scholarly journals Cerebral hemodynamic responses to seizure in the mouse brain: simultaneous near-infrared spectroscopy–electroencephalography study

2010 ◽  
Vol 15 (3) ◽  
pp. 037010 ◽  
Author(s):  
Seungduk Lee ◽  
Mina Lee ◽  
Dalkwon Koh ◽  
Beop-Min Kim ◽  
Jee Hyun Choi
Keyword(s):  
Infrared Spectroscopy ◽  
Mouse Brain ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Hemodynamic Responses ◽  
Cerebral Hemodynamic

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.

Near-infrared spectroscopy: a tool to monitor cerebral hemodynamic and metabolic changes after cardiac arrest in rats

Resuscitation ◽  
2004 ◽  
Vol 63 (2) ◽  
pp. 213-220 ◽  
Author(s):  
Feng Xiao ◽  
Juan Rodriguez ◽  
Thomas C. Arnold ◽  
Shu Zhang ◽  
Davon Ferrara ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Metabolic Changes ◽  
Cerebral Hemodynamic

scholarly journals Cerebral Hemodynamic Response to Unpleasant Odors in the Preterm Newborn Measured by Near-Infrared Spectroscopy

2001 ◽  
Vol 50 (3) ◽  
pp. 324-330 ◽  
Author(s):  
Marco Bartocci ◽  
Jan Winberg ◽  
Gesa Papendieck ◽  
Teresa Mustica ◽  
Giovanni Serra ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Hemodynamic Response ◽  
Preterm Newborn ◽  
Cerebral Hemodynamic
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