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Found 13 papers, 2 papers with code
Personalised and Adjustable Interval Type-2 Fuzzy-Based PPG Quality Assessment for the Edge
The proposed system employs a personalised approach to adapt the IT2FLS parameters to the unique characteristics of each individual's PPG signals. Additionally, the system provides adjustable levels of personalisation, allowing healthcare providers to adjust the system to meet specific requirements for different applications.
EMGTFNet: Fuzzy Vision Transformer to decode Upperlimb sEMG signals for Hand Gestures Recognition
In this paper, we propose the design of a Vision Transformer (ViT) based architecture with a Fuzzy Neural Block (FNB) called EMGTFNet to perform Hand Gesture Recognition from surface electromyography (sEMG) signals.
ARTxAI: Explainable Artificial Intelligence Curates Deep Representation Learning for Artistic Images using Fuzzy Techniques
We also show that some of the features used by these models can be more clearly correlated to visual traits in the original image than others.
Are advanced methods necessary to improve infant fNIRS data analysis? An assessment of baseline-corrected averaging, general linear model (GLM) and multivariate pattern analysis (MVPA) based approaches
In the last decade, fNIRS has provided a non-invasive method to investigate neural activation in developmental populations.
A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence
In this work, we present novel Temporal Type-2 FLS Based Approach for time-dependent XAI (TXAI) systems, which can account for the likelihood of a measurement's occurrence in the time domain using (the measurement's) frequency of occurrence.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
A Gentle Introduction and Survey on Computing with Words (CWW) Methodologies
Human beings have an inherent capability to use linguistic information (LI) seamlessly even though it is vague and imprecise.
EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery Classification
We also comprehensively explain and support the validity of network illustration from a neuroscientific perspective.
Fuzzy temporal convolutional neural networks in P300-based Brain-computer interface for smart home interaction
The remarkable performance of the proposed model, EEG-TCFNet, and the general integration of fuzzy units to other classifiers would pave the way for enhanced P300-based BCIs for smart home interaction within natural settings.
Towards Understanding Human Functional Brain Development with Explainable Artificial Intelligence: Challenges and Perspectives
The last decades have seen significant advancements in non-invasive neuroimaging technologies that have been increasingly adopted to examine human brain development.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
On the utility of power spectral techniques with feature selection techniques for effective mental task classification in noninvasive BCI
In the case of mental task classification, the availability of training samples to features are minimal.
Symptoms of depersonalisation/derealisation disorder as measured by brain electrical activity: A systematic review
Depersonalisation/derealisation disorder (DPD) refers to frequent and persistent detachment from bodily self and disengagement from the outside world.
A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels
We seek to evaluate the detection performance of a rapid primary screening tool of Covid-19 solely based on the cough sound from 8, 380 clinically validated samples with laboratory molecular-test (2, 339 Covid-19 positives and 6, 041 Covid-19 negatives).
Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning
A deep learning framework has been designed to incorporate EMG and ECG features.
