Selection of the minimum number of EEG sensors to guarantee biometric identification of individuals

J Ortega-Rodríguez, JF Gómez-González, E Pereda - Sensors, 2023 - mdpi.com
Biometric identification uses person recognition techniques based on the extraction of some
of their physical or biological properties, which make it possible to characterize and …

Impact of reduced‐dimensionality independent components analysis on event‐related potential measurements

VJ Pokorny, SR Sponheim, E Rawls - Psychophysiology, 2023 - Wiley Online Library
Independent components analysis (ICA) is an effective and ubiquitous tool for cleaning EEG.
To reduce computation time, many analysis pipelines decrease EEG dimensionality prior to …

Data preprocessing impact on machine learning algorithm performance

A Amato, V Di Lecce - Open Computer Science, 2023 - degruyter.com
The popularity of artificial intelligence applications is on the rise, and they are producing
better outcomes in numerous fields of research. However, the effectiveness of these …

Comparison of the Effectiveness of Various Classifiers for Breast Cancer Detection Using Data Mining Methods

NK Al-Qazzaz, IK Mohammed, HK Al-Qazzaz… - Applied Sciences, 2023 - mdpi.com
Countless women and men worldwide have lost their lives to breast cancer (BC). Although
researchers from around the world have proposed various diagnostic methods for detecting …

Modulation of sleep architecture by whole-body static magnetic exposure: A study based on EEG-based automatic sleep staging

L Yang, H Jiang, X Ding, Z Liao, M Wei, J Li… - International Journal of …, 2022 - mdpi.com
A steady increase in sleep problems has been observed along with the development of
society. Overnight exposure to a static magnetic field has been found to improve sleep …

Different routes or methods of application for dimensionality reduction in multicenter studies databases

N Boukichou-Abdelkader, MÁ Montero-Alonso… - Mathematics, 2022 - mdpi.com
Technological progress and digital transformation, which began with Big Data and Artificial
Intelligence (AI), are currently transforming ways of working in all fields, to support decision …

Identification of Cognitive Workload during Surgical Tasks with Multimodal Deep Learning

K Jin, A Rubio-Solis, R Naik, T Onyeogulu… - arXiv preprint arXiv …, 2022 - arxiv.org
The operating room (OR) is a dynamic and complex environment consisting of a
multidisciplinary team working together in a high take environment to provide safe and …

The different expression patterns of cytokines in Pacific oyster Crassostrea gigas response against bacterial stimulation

Z Zhang, L Gao, Q Li, Z Xing, R Liu, K Zhou, L Wang… - Aquaculture, 2023 - Elsevier
Cytokines can be induced by pathogen stimulation for the information exchange between
cells, and their expression patterns indicate the response status of cells. In the present study …

Portable deep-learning decoder for motor imaginary EEG signals based on a novel compact convolutional neural network incorporating spatial-attention mechanism

Z Wu, X Tang, J Wu, J Huang, J Shen… - Medical & Biological …, 2023 - Springer
Due to high computational requirements, deep-learning decoders for motor imaginary (MI)
electroencephalography (EEG) signals are usually implemented on bulky and heavy …

Automatic sleep scoring with LSTM networks: impact of time granularity and input signals

AM Tăuțan, AC Rossi, B Ionescu - Biomedical Engineering …, 2022 - degruyter.com
Supervised automatic sleep scoring algorithms are usually trained using sleep stage labels
manually annotated on 30 s epochs of PSG data. In this study, we investigate the impact of …