Common Practices in Clinical Electroencephalography
Korean Journal of Clinical Laboratory Science, 2021 Electroencephalography (EEG) provides the most accurate and quickest diagnosis of epilepsy. It is also an important examination for the real-time evaluation of brain function and seizures, no matter where.
Soon-Chul Hyun, Dongyeop Kim
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Frontiers in Systems Neuroscience, 2020 Dynamic functional connectivity (DFC) was established in the past decade as a potent approach to reveal non-trivial, time-varying properties of neural interactions – such as their multifractality or information content –, that otherwise remain hidden ...
Frigyes Samuel Racz +3 more
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Supervised ANN vs. unsupervised SOM to classify EEG data for BCI: why can GMDH do better? [PDF]
, 2013 Construction of a system for measuring the brain activity (electroencephalogram (EEG)) and recognising thinking patterns comprises significant challenges, in addition to the noise and distortion present in any measuring technique.
al-Ketbi, Omar, Conrad, Marc
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International Journal of Distributed Sensor Networks, 2018 Wearable electroencephalography systems of out-of-hospital can both provide complementary recordings and offer several benefits over long-term monitoring. However, several limitations were present in these new-born systems, for example, uncomfortable for
Qing Zhang +9 more
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Time-varying parametric modelling and time-dependent spectral characterisation with applications to EEG signals using multi-wavelets [PDF]
, 2008 A new time-varying autoregressive (TVAR) modelling approach is proposed for nonstationary signal processing and analysis, with application to EEG data modelling and power spectral estimation.
Billings, S.A., Liu, J., Wei, H.L.
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AR-PCA-HMM approach for sensorimotor task classification in EEG-based brain-computer interfaces [PDF]
, 2010 We propose an approach based on Hidden Markov models (HMMs) combined with principal component analysis (PCA) for classification of four-class single trial motor imagery EEG data for brain computer interfacing (BCI) purposes. We extract autoregressive (AR)
Argunsah, Ali Ozgur +3 more
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Protocol for electrophysiological monitoring of carotid endarterectomies. [PDF]
, 2010 Near zero stroke rates can be achieved in carotid endarterectomy (CEA) surgery with selective shunting and electrophysiological neuromonitoring. though false negative rates as high as 40% have been reported.
Di Giorgio, Anthony M +4 more
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Dissociation of Cerebral Blood Flow and Femoral Artery Blood Pressure Pulsatility After Cardiac Arrest and Resuscitation in a Rodent Model: Implications for Neurological Recovery. [PDF]
, 2020 Background Impaired neurological function affects 85% to 90% of cardiac arrest (CA) survivors. Pulsatile blood flow may play an important role in neurological recovery after CA.
Akbari, Yama +6 more
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Laserlight visual cueing device for freezing of gait in Parkinson's disease: a case study of the biomechanics involved [PDF]
, 2015 Background: Freezing of gait (FOG) is a serious gait disorder affecting up to two-thirds of people with Parkinson's disease (PD). Cueing has been explored as a method of generating motor execution using visual transverse lines on the floor.
B. Evans +7 more
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An Accurate Sleep Stages Classification Method Based on State Space Model
IEEE Access, 2019 The classification of sleep stages is the process which helps to evaluate the quality of sleep and detect the sleep related disorders. Through analyzing the electroencephalography, the sleep stages can be discriminated manually by specialists.
Huaming Shen +4 more
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