Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Nesma Houmani"'
Autor:
Katia Andrade, Nesma Houmani, Thomas Guieysse, Solofo Razafimahatratra, André Klarsfeld, Gérard Dreyfus, Bruno Dubois, François Vialatte, Takfarinas Medani
Publikováno v:
Journal of Integrative Neuroscience, Vol 23, Iss 3, p 67 (2024)
Background: Electroencephalography (EEG) stands as a pivotal non-invasive tool, capturing brain signals with millisecond precision and enabling real-time monitoring of individuals’ mental states. Using appropriate biomarkers extracted from these EE
Externí odkaz:
https://doaj.org/article/14bc0110a5e34bd3bcb6f27f61a130b4
Autor:
Lorenzo Hermez, Abdelghani Halimi, Nesma Houmani, Sonia Garcia-Salicetti, Omar Galarraga, Vincent Vigneron
Publikováno v:
Sensors, Vol 23, Iss 14, p 6566 (2023)
This study addresses the characterization of normal gait and pathological deviations induced by neurological diseases, considering knee angular kinematics in the sagittal plane. We propose an unsupervised approach based on Dynamic Time Warping (DTW)
Externí odkaz:
https://doaj.org/article/4bed1d9e326a4264a90eee71ea6fcc4a
Publikováno v:
Bioengineering, Vol 9, Iss 8, p 375 (2022)
This work proposes a decision-aid tool for detecting Alzheimer’s disease (AD) at an early stage, based on the Archimedes spiral, executed on a Wacom digitizer. Our work assesses the potential of the task as a dynamic gesture and defines the most pe
Externí odkaz:
https://doaj.org/article/e685fd558dc9496ca7593765789529a2
Publikováno v:
Bioengineering, Vol 9, Iss 2, p 62 (2022)
This study addresses brain network analysis over different clinical severity stages of cognitive dysfunction using electroencephalography (EEG). We exploit EEG data of subjective cognitive impairment (SCI) patients, mild cognitive impairment (MCI) pa
Externí odkaz:
https://doaj.org/article/7d6490b4486f49c390567fc527387d0f
Publikováno v:
Entropy, Vol 23, Iss 11, p 1553 (2021)
This work addresses brain network analysis considering different clinical severity stages of cognitive dysfunction, based on resting-state electroencephalography (EEG). We use a cohort acquired in real-life clinical conditions, which contains EEG dat
Externí odkaz:
https://doaj.org/article/2450386c292a42efb9d927022d59909c
Publikováno v:
Sensors, Vol 20, Iss 3, p 933 (2020)
We aim at enhancing personal identity security on mobile touch-screen sensors by augmenting handwritten signatures with specific additional information at the enrollment phase. Our former works on several available and private data sets acquired on d
Externí odkaz:
https://doaj.org/article/ecbc15ac2de444e9bf70972851ff4e4c
Autor:
Nesma Houmani, François Vialatte, Esteve Gallego-Jutglà, Gérard Dreyfus, Vi-Huong Nguyen-Michel, Jean Mariani, Kiyoka Kinugawa
Publikováno v:
PLoS ONE, Vol 13, Iss 3, p e0193607 (2018)
This study addresses the problem of Alzheimer's disease (AD) diagnosis with Electroencephalography (EEG). The use of EEG as a tool for AD diagnosis has been widely studied by comparing EEG signals of AD patients only to those of healthy subjects. By
Externí odkaz:
https://doaj.org/article/cf4f6da3da3b443898f868e6934e3dea
Autor:
Katia Andrade, Thomas Guieysse, Solofo Razafimahatratra, Nesma Houmani, André Klarsfeld, Gérard Dreyfus, Bruno Dubois, Takfarinas Medani, François Vialatte
BackgroundElectroencephalography (EEG) is a non-invasive method that records the brain signals with time resolution in the millisecond range, thereby allowing the monitoring of subjects’ mental states in real time. Using appropriate biomarkers extr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c61a79835b1c5277abb88d83f909fd68
https://doi.org/10.1101/2022.09.26.509227
https://doi.org/10.1101/2022.09.26.509227
N°339 – A multi-scale brain connectivity analysis of electroencephalography signals for AD detection
Autor:
Nesma Houmani, Majd Abazid, Jerome Boudy, Bernadette Dorizzi, Jean Mariani, Kiyoka Kinugawa Bourron
Publikováno v:
Clinical Neurophysiology. 150:e178
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9db1e2f0caf4f0bc26d0994fc6d297a5
https://doi.org/10.1016/j.clinph.2023.03.314
https://doi.org/10.1016/j.clinph.2023.03.314
Publikováno v:
Bioengineering; Volume 9; Issue 8; Pages: 375
This work proposes a decision-aid tool for detecting Alzheimer’s disease (AD) at an early stage, based on the Archimedes spiral, executed on a Wacom digitizer. Our work assesses the potential of the task as a dynamic gesture and defines the most pe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::e5b715934a15c5c0cb6a67bcf7b91198