Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Virginia R. de Sa"'
Publikováno v:
Frontiers in Human Neuroscience, Vol 12 (2018)
We used pattern classifiers to extract features related to recognition memory retrieval from the temporal information in single-trial electroencephalography (EEG) data during attempted memory retrieval. Two-class classification was conducted on corre
Externí odkaz:
https://doaj.org/article/f010364f41594557af831b2065a7f57e
Autor:
Virginia R. de Sa, Hooman Nezamfar, Büşra Tuğçe Susam, Kenneth D. Craig, Murat Akcakaya, Damaris Diaz, Jeannie S. Huang, Xiaojing Xu, Matthew S. Goodwin, Nathan T. Riek
Publikováno v:
IEEE Transactions on Biomedical Engineering. 69:422-431
Pain assessment in children continues to challenge clinicians and researchers, as subjective experiences of pain require inference through observable behaviors, both involuntary and deliberate. The presented approach supplements the subjective self-r
Publikováno v:
2022 10th International Winter Conference on Brain-Computer Interface (BCI).
Autor:
Xiaojing, Xu, Virginia R, de Sa
Publikováno v:
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
Pain is a personal, subjective experience, and the current gold standard to evaluate pain is the Visual Analog Scale (VAS), which is self-reported at the video level. One problem with the current automated pain detection systems is that the learned m
Autor:
Mahta Mousavi, Virginia R. de Sa
Publikováno v:
NER
Brain-computer interface (BCI) systems read and infer the user brain activity directly from the brain providing a means of communication and rehabilitation for patients in need. However, brain signals are known to be non-stationary and existing syste
Autor:
Virginia R. de Sa, Xiaojing Xu
Publikováno v:
FG
Although pain is widely recognized to be a multidimensional experience, it is typically measured by unidimensional patient self-reported visual analog scale (VAS). However, self-reported pain is subjective, difficult to interpret and sometimes imposs
Autor:
Priya eVelu, Virginia R de Sa
Publikováno v:
Frontiers in Neuroscience, Vol 7 (2013)
Neuroimaging studies provide evidence of cortical involvement immediately before and during gait and during gait-related behaviors such as stepping in place or motor imagery of gait. Here we attempt to perform single-trial classification of gait inte
Externí odkaz:
https://doaj.org/article/ef842eb046fc4500b0d0dbacec38a9d9
Autor:
Mahta Mousavi, Virginia R. de Sa
Publikováno v:
EMBC
Brain-computer interface (BCI) systems are proposed as a means of communication for locked-in patients. One common BCI paradigm is motor imagery in which the user controls a BCI by imagining movements of different body parts. It is known that imagini
Publikováno v:
Brain-Computer Interfaces. 4:74-86
In brain-computer interface (BCI) systems, the non-stationarity of brain signals is known to be a challenge for training robust classifiers as other brain processes produce signals that coincide wi...
Autor:
Büşra Tuğçe Susam, Kenneth D. Craig, Virginia R. de Sa, Jeannie S. Huang, Xiaojing Xu, Matthew S. Goodwin, Damaris Diaz, Murat Akcakaya
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030127374
AIH@IJCAI (Revised Selected Papers)
AIH@IJCAI (Revised Selected Papers)
Accurately determining pain levels in children is difficult, even for trained professionals and parents. Facial activity provides sensitive and specific information about pain, and computer vision algorithms have been developed to automatically detec