In this paper, a continuous non-occluding blood pressure (BP) prediction method is proposed using multiple photoplethysmogram (PPG) signals. In the new method, BP is predicted by a committee machine or ensemble learning framework comprising multiple ...
BACKGROUND: A seizure prediction system can detect seizures prior to their occurrence and allow clinicians to provide timely treatment for patients with epilepsy. Research on seizure prediction has progressed from signal processing analyses to machin...
IEEE journal of biomedical and health informatics
Aug 9, 2019
State-of-the-art electroencephalogram (EEG)-based emotion-classification works indicate that a personalized model may not be well exploited until sufficient labeled data are available, given a substantial EEG non-stationarity over days. However, it i...
In this study, a deep-transfer learning approach is proposed for the automated diagnosis of diabetes mellitus (DM), using heart rate (HR) signals obtained from electrocardiogram (ECG) data. Recent progress in deep learning has contributed significant...
In this letter, we propose two novel methods for four-class motor imagery (MI) classification using electroencephalography (EEG). Also, we developed a real-time health 4.0 (H4.0) architecture for brain-controlled internet of things (IoT) enabled envi...
Olive oil is an essential diet component in all Mediterranean countries having a considerable impact on the local economies, which are producing almost 90% of the world production. Therefore, the quality assessment of olive oil in terms of its acidit...
BACKGROUND: Major depressive disorder (MDD) is one of the leading causes of disability; however, current MDD diagnosis methods lack an objective assessment of depressive symptoms. Here, a machine learning approach to separate MDD patients from health...
Atrial fibrillation (AF) is the most common heart arrhythmia, and 12-lead electrocardiogram (ECG) is regarded as the gold standard for AF diagnosis. Highly accurate diagnosis of AF based on 12-lead ECG is valuable and remains challenging. In this pap...
International journal of neural systems
Aug 2, 2019
Epileptic seizures arise from synchronous firing of multiple spatially separated neural masses; therefore, many synchrony measures are used for seizure detection and characterization. However, synchrony measures reflect only the overall interaction s...