Combining time-resolved near-infrared spectroscopy with regression analysis to improve the reconstruction of cerebral hemodynamic responses

2021 ◽  
Author(s):  
Daniel Milej ◽  
Androu Abdalmalak ◽  
Ajay Rajaram ◽  
Marianne Suwalski ◽  
Keith St. Lawrence
Keyword(s):  
Regression Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Hemodynamic Responses ◽  
Time Resolved ◽  
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.

scholarly journals A Versatile Setup for Time-Resolved Functional Near Infrared Spectroscopy Based on Fast-Gated Single-Photon Avalanche Diode and on Four-Wave Mixing Laser

2019 ◽  
Vol 9 (11) ◽  
pp. 2366 ◽  
Author(s):  
Laura Di Sieno ◽  
Alberto Dalla Mora ◽  
Alessandro Torricelli ◽  
Lorenzo Spinelli ◽  
Rebecca Re ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Single Photon ◽  
Wave Mixing ◽  
Functional Near Infrared Spectroscopy ◽  
Time Resolved ◽  
Diffusive Medium ◽  
Spectroscopy System

In this paper, a time-domain fast gated near-infrared spectroscopy system is presented. The system is composed of a fiber-based laser providing two pulsed sources and two fast gated detectors. The system is characterized on phantoms and was tested in vivo, showing how the gating approach can improve the contrast and contrast-to-noise-ratio for detection of absorption perturbation inside a diffusive medium, regardless of source-detector separation.

ERRATA

PEDIATRICS ◽  
1993 ◽  
Vol 92 (1) ◽  
pp. 190-190
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Neurological Disorders ◽  
Near Infrared ◽  
Time Resolved

In the article, "A Report of the National Institute of Neurological Disorders and Stroke Workshop on Near Infrared Spectroscopy" by Hirtz (Pediatrics. 1993;91:414-417), on page 416, middle of the second paragraph, "The accuracy of time-resolved methods is 30% of saturation..." should read "The accuracy of time resolved methods is 3% of saturation ..."

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