Search results for "Eeg"
showing 10 items of 313 documents
Three different approaches to cognitive fatigue in patients with a mild form of multiple sclerosis : objective cognitive, subjective cognitive and ne…
2017
Tämän tutkimuksen tarkoitus oli arvioida kognitiivista uupumusta lievää multippeli skleroosin (MS) muotoa sairastavilla potilailla kolmea eri lähestymistapaa käyttäen: objektiivista kognitiivista, subjektiivista kognitiivista ja neurofysiologista. Objektiivista kognitiivista uupumusta arvioitiin tarkkaavuuden ylläpitoa, reaktionopeutta ja työmuistia mittaavilla tehtävillä. Subjektiivista kognitiivista uupumusta sekä elämänlaatua arvioitiin itsearvioilla. Neurofysiologiset mittaukset käsittivät aivojen sähköiin herätevasteisiin perustuvia observaatioita. Mittareina olivat kontingentti negatiivinen variaatio (CNV) ja P3. Tutkimukseen osallistui 20 MS-tautia sairastavaa ja 20 verrallistettua t…
Electrophysiological evidence for the effectiveness of images versus text in warnings
2023
AbstractWarning sign plays an important role in risk avoidance. Many studies have found that images are better warnings than text, while others have revealed flaws of image-only warning signs. To better understand the factors underlying the effectiveness of different types of warning signs (image only, text only, or image and text), this study adopted event-related potential technology to explore the differences at the neurocognitive level using the oddball paradigm and the Go/No-go paradigm. Together, the behavioral and electroencephalogram results showed that text-only warnings had the lowest effectiveness, but there was little difference between the image-only and image-and-text warnings…
LightSleepNet: A Lightweight Deep Model for Rapid Sleep Stage Classification with Spectrograms.
2021
Deep learning has achieved unprecedented success in sleep stage classification tasks, which starts to pave the way for potential real-world applications. However, due to its enormous size, deployment of deep neural networks is hindered by high cost at various aspects, such as computation power, storage, network bandwidth, power consumption, and hardware complexity. For further practical applications (e.g., wearable sleep monitoring devices), there is a need for simple and compact models. In this paper, we propose a lightweight model, namely LightSleepNet, for rapid sleep stage classification based on spectrograms. Our model is assembled by a much fewer number of model parameters compared to…
One-Dimensional Convolutional Neural Networks Combined with Channel Selection Strategy for Seizure Prediction Using Long-Term Intracranial EEG
2022
Seizure prediction using intracranial electroencephalogram (iEEG) has attracted an increasing attention during recent years. iEEG signals are commonly recorded in the form of multiple channels. Many previous studies generally used the iEEG signals of all channels to predict seizures, ignoring the consideration of channel selection. In this study, a method of one-dimensional convolutional neural networks (1D-CNN) combined with channel selection strategy was proposed for seizure prediction. First, we used 30-s sliding windows to segment the raw iEEG signals. Then, the 30-s iEEG segments, which were in three channel forms (single channel, channels only from seizure onset or free zone and all c…
One and Two Dimensional Convolutional Neural Networks for Seizure Detection Using EEG Signals
2021
Deep learning for the automated detection of epileptic seizures has received much attention during recent years. In this work, one dimensional convolutional neural network (1D-CNN) and two dimensional convolutional neural network (2D-CNN) are simultaneously used on electroencephalogram (EEG) data for seizure detection. Firstly, using sliding windows without overlap on raw EEG to obtain the definite one-dimension time EEG segments (1D-T), and continuous wavelet transform (CWT) for 1D-T signals to obtain the two-dimension time-frequency representations (2D-TF). Then, 1D-CNN and 2D-CNN model architectures are used on 1D-T and 2D-TF signals for automatic classification, respectively. Finally, t…
Smadzeņu aktivitāte un volumetriskais ekrāns
2020
Maģistra darbs uzrakstīts angļu valodā uz 32 lappusēm. Tas satur 15 attēlus un ir atsauces uz 37 literatūras avotiem. Strauji attīstoties trīsdimensiju (3D) vizualizācijas tehnoloģijai ir nepieciešams precīzi novērtēt cilvēka spēju pielāgoties tai. Šādos pētījumos plaši tiek izmantots EEG. Pētījuma mērķis bija izpētīt smadzeņu aktivitātes īslaicīgās izmaiņas, skatoties uz volumetriskiem attēliem un salīdzinot ar anaglifa 3D attēlu aplūkošanu. Uzdevums bija noteikt tuvāk esošo apli starp četriem projicētiem apļiem. Smadzeņu aktivitātes signālu reģistrēšanai tika izmantots EEG. Izsaukto potenciālu P300 komponentē darba slodzes ietekmē netika novērotas būtiskas izmaiņas. Būtiskas izmaiņas tika…
Reproducibility of Rolandic beta rhythm modulation in MEG and EEG
2022
The Rolandic beta rhythm, at ∼20 Hz, is generated in the somatosensory and motor cortices and is modulated by motor activity and sensory stimuli, causing a short lasting suppression that is followed by a rebound of the beta rhythm. The rebound reflects inhibitory changes in the primary sensorimotor (SMI) cortex, and thus it has been used as a biomarker to follow the recovery of patients with acute stroke. The longitudinal stability of beta rhythm modulation is a prerequisite for its use in long-term follow-ups. We quantified the reproducibility of beta rhythm modulation in healthy subjects in a 1-year-longitudinal study both for MEG and EEG at T0, 1 month (T1-month, n = 8) and 1 year (T1-ye…
The effect of improvisational music therapy on the treatment of depression: protocol for a randomised controlled trial
2008
Background. Music therapy is frequently offered to individuals suffering from depression. Despite the lack of research into the effects of music therapy on this population, anecdotal evidence suggests that the results are rather promising. The aim of this study is to examine whether improvisational, psychodynamically orientated music therapy in an individual setting helps reduce symptoms of depression and improve other health-related outcomes. In particular, attention will be given to mediator agents, such as musical expression and interaction in the sessions, as well as to the explanatory potential of EEG recordings in investigating emotion related music perception of individuals with depr…
The role of expert evaluation for microsleep detection
2015
Abstract Recently, it has been shown by overnight driving simulation studies that microsleep density is the only known sleepiness indicator which rapidly increases within a few seconds immediately before sleepiness related crashes. This indicator is based solely on EEG and EOG and subsequent adaptive pattern recognition. Accurate microsleep recognition is very important for the performance of this sleepiness indicator. The question is whether expensive evaluations of microsleep events by a) experts are necessary or b) non-experts provide sufficient evaluations. Based on 11,114 microsleep events in case a) and 12,787 in case b) recognition accuracies were investigated utilizing (i) artificia…
Mixis strategies and resting eeg production of rotifers living in temporally-varying habitats
1993
A dynamic model based on six differential equations has been developed to explore the control of mixis of rotifers living in temporally-varying habitats. The equations give variation rates of amictic females, three stages of mictic females, males and resting eggs. The model takes into account some constraints on mixis (e.g., male-female encounter probability and effort involved in resting egg production) and its predictions have been generated by computer simulation using parameter values from the literature. For simulation, a time-dependent birth rate function was assumed to account for changes in the environment, and several mixis patterns (i.e., moment of mixis induction and mictic rate …