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Spectroscopy, Near-Infrared

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A Deep-Learning Empowered, Real-Time Processing Platform of fNIRS/DOT for Brain Computer Interfaces and Neurofeedback.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brain-Computer Interfaces (BCI) and Neurofeedback (NFB) approaches, which both rely on real-time monitoring of brain activity, are increasingly being applied in rehabilitation, assistive technology, neurological diseases and behavioral disorders. Fun...

A novel flexible near-infrared endoscopic device that enables real-time artificial intelligence fluorescence tissue characterization.

PloS one
Real-time endoscopic rectal lesion characterization employing artificial intelligence (AI) and near-infrared (NIR) imaging of the fluorescence perfusion indicator agent Indocyanine Green (ICG) has demonstrated promise. However, commercially available...

Fingerprinting of Boletus bainiugan: FT-NIR spectroscopy combined with machine learning a new workflow for storage period identification.

Food microbiology
Food authenticity and food safety issues have threatened the prosperity of the entire community. The phenomenon of selling porcini mushrooms as old mixed with new jeopardizes consumer safety. Herein, nucleoside contents and spectra of 831 Boletus bai...

Predicting oleogels properties using non-invasive spectroscopic techniques and machine learning.

Food research international (Ottawa, Ont.)
Oleogelators are considered food additives that require approval from regulatory authorities. Therefore, classifying these ingredients that may have characteristics (e.g., waxiness), cost and origin (e.g., animal or vegetable) is crucial to ensure co...

Leveraging infrared spectroscopy for cocoa content prediction: A dual approach with Kohonen neural network and multivariate modeling.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
People of all ages enjoy chocolate, and its popularity is attributed to its pleasant taste and aroma, as well as its associated health benefits. Produced through both artisanal and industrial processes, which involve harvesting, selecting, fermenting...

A review: Integration of NIRS and chemometric methods for tea quality control-principles, spectral preprocessing methods, machine learning algorithms, research progress, and future directions.

Food research international (Ottawa, Ont.)
With the steady rise in tea production, the need for effective tea quality monitoring has become increasingly pressing. Traditional sensory evaluation and wet chemical detection methods are insufficient for real-time tea quality monitoring. As an eme...

Neurorehabilitation in spinal cord injury: Increased cortical activity through tDCS and robotic gait training.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: This study investigates the neurophysiological outcomes of combining robot-assisted gait training (RAGT) with active transcranial direct current stimulation (tDCS) on individuals with spinal cord injury (SCI).

Application of artificial intelligence in the rapid determination of moisture content in medicine food homology substances.

Food chemistry
Moisture content is crucial in quality testing of medicine food homology substances. This study aimed to present a new modeling method for moisture content based on near-infrared spectroscopy. When comparing three methods of partial least squares reg...

Model updating strategy study about sex identification of silkworm pupae using transfer learning and NIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This paper proposes a novel model updating strategy named SilkwormNet for the first time to address the sex discrimination problem of silkworm pupae with new species. SilkwormNet integrates a ResNet block, a multi-head attention mechanism, and a Sche...

A general deep learning model for predicting and classifying pea protein content via visible and near-infrared spectroscopy.

Food chemistry
Rapid and accurate detection of pea protein content is crucial for breeding and ensuring food quality. This study introduces the PeaNet model, which employs an improved convolutional neural network architecture to predict and classify pea protein con...