Accurate muscle activity onset detection is an essential prerequisite for many applications of surface electromyogram (EMG). This study presents an unsupervised EMG learning framework based on a sequential Gaussian mixture model (GMM) to detect muscl...
Automatic processing of magnetic resonance images is a vital part of neuroscience research. Yet even the best and most widely used medical image processing methods will not produce consistent results when their input images are acquired with differen...
With the rapid increase of 3-dimensional (3D) content, considerable research related to the 3D human factor has been undertaken for quantitatively evaluating visual discomfort, including eye fatigue and dizziness, caused by viewing 3D content. Variou...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 29, 2015
Slow feature analysis (SFA) is a dimensionality reduction technique which has been linked to how visual brain cells work. In recent years, the SFA was adopted for computer vision tasks. In this paper, we propose an exact kernel SFA (KSFA) framework f...
Computational intelligence and neuroscience
Apr 21, 2015
This paper presents an investigation aimed at drastically reducing the processing burden required by motor imagery brain-computer interface (BCI) systems based on electroencephalography (EEG). In this research, the focus has moved from the channel to...
The most common approach to assess fetal well-being during delivery is monitoring of fetal heart rate and uterine contractions-the cardiotocogram (CTG). Nevertheless, 40 years since the introduction of CTG to clinical practice, its evaluation is stil...
Myocardial Infarction (MI) or acute MI (AMI) is one of the leading causes of death worldwide. Precise and timely identification of MI and extent of muscle damage helps in early treatment and reduction in the time taken for further tests. MI diagnosis...
This paper presents two new concepts for discrimination of signals of different complexity. The first focused initially on solving the problem of setting entropy descriptors by varying the pattern size instead of the tolerance. This led to the search...
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Automatic detection of AF could substantially help in early diagnosis, management and co...
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