BMC medical informatics and decision making
Feb 21, 2020
BACKGROUND: The detection of Alzheimer's Disease (AD) in its formative stages, especially in Mild Cognitive Impairments (MCI), has the potential of helping the clinicians in understanding the condition. The literature review shows that the classifica...
This paper proposes an approach to accurately estimate the impedance value of a high impedance fault (HIF) and the distance from its fault location for a distribution system. Based on the three-phase voltage and current waveforms which are monitored ...
Auscultation of the lung is a conventional technique used for diagnosing chronic obstructive pulmonary diseases (COPDs) and lower respiratory infections and disorders in patients. In most of the earlier works, wavelet transforms or spectrograms have ...
Automatic or semi-automatic analysis of the equine electrocardiogram (eECG) is currently not possible because human or small animal ECG analysis software is unreliable due to a different ECG morphology in horses resulting from a different cardiac inn...
In recent years, there are several cost-effective intelligent sensing systems such as ultrasound imaging systems for visualizing the internal body structures of the body. Further, such intelligent sensing systems such as ultrasound systems have been ...
The stock market is known for its extreme complexity and volatility, and people are always looking for an accurate and effective way to guide stock trading. Long short-term memory (LSTM) neural networks are developed by recurrent neural networks (RNN...
Neural networks : the official journal of the International Neural Network Society
Dec 14, 2019
Electroencephalographic (EEG) recordings generate an electrical map of the human brain that are useful for clinical inspection of patients and in biomedical smart Internet-of-Things (IoT) and Brain-Computer Interface (BCI) applications. From a signal...
Electroencephalography (EEG) signals have been widely used to diagnose brain diseases for instance epilepsy, Parkinson's Disease (PD), Multiple Skleroz (MS), and many machine learning methods have been proposed to develop automated disease diagnosis ...
The International journal of neuroscience
Dec 4, 2019
We propose a convolutional neural network (CNN) based on wavelet for verifying the activation regions decided with statistical analysis. Because the functional magnetic resonance imaging (fMRI) data contains lots of noises, it is difficult to get th...
Due to growth in population, Individual persons with disabilities are increasing daily. To overcome the disability especially in Locked in State (LIS) due to Spinal Cord Injury (SCI), we planned to design four states moving robot from four imagery ta...