IEEE journal of biomedical and health informatics
Sep 23, 2019
This paper presents a novel deep learning framework for the inter-patient electrocardiogram (ECG) heartbeat classification. A symbolization approach especially designed for ECG is introduced, which can jointly represent the morphology and rhythm of t...
International journal of neural systems
Sep 18, 2019
Human gait recognition is one of the most promising biometric technologies, especially for unobtrusive video surveillance and human identification from a distance. Aiming at improving recognition rate, in this paper we study gait recognition using de...
Electromyography-assisted optimization (EMGAO) approach is widely used to predict lumbar joint loads under various dynamic and static conditions. However, such approach uses numerous anthropometric, kinematic, kinetic, and electromyographic data in t...
IEEE journal of biomedical and health informatics
Sep 16, 2019
In this paper, deep belief net (DBN) was applied into the field of wearable-sensor based Chinese sign language (CSL) recognition. Eight subjects were involved in the study, and all of the subjects finished a five-day experiment performing CSL on a ta...
A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from multiple single-trial measurements. This is often accomplished by learning a simple, linear ...
IEEE journal of biomedical and health informatics
Sep 13, 2019
OBJECTIVE: We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introduced to functional network classification only very recently...
The severity of obstructive sleep apnea (OSA) is classified using apnea-hypopnea index (AHI). Accurate determination of AHI currently requires manual analysis and complicated registration setup making it expensive and labor intensive. Partially for t...
IEEE journal of biomedical and health informatics
Sep 11, 2019
With the development of deep learning in medical image analysis, decoding brain states from functional magnetic resonance imaging (fMRI) signals has made significant progress. Previous studies often utilized deep neural networks to automatically clas...
Computational intelligence and neuroscience
Sep 9, 2019
Fatigue driving can easily lead to road traffic accidents and bring great harm to individuals and families. Recently, electroencephalography- (EEG-) based physiological and brain activities for fatigue detection have been increasingly investigated. H...
Nonconvulsive epileptic seizures (NCSz) and nonconvulsive status epilepticus (NCSE) are two neurological entities associated with increment in morbidity and mortality in critically ill patients. In a previous work, we introduced a method which accura...