[HTML][HTML] Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade
Mental health is a basic need for a sustainable and developing society. The prevalence and
financial burden of mental illness have increased globally, and especially in response to …
financial burden of mental illness have increased globally, and especially in response to …
Evidence of chaos in electroencephalogram signatures of human performance: A systematic review
(1) Background: Chaos, a feature of nonlinear dynamical systems, is well suited for
exploring biological time series, such as heart rates, respiratory records, and particularly …
exploring biological time series, such as heart rates, respiratory records, and particularly …
SchizoNET: a robust and accurate Margenau–Hill time-frequency distribution based deep neural network model for schizophrenia detection using EEG signals
Objective. Schizophrenia (SZ) is a severe chronic illness characterized by delusions,
cognitive dysfunctions, and hallucinations that impact feelings, behaviour, and thinking …
cognitive dysfunctions, and hallucinations that impact feelings, behaviour, and thinking …
Continual learning of a transformer-based deep learning classifier using an initial model from action observation EEG data to online motor imagery classification
PL Lee, SH Chen, TC Chang, WK Lee, HT Hsu… - Bioengineering, 2023 - mdpi.com
The motor imagery (MI)-based brain computer interface (BCI) is an intuitive interface that
enables users to communicate with external environments through their minds. However …
enables users to communicate with external environments through their minds. However …
ECGPsychNet: An optimized hybrid ensemble model for automatic detection of psychiatric disorders using ECG signals
Background. Psychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BD), and
depression (DPR) are some of the leading causes of disability and suicide worldwide. The …
depression (DPR) are some of the leading causes of disability and suicide worldwide. The …
Exploring the role of visual guidance in motor imagery-based brain-computer interface: An EEG microstate-specific functional connectivity study
Motor imagery-based brain–computer interfaces (BCI) have been widely recognized as
beneficial tools for rehabilitation applications. Moreover, visually guided motor imagery was …
beneficial tools for rehabilitation applications. Moreover, visually guided motor imagery was …
Focal and non-focal EEG signal classification using the Wigner–Ville distribution and deep feature extraction
Accurate detection of focal epilepsy is helpful in locating the epileptogenic region for
effective surgery. Electroencephalogram (EEG) signals capture the changes in the brain …
effective surgery. Electroencephalogram (EEG) signals capture the changes in the brain …
[HTML][HTML] Biomedical Signal Processing and Health Monitoring Based on Sensors
The healthcare industry is undergoing rapid transformation driven by advancements in
Internet of Things (IoT) technologies, particularly in biomedical signal processing and health …
Internet of Things (IoT) technologies, particularly in biomedical signal processing and health …
Speech Deception Detection Based on EMD and Temporal Neural Network
Y Jiang, H Chen, S Yuan, H Xing, Y Cao… - Computational …, 2023 - Wiley Online Library
Deceptive behaviour is a common phenomenon in human society. Research has shown that
humans are not good at distinguishing deception, so studying automated deception …
humans are not good at distinguishing deception, so studying automated deception …
A FUSION OF A DISCRETE WAVELET TRANSFORM-BASED AND TIME-DOMAIN FEATURE EXTRACTION FOR MOTOR IMAGERY CLASSIFICATION.
ABSTRACT A motor imagery (MI)-based brain-computer interface (BCI) has performed
successfully as a control mechanism with multiple electroencephalogram (EEG) channels …
successfully as a control mechanism with multiple electroencephalogram (EEG) channels …