Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Mohammad Moghadamfalahi"'
Autor:
Paula Gonzalez-Navarro, Basak Celik, Mohammad Moghadamfalahi, Murat Akcakaya, Melanie Fried-Oken, Deniz Erdoğmuş
Publikováno v:
Frontiers in Human Neuroscience, Vol 15 (2022)
Error related potentials (ErrP), which are elicited in the EEG in response to a perceived error, have been used for error correction and adaption in the event related potential (ERP)-based brain computer interfaces designed for typing. In these typin
Externí odkaz:
https://doaj.org/article/e60d7ca54e1444f3bacfdd696b1a5d33
Autor:
Paula Gonzalez-Navarro, Basak Celik, Mohammad Moghadamfalahi, Murat Akcakaya, Melanie Fried-Oken, Deniz Erdoğmuş
Publikováno v:
Frontiers in Human Neuroscience, Vol 15 (2022)
Error related potentials (ErrP), which are elicited in the EEG in response to a perceived error, have been used for error correction and adaption in the event related potential (ERP)-based brain computer interfaces designed for typing. In these typin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2f4503f1ffb8bced9c8d85b9ab48353
https://pubmed.ncbi.nlm.nih.gov/35145386
https://pubmed.ncbi.nlm.nih.gov/35145386
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26:1835-1844
Augmentative and alternative communication (AAC) is typically used by people with severe speech and physical disabilities (SSPI) and is one of the main application areas for brain computer interface (BCI) technology. The target population includes pe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88dcf932a6e160a160e78ce14b9460f1
https://doi.org/10.1109/tnsre.2018.2859432
https://doi.org/10.1109/tnsre.2018.2859432
Publikováno v:
Signal Processing. 131:333-343
Multichannel electroencephalography (EEG) is widely used in non-invasive brain computer interfaces (BCIs) for user intent inference. EEG can be assumed to be a Gaussian process with unknown mean and autocovariance, and the estimation of parameters is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdcdcdb8c96e8f734eade4950cf95c38
https://doi.org/10.1016/j.sigpro.2016.08.001
https://doi.org/10.1016/j.sigpro.2016.08.001
Publikováno v:
Biomedical signal processing and control. 39
Noninvasive EEG (electroencephalography) based auditory attention detection could be useful for improved hearing aids in the future. This work is a novel attempt to investigate the feasibility of online modulation of sound sources by probabilistic de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0a75b9c5ecb84640284a278452d003e
https://pubmed.ncbi.nlm.nih.gov/31118975
https://pubmed.ncbi.nlm.nih.gov/31118975
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030206512
NFM
NFM
Reinforcement learning (RL) is emerging as a powerful machine learning paradigm to develop autonomous safety critical systems; RL enables the systems to learn optimal control strategies by interacting with the environment. However, there is also wide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::579d3e99ea9f8a8fd93d406b826ae76c
https://doi.org/10.1007/978-3-030-20652-9_22
https://doi.org/10.1007/978-3-030-20652-9_22
Autor:
Yeganeh M. Marghi, Murat Akcakaya, Paula Gonzalez-Navarro, Bruna Girvent, Deniz Erdogmus, Mohammad Moghadamfalahi, James P. McLean, Fernando Quivira
Publikováno v:
Signal Processing and Machine Learning for Brain-Machine Interfaces ISBN: 9781785613982
Electroencephalography (EEG)-based brain-computer interfaces (BCIs) are developed to provide access channels for alternative communication and control systems to people with severe speech and physical impairments. Designs that exploit evoked response
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7617f88e44bf3f92c8cf5a5193c017cd
https://doi.org/10.1049/pbce114e_ch10
https://doi.org/10.1049/pbce114e_ch10
Publikováno v:
Signal Processing and Machine Learning for Biomedical Big Data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3699988460ed37236390f5fd5e89a741
https://doi.org/10.1201/9781351061223-6
https://doi.org/10.1201/9781351061223-6
Autor:
Deniz Erdogmus, Hooman Nezamfar, Marzieh Haghighi, Mohammad Moghadamfalahi, Seyed Sadegh Mohseni Salehi
Publikováno v:
EMBC
Noninvasive brain computer interfaces (BCI), and more specifically Electroencephalography (EEG) based systems for intent detection need to compensate for the low signal to noise ratio of EEG signals. In many applications, the temporal dependency info
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c72900b58bf2a4b279f8a76b26cc6f7
https://doi.org/10.1109/embc.2017.8037481
https://doi.org/10.1109/embc.2017.8037481