Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Reza Foodeh"'
Publikováno v:
IEEE Access, Vol 9, Pp 148756-148770 (2021)
In this paper, a novel fully-automated state-based decoding method has been proposed for continuous decoding problems in brain-machine interface (BMI) systems, called Gaussian mixture of model (GMM)-assisted PLS (GMMPLS). In contrast to other state-b
Externí odkaz:
https://doaj.org/article/f15419abfc554b26a732ae91211a69ae
Publikováno v:
IEEE Access, Vol 9, Pp 148756-148770 (2021)
In this paper, a novel fully-automated state-based decoding method has been proposed for continuous decoding problems in brain-machine interface (BMI) systems, called Gaussian mixture of model (GMM)-assisted PLS (GMMPLS). In contrast to other state-b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97fc936c2911512be914b6231bb07de1
https://ieeexplore.ieee.org/document/9585446/
https://ieeexplore.ieee.org/document/9585446/
Publikováno v:
Neuroinformatics. 18:465-477
Continuous decoding is a crucial step in many types of brain-computer interfaces (BCIs). Linear regression techniques have been widely used to determine a linear relation between the input and desired output. A serious issue in this technique is the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::034e2613506dd00c0dfe956314bc44f0
https://doi.org/10.1007/s12021-020-09455-x
https://doi.org/10.1007/s12021-020-09455-x
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26:18-25
A local field potential (LFP) signal is an alternative source to neural action potentials for decoding kinematic and kinetic information from the brain. Here, we demonstrate that the better extraction of force-related features from multichannel LFPs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d998bc39d8430b91750c7dbb9ecd854
https://doi.org/10.1109/tnsre.2017.2751579
https://doi.org/10.1109/tnsre.2017.2751579
Publikováno v:
Journal of Neuroscience Methods. 358:109182
Background Removing artifacts is a prerequisite step for the analysis of electroencephalographic (EEG) signals. Artifacts appear in both time and time-frequency as well as spatial (multi-channel) domains. New methods Here, we introduce two novel meth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64e8f0dad6268f331b6245c11ef1ff89
https://doi.org/10.1016/j.jneumeth.2021.109182
https://doi.org/10.1016/j.jneumeth.2021.109182
Publikováno v:
Australasian physicalengineering sciences in medicine.
The development of brain-computer interface (BCI) systems is an important approach in brain studies. Control of communication devices and prostheses in real-world scenarios requires complex movement parameters. Decoding a variety of neural signals ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a2ec3c3f79776f3af614b7b21ecf0d5
https://pubmed.ncbi.nlm.nih.gov/31898242
https://pubmed.ncbi.nlm.nih.gov/31898242
Publikováno v:
Journal of Neuroscience Methods. 350:109022
Background Brain-computer interfaces (BCIs) seek to establish a direct connection from brain to computer, to use in applications such as motor prosthesis control, control of a cursor on the monitor, and so on. Hence, the accuracy of movement decoding
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f53f82ee6e2ca7ca4708acc42bfab897
https://doi.org/10.1016/j.jneumeth.2020.109022
https://doi.org/10.1016/j.jneumeth.2020.109022
Publikováno v:
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 25(8)
In this paper a novel automated and unsupervised method for removing artifacts from multichannel field potential signals is introduced which can be used in brain computer interface (BCI) applications. The method, which is called minimum noise estimat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20006e5e0fc6f28f9deee2efa10ad7d8
https://pubmed.ncbi.nlm.nih.gov/28113378
https://pubmed.ncbi.nlm.nih.gov/28113378