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Spectroscopy, Near-Infrared

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Improved performance of fNIRS-BCI by stacking of deep learning-derived frequency domain features.

PloS one
The functional near-infrared spectroscopy-based brain-computer interface (fNIRS-BCI) systems recognize patterns in brain signals and generate control commands, thereby enabling individuals with motor disabilities to regain autonomy. In this study han...

A machine learning approach fusing multisource spectral data for prediction of floral origins and taste components of Apis cerana honey.

Food research international (Ottawa, Ont.)
This study explores the use of near-infrared (NIR), mid-infrared (MIR), and Raman spectral fusion for the rapid prediction of floral origins and main taste components in Apis cerana (A. cerana) honey. Feature-level fusion with the partial least squar...

Improvement of near-infrared spectroscopic assessment methods for the quality of Keemun black tea: Utilizing transfer learning.

Food research international (Ottawa, Ont.)
Keemun black tea, a renowned Chinese black tea, presents challenges in quality assessment due to variability in data across different years. To address this, we developed transfer learning algorithms using near-infrared spectral data. The qualitative...

Compositional analysis of alternative protein blends using near and mid-infrared spectroscopy coupled with conventional and machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The non-invasive real-time analysis of the composition of alternative, plant-based protein sources is important to control high moisture extrusion processes and ensure the quality and texture of the final extrudates used in the elaboration of meat an...

Simultaneous detection of citrus internal quality attributes using near-infrared spectroscopy and hyperspectral imaging with multi-task deep learning and instrumental transfer learning.

Food chemistry
Simultaneous determination of multiple quality attributes of citrus fruits using hyperspectral imaging (HSI) and near-infrared (NIR) spectroscopy and successfully transferring the models among different instruments are two main challenges. In this st...

Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly sensitive and minimally invasive early diagnostic methods. Near-infrared spectroscopy (NIRS) offers unique advantages in probing molecular vibrational i...

An interpretable deep-learning approach to detect biomarkers in anxious-depressed symptoms from prefrontal fNIRS signals during an autobiographical memory test.

Asian journal of psychiatry
BACKGROUND: Individuals with anxious-depressed (AD) symptoms have more severe mood disorders and cognitive impairment than those with non-anxious depression (NAD) symptoms. Therefore, it is important to clarify the underlying neurophysiology of these...

A Multitask CNN for Near-Infrared Probe: Enhanced Real-Time Breast Cancer Imaging.

Sensors (Basel, Switzerland)
The early detection of breast cancer, particularly in dense breast tissues, faces significant challenges with traditional imaging techniques such as mammography. This study utilizes a Near-infrared Scan (NIRscan) probe and an advanced convolutional n...

fNIRS experimental study on the impact of AI-synthesized familiar voices on brain neural responses.

Scientific reports
With the advancement of artificial intelligence (AI) speech synthesis technology, its application in personalized voice services and its potential role in emotional comfort have become research focal points. This study aims to explore the impact of A...