing. The classification accuracy in neuromarketing is a critical factor in evaluating the intentions of the consumers. Functional near-infrared spectroscopy (fNIRS) is utilized as a neuroimaging modality to measure the cerebral hemodynamic responses. In this study, a specific decoding structure, called CNN-based fNIRS-data analysis, was designed to achieve a high classification accuracy. Compared to other methods, the automated characteristics, constant training of the dataset, and learning efficiency of the proposed method are the main advantages. The experimental procedure required eight healthy participants (four female and four male) to view commercial advertisement videos of different durations (15, 30, and 60 s). The cerebral hemodynamic responses of the participants were measured. To compare the preference classification performances, CNN was utilized to extract the most common features, including the mean, peak, variance, kurtosis, and skewness. Considering three video durations, the average classification accuracies of 15, 30, and 60 s videos were 84.3, 87.9, and 86.4%, respectively. Among them, the classification accuracy of 87.9% for 30 s videos was the highest. The average classification accuracies of three preferences in females and males were 86.2 and 86.3%, respectively, showing no difference in each group. By comparing the classification performances in three different combinations (like vs. so-so, like vs. dislike, and so-so vs. dislike) between two groups, male participants were observed to have targeted preferences for commercial advertising, and the classification performance 88.4% between “like” vs. “dislike” out of three categories was the highest. Finally, pairwise classification performance are shown as follows: For female, 86.1% (like vs. so-so), 87.4% (like vs. dislike), 85.2% (so-so vs. dislike), and for male 85.7, 88.4, 85.1%, respectively.

Measuring Prefrontal Hemodynamic Responses Using Functional Near-Infrared Spectroscopy During Mobility for a Child With Motor Impairment

2017 ◽  
Vol 71 (4_Supplement_1) ◽  
pp. 7111505120p1
Author(s):  
Kelly Cusick ◽  
Alexandra DiStasi ◽  
Stephanie Holowinski ◽  
Olivia Fitzpatrick ◽  
Megan Davis ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Motor Impairment ◽  
Hemodynamic Responses ◽  
Functional Near Infrared Spectroscopy
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