AIMC Topic: Electroencephalography
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[Automatic Sleep Staging Method Based on Energy Features and Least Squares Support Vector Machine Classifier].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Jun 1, 2015
The research of sleep staging is not only the basis of diagnosing sleep related diseases, but also the precondition of evaluating sleep quality, and has important clinical significance. In recent years, the research of automatic sleep staging based o...
[Study on Sleep Staging Based on Support Vector Machines and Feature Selection in Single Channel Electroencephalogram].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Jun 1, 2015
Sleep electroencephalogram (EEG) is an important index in diagnosing sleep disorders and related diseases. Manual sleep staging is time-consuming and often influenced by subjective factors. Existing automatic sleep staging methods have high complexit...
An EEG/EOG-based hybrid brain-neural computer interaction (BNCI) system to control an exoskeleton for the paralyzed hand.
Biomedizinische Technik. Biomedical engineering
Jun 1, 2015
The loss of hand function can result in severe physical and psychosocial impairment. Thus, compensation of a lost hand function using assistive robotics that can be operated in daily life is very desirable. However, versatile, intuitive, and reliable...
Convergent Cross Mapping: Basic concept, influence of estimation parameters and practical application.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jan 1, 2015
In neuroscience, data are typically generated from neural network activity. Complex interactions between measured time series are involved, and nothing or only little is known about the underlying dynamic system. Convergent Cross Mapping (CCM) provid...
Seizure detection using regression tree based feature selection and polynomial SVM classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jan 1, 2015
This paper presents a novel patient-specific algorithm for detection of seizures in epileptic patients with low hardware complexity and low power consumption. In the proposed approach, we first compute the spectrogram of the input fragmented EEG sign...
Reverse bi-orthogonal wavelets & fuzzy classifiers for the automatic detection of spike waves in the EEG of the hypoxic ischemic pre-term fetal sheep.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jan 1, 2015
There exists a 6-8 hour window of opportunity for the treatment of perinatal Hypoxic-Ischemic Encephalopathy (HIE) following the original insult after which significant irreversible brain injury manifests leading to debilitating neurological conditio...
Cooperation driven coherence: Brains working hard together.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jan 1, 2015
The current study aims to look at the difference in coupling of EEG activity of participant pairs while they perform a cooperative, concurrent, independent yet different task at high and low difficulty levels. Participants performed the National Aero...
Assessing neuro-motor recovery in a stroke survivor with high-resolution EEG, robotics and Virtual Reality.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jan 1, 2015
One post-stroke patient underwent neuro-motor rehabilitation of one upper limb with a novel system combining a passive robotic device, Virtual Reality training applications and high resolution electroencephalography (HR-EEG). The outcome of the clini...
On the use of convolutional neural networks and augmented CSP features for multi-class motor imagery of EEG signals classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jan 1, 2015
Learning the deep structures and unknown correlations is important for the detection of motor imagery of EEG signals (MI-EEG). This study investigates the use of convolutional neural networks (CNNs) for the classification of multi-class MI-EEG signal...
Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2015
BACKGROUND: Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diver...
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