Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …

This paper reviews the recent literature on machine learning (ML) models that have been
used for condition monitoring in wind turbines (eg blade fault detection or generator …

The spectral analysis of signals is currently either dominated by the speed–accuracy trade-
off or ignores a signal's often non-stationary character. Here we introduce an open-source …

Since the manual detection of electrographic seizures in continuous electroencephalogram
(EEG) monitoring is very time-consuming and requires a trained expert, attempts to develop …

Multifractality is ubiquitously observed in complex natural and socioeconomic systems.
Multifractal analysis provides powerful tools to understand the complex nonlinear nature of …

It has long been proposed that flying and swimming animals could exploit neighbour-
induced flows. Despite this it is still not clear whether, and if so how, schooling fish …

Over the past decade, many researchers have come up with different implementations of
systems for decoding covert or imagined speech from EEG (electroencephalogram). They …

To explore human emotions, in this paper, we design and build a multi-modal physiological
emotion database, which collects four modal physiological signals, ie …

The climatic warming and humidification observed in the arid region of Northwest China
(ARNC) and their impacts on the ecological environment have become an issue of concern …

Objective: This paper investigates the multivariate oscillatory nature of
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …