Participants were presented with polyphonic music made of two monophonic streams (PolyOrig condition), with control stimuli where the average pi ...

Neuralis is the company’s wearable BCI headset targeting the motor cortex, with dry sensors and on-device signal processing ...

Introduction: Brain-computer interfaces (BCIs) leverage EEG signal processing to enable human-machine communication and have broad application potential. However, existing deep learning-based BCI ...

Abstract: Graph Signal Processing (GSP), an emerging field, provides a flexible framework to model and analyze Electroencephalogram (EEG) sensor data that exhibit intricate relationships and ...

In the world around us, many things exist in the context of time: a bird’s path through the sky is understood as different positions over a period of time, and conversations as a series of words ...

New research looks at EEG's role in real-time monitoring of workers' cognitive and emotional states and its potential in automating the detection of psychological hazards like stress and fatigue, ...

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...

ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...

Abstract: To analyze the physiological information within the acquired EEG signal is very cumbersome due to the possibility of several factors, viz. noise and artifacts, complexity of brain dynamics, ...

The purpose of this study was to apply deep learning to music perception education. Music perception therapy for autistic children using gesture interactive robots based on the concept of educational ...