Results 31 to 40 of about 49,364 (181)
Robust learning from corrupted EEG with dynamic spatial filtering
NeuroImage, 2022 Building machine learning models using EEG recorded outside of the laboratory setting requires methods robust to noisy data and randomly missing channels.
Hubert Banville +4 more
doaj +1 more source
A note on brain actuated spelling with the Berlin brain-computer interface [PDF]
, 2007 Brain-Computer Interfaces (BCIs) are systems capable of decoding neural activity in real time, thereby allowing a computer application to be directly controlled by the brain.
A. Kübler +18 more
core +5 more sources
A real time classification algorithm for EEG-based BCI driven by self-induced emotions [PDF]
, 2015 Background and objective: The aim of this paper is to provide an efficient, parametric, general, and completely automatic real time classification method of electroencephalography (EEG) signals obtained from self-induced emotions.
IACOVIELLO, Daniela +3 more
core +1 more source
Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions. [PDF]
, 2017 Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and ...
Jung, Tzyy-Ping +2 more
core +2 more sources
Frontiers in Human Neuroscience, 2015 There has been a recent surge in the use of electroencephalography (EEG) as a tool for mobile brain imaging due to its portability and fine time resolution. When EEG is combined with independent component analysis (ICA) and source localization techniques,
Kristine Lynne Snyder +5 more
doaj +1 more source
An Epileptic Seizure Detection Technique Using EEG Signals with Mobile Application Development
Applied Sciences, 2023 Epileptic seizure detection classification distinguishes between epileptic and non-epileptic signals and is an important step that can aid doctors in diagnosing and treating epileptic seizures.
Zakareya Lasefr +4 more
doaj +1 more source
Privacy for Personal Neuroinformatics
, 2014 Human brain activity collected in the form of Electroencephalography (EEG), even with low number of sensors, is an extremely rich signal. Traces collected from multiple channels and with high sampling rates capture many important aspects of participants'
Greenwood, Dazza +3 more
core +1 more source
Pleasure of paying when using mobile payment: Evidence from EEG studies
Frontiers in Psychology, 2022 Mobile payment has emerged as a popular payment method in many countries. While much research has focused on the antecedents of mobile payment adoption, limited research has investigated the consequences of mobile payment usage relating to how it would ...
Manlin Wang +7 more
doaj +1 more source
, 2014 Energy consumption is an important issue in continuous wireless telemonitoring of physiological signals. Compressed sensing (CS) is a promising framework to address it, due to its energy-efficient data compression procedure.
Jung, Tzyy-Ping +4 more
core +1 more source
Effects of mobile phones electromagnetic radiation on patients with epilepsy: an EEG study
The Egyptian Journal of Neurology, Psychiatry and Neurosurgery, 2020 Background Recently, an exceptional increase was witnessed in cell phone users. The brain has greater exposure to the electromagnetic field (EMF) created during mobile phone use than the rest of the body, which may impair its function.
Radwa Azmy +4 more
doaj +1 more source