Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Sam Darvishi"'
Autor:
Simanto Saha, Khondaker A. Mamun, Khawza Ahmed, Raqibul Mostafa, Ganesh R. Naik, Sam Darvishi, Ahsan H. Khandoker, Mathias Baumert
Publikováno v:
Frontiers in Systems Neuroscience, Vol 15 (2021)
Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and
Externí odkaz:
https://doaj.org/article/30bde0e4a49b43aab3e42c4387bd2ba6
Publikováno v:
IEEE Journal of Translational Engineering in Health and Medicine, Vol 6, Pp 1-11 (2018)
There is evidence that 15–30% of the general population cannot effectively operate brain–computer interfaces (BCIs). Thus the BCI performance predictors are critically required to pre-screen participants. Current neurophysiological and psychologi
Externí odkaz:
https://doaj.org/article/4d3ac56c1e884e2a8f5994d6f7932782
Publikováno v:
Royal Society Open Science, Vol 4, Iss 8 (2017)
Restorative brain–computer interfaces (BCIs) have been proposed to enhance stroke rehabilitation. Restorative BCIs are able to close the sensorimotor loop by rewarding motor imagery (MI) with sensory feedback. Despite the promising results from ear
Externí odkaz:
https://doaj.org/article/c33e7c7b56614911987ea14fbbb2c1c0
Autor:
David M. Booth, Brandon Pincombe, Sam Darvishi, Gary Hanly, Kym Meaney, Peter Vincent Aquilina
Publikováno v:
ANZIAM Journal. 61:C273-C287
We investigate the use of a yellow-green filter to increase the signal-to-noise ratio (snr) in imaging photoplethysmography (iPPG) and test if high frame rate (HFR) video improves the accuracy of the derived heart rate variability (HRV). This pilot s
Autor:
Masashi Hamada, Brenton Hordacre, Ann-Maree Vallence, Sam Darvishi, Bahar Moezzi, Mitchell R. Goldsworthy, Michael C. Ridding, John C. Rothwell
Publikováno v:
Brain Stimulation, Vol 10, Iss 3, Pp 588-595 (2017)
Background The potential of non-invasive brain stimulation (NIBS) for both probing human neuroplasticity and the induction of functionally relevant neuroplastic change has received significant interest. However, at present the utility of NIBS is limi
Publikováno v:
IEEE Journal of Translational Engineering in Health and Medicine
There is evidence that 15–30% of the general population cannot effectively operate brain–computer interfaces (BCIs). Thus the BCI performance predictors are critically required to pre-screen participants. Current neurophysiological and psychologi
Autor:
Derek Abbott, Michael C. Ridding, Alireza Gharabaghi, Chadwick B. Boulay, Sam Darvishi, Mathias Baumert
Publikováno v:
Frontiers in Neuroscience
Motor imagery (MI) activates the sensorimotor system independent of actual movements and might be facilitated by neurofeedback. Knowledge on the interaction between feedback modality and the involved frequency bands during MI-related brain self-regul
Publikováno v:
Royal Society Open Science, Vol 4, Iss 8 (2017)
Royal Society Open Science
Royal Society Open Science
Restorative brain-computer interfaces (BCIs) have been proposed to enhance stroke rehabilitation. Restorative BCIs are able to close the sensorimotor loop by rewarding motor imagery (MI) with sensory feedback. Despite the promising results from early
Publikováno v:
EMBC
Brain computer interfaces (BCIs) enable human brains to interact directly with machines. Motor imagery based BCI (MI-BCI) encodes the motor intentions of human agents and provides feedback accordingly. However, 15–30% of people are not able to perf
Publikováno v:
NER
Brain computer interfaces (BCI) are used for communication and rehabilitation. One of the main categories of BCI techniques is motor imagery based BCI (MI-BCI). A large number of studies have focused on machine learning approaches to optimize MI-BCI