150 citations · 333 across the 11 of their papers we have counts for
11 papers
Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data
Christian Flores, Marcelo Contreras, Ichiro Macedo +1
Machine learning and deep learning advancements have boosted Brain-Computer Interface (BCI) performance, but their wide-scale applicability is limited due to factors like individua…
EMGTFNet: Fuzzy Vision Transformer to decode Upperlimb sEMG signals for Hand Gestures Recognition
Joseph Cherre Córdova, Christian Flores, Javier Andreu-Perez
Myoelectric control is an area of electromyography of increasing interest nowadays, particularly in applications such as Hand Gesture Recognition (HGR) for bionic prostheses. Today…
Personalised and Adjustable Interval Type-2 Fuzzy-Based PPG Quality Assessment for the Edge
Jose A. Miranda, Celia López-Ongil, Javier Andreu-Perez
Most of today's wearable technology provides seamless cardiac activity monitoring. Specifically, the vast majority employ Photoplethysmography (PPG) sensors to acquire blood volume…
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
Maria Laura Filippetti, Javier Andreu-Perez, Carina de Klerk +2
In the last decade, fNIRS has provided a non-invasive method to investigate neural activation in developmental populations. Despite its increasing use in developmental cognitive ne…
EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery Classification
Abbas Salami, Javier Andreu-Perez, Helge Gillmeister
In recent years, neural networks and especially deep architectures have received substantial attention for EEG signal analysis in the field of brain-computer interfaces (BCIs). In…
Fuzzy temporal convolutional neural networks in P300-based Brain-computer interface for smart home interaction
Christian Flores Vega, Jonathan Quevedo, Elmer Escandón +3
The processing and classification of electroencephalographic signals (EEG) are increasingly performed using deep learning frameworks, such as convolutional neural networks (CNNs),…
Towards Understanding Human Functional Brain Development with Explainable Artificial Intelligence: Challenges and Perspectives
Mehrin Kiani, Javier Andreu-Perez, Hani Hagras +2
The last decades have seen significant advancements in non-invasive neuroimaging technologies that have been increasingly adopted to examine human brain development. However, these…
Symptoms of depersonalisation/derealisation disorder as measured by brain electrical activity: A systematic review
Abbas Salami, Javier Andreu-Perez, Helge Gillmeister
Depersonalisation/derealisation disorder (DPD) refers to frequent and persistent detachment from bodily self and disengagement from the outside world. As a dissociative disorder, D…
Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning
Delaram Jarchi, Javier Andreu-Perez, Mehrin Kiani +4
Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In th…
Clinical Brain-Computer Interface Challenge 2020 (CBCIC at WCCI2020): Overview, methods and results
Anirban Chowdhury, Javier Andreu-Perez
In the field of brain-computer interface (BCI) research, the availability of high-quality open-access datasets is essential to benchmark the performance of emerging algorithms. The…
Artificial Intelligence and Robotics
Javier Andreu-Perez, Fani Deligianni, Daniele Ravi +1
The recent successes of AI have captured the wildest imagination of both the scientific communities and the general public. Robotics and AI amplify human potentials, increase produ…