Keyword search (4,163 papers available)

"electroencephalography" Keyword-tagged Publications:

Title Authors PubMed ID
1 Sound degradation type differentially affects neural indicators of cognitive workload and speech tracking Gagné N; Greenlaw KM; Coffey EBJ; 40412301
PSYCHOLOGY
2 Phase-Amplitude Coupling of NREM Sleep Oscillations Shows Between-Night Stability and is Related to Overnight Memory Gains Cross N; O' Byrne J; Weiner OM; Giraud J; Perrault AA; Dang-Vu TT; 40214027
PERFORM
3 PreVISE: an efficient virtual reality system for SEEG surgical planning Spiegler P; Abdelsalam H; Hellum O; Hadjinicolaou A; Weil AG; Xiao Y; 39735694
ENCS
4 Metrics for evaluation of automatic epileptogenic zone localization in intracranial electrophysiology Hrtonova V; Nejedly P; Travnicek V; Cimbalnik J; Matouskova B; Pail M; Peter-Derex L; Grova C; Gotman J; Halamek J; Jurak P; Brazdil M; Klimes P; Frauscher B; 39608298
SOH
5 A protocol for trustworthy EEG decoding with neural networks Borra D; Magosso E; Ravanelli M; 39549492
ENCS
6 SpeechBrain-MOABB: An open-source Python library for benchmarking deep neural networks applied to EEG signals Borra D; Paissan F; Ravanelli M; 39265481
ENCS
7 The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study Jourde HR; Merlo R; Brooks M; Rowe M; Coffey EBJ; 37675803
CONCORDIA
8 Dynamic networks differentiate the language ability of children with cochlear implants Koirala N; Deroche MLD; Wolfe J; Neumann S; Bien AG; Doan D; Goldbeck M; Muthuraman M; Gracco VL; 37409105
PSYCHOLOGY
9 Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data Thölke P; Mantilla-Ramos YJ; Abdelhedi H; Maschke C; Dehgan A; Harel Y; Kemtur A; Mekki Berrada L; Sahraoui M; Young T; Bellemare Pépin A; El Khantour C; Landry M; Pascarella A; Hadid V; Combrisson E; O' Byrne J; Jerbi K; 37385392
IMAGING
10 Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy Frauscher B; Bénar CG; Engel JJ; Grova C; Jacobs J; Kahane P; Wiebe S; Zjilmans M; Dubeau F; 37119580
PERFORM
11 Electroencephalographic characteristics of children and adolescents with chronic musculoskeletal pain Ocay DD; Teel EF; Luo OD; Savignac C; Mahdid Y; Blain-Moraes S; Ferland CE; 36601627
HKAP
12 Alpha and beta neural oscillations differentially reflect age-related differences in bilateral coordination Shih PC; Steele CJ; Nikulin VV; Gundlach C; Kruse J; Villringer A; Sehm B; 33979705
PSYCHOLOGY
13 Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography. Avigdor T, Abdallah C, von Ellenrieder N, Hedrich T, Rubino A, Lo Russo G, Bernhardt B, Nobili L, Grova C, Frauscher B 33450578
PERFORM
14 PASS: A Multimodal Database of Physical Activity and Stress for Mobile Passive Body/ Brain-Computer Interface Research Parent M; Albuquerque I; Tiwari A; Cassani R; Gagnon JF; Lafond D; Tremblay S; Falk TH; 33363449
PERFORM
15 Source imaging of deep-brain activity using the regional spatiotemporal Kalman filter Hamid L; Habboush N; Stern P; Japaridze N; Aydin Ü; Wolters CH; Claussen JC; Heute U; Stephani U; Galka A; Siniatchkin M; 33250282
PERFORM
16 Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy. Heers M, Chowdhury RA, Hedrich T, Dubeau F, Hall JA, Lina JM, Grova C, Kobayashi E 25609211
PERFORM
17 Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia Dang-Vu TT; Hatch B; Salimi A; Mograss M; Boucetta S; O' Byrne J; Brandewinder M; Berthomier C; Gouin JP; 29157588
PERFORM

 

Title:PASS: A Multimodal Database of Physical Activity and Stress for Mobile Passive Body/ Brain-Computer Interface Research
Authors:Parent MAlbuquerque ITiwari ACassani RGagnon JFLafond DTremblay SFalk TH
Link:https://pubmed.ncbi.nlm.nih.gov/33363449/
DOI:10.3389/fnins.2020.542934
Publication:Frontiers in neuroscience
Keywords:body/brain-computer interfaceselectrodermal activityelectroencephalography (EEG)heart rate variabilityneurophysiologyphysical activitystresswearables
PMID:33363449 Category: Date Added:2020-12-28
Dept Affiliation: PERFORM
1 INRS-EMT, Université du Québec, Montréal, QC, Canada.
2 Thales Research and Technology Canada, Quebec City, QC, Canada.
3 Université Laval, School of Psychology, Quebec City, QC, Canada.
4 PERFORM Center, Concordia University, Montréal, QC, Canada.

Description:

With the burgeoning of wearable devices and passive body/brain-computer interfaces (B/BCIs), automated stress monitoring in everyday settings has gained significant attention recently, with applications ranging from serious games to clinical monitoring. With mobile users, however, challenges arise due to other overlapping (and potentially confounding) physiological responses (e.g., due to physical activity) that may mask the effects of stress, as well as movement artifacts that can be introduced in the measured signals. For example, the classical increase in heart rate can no longer be attributed solely to stress and could be caused by the activity itself. This makes the development of mobile passive B/BCIs challenging. In this paper, we introduce PASS, a multimodal database of Physical Activity and StresS collected from 48 participants. Participants performed tasks of varying stress levels at three different activity levels and provided quantitative ratings of their perceived stress and fatigue levels. To manipulate stress, two video games (i.e., a calm exploration game and a survival game) were used. Peripheral physical activity (electrocardiography, electrodermal activity, breathing, skin temperature) as well as cerebral activity (electroencephalography) were measured throughout the experiment. A complete description of the experimental protocol is provided and preliminary analyses are performed to investigate the physiological reactions to stress in the presence of physical activity. The PASS database, including raw data and subjective ratings has been made available to the research community at http://musaelab.ca/pass-database/. It is hoped that this database will help advance mobile passive B/BCIs for use in everyday settings.





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