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Spectroscopy, Near-Infrared

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Non-Invasive Estimation of Intracranial Pressure by Diffuse Optics: A Proof-of-Concept Study.

Journal of neurotrauma
Intracranial pressure (ICP) is an important parameter to monitor in several neuropathologies. However, because current clinically accepted methods are invasive, its monitoring is limited to patients in critical conditions. On the other hand, there ar...

Accurate Prediction of Sensory Attributes of Cheese Using Near-Infrared Spectroscopy Based on Artificial Neural Network.

Sensors (Basel, Switzerland)
The acceptance of a food product by the consumer depends, as the most important factor, on its sensory properties. Therefore, it is clear that the food industry needs to know the perceptions of sensory attributes to know the acceptability of a produc...

An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra.

PloS one
After mating, female mosquitoes need animal blood to develop their eggs. In the process of acquiring blood, they may acquire pathogens, which may cause different diseases in humans such as malaria, zika, dengue, and chikungunya. Therefore, knowing th...

Proposing a convolutional neural network for stress assessment by means of derived heart rate from functional near infrared spectroscopy.

Computers in biology and medicine
BACKGROUND: Stress is known as one of the major factors threatening human health. A large number of studies have been performed in order to either assess or relieve stress by analyzing the brain and heart-related signals.

Discrimination of Tetrastigma hemsleyanum according to geographical origin by near-infrared spectroscopy combined with a deep learning approach.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Recently, deep learning has presented as a powerful approach to overcome the deficiencies of the conventional biochemical approaches. In this study, a method for discriminating medicinal plant Tetrastigma hemsleyanum from different origins was propos...

Detection and identification of Cannabis sativa L. using near infrared hyperspectral imaging and machine learning methods. A feasibility study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Remote identification of illegal plantations of Cannabis sativa Linnaeus is an important task for the Brazilian Federal Police. The current analytical methodology is expensive and strongly dependent on the expertise of the forensic investigator. A fa...

Hyperspectral imaging for accurate determination of rice variety using a deep learning network with multi-feature fusion.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The phenomena of rice adulteration and shoddy rice arise continuously in high-quality rice and reduce the interests of producers, consumers and traders. Hyperspectral imaging (HSI) was conducted to determine rice variety using a deep learning network...

fNIRS-GANs: data augmentation using generative adversarial networks for classifying motor tasks from functional near-infrared spectroscopy.

Journal of neural engineering
OBJECTIVE: Functional near-infrared spectroscopy (fNIRS) is expected to be applied to brain-computer interface (BCI) technologies. Since lengthy fNIRS measurements are uncomfortable for participants, it is difficult to obtain enough data to train cla...

The averaged inter-brain coherence between the audience and a violinist predicts the popularity of violin performance.

NeuroImage
Why is some music well-received whereas other music is not? Previous research has indicated the close temporal dependencies of neural activity among performers and among audiences. However, it is unknown whether similar neural contingencies exist bet...

Instructor-learner brain coupling discriminates between instructional approaches and predicts learning.

NeuroImage
The neural mechanisms that support naturalistic learning via effective pedagogical approaches remain elusive. Here we used functional near-infrared spectroscopy to measure brain activity from instructor-learner dyads simultaneously during dynamic con...