Electroencephalogram (EEG) is one of the most powerful tools that offer valuable
information related to different abnormalities in the human brain. One of these abnormalities …

The application of machine learning techniques in medicine and biomedicine has shown a
rising trend and corresponding promising results. Several machine learning techniques …

A noise-aware version of support vector machines is utilized for feature selection in this
paper. Combining this method and sequential backward search (SBS), a new algorithm for …

Electroencephalogram (EEG) to detect epilepsy seizures in their early stages. Epilepsy
seizure is a severe neurological disease. Practitioners continue to rely on manual testing of …

Looking back, I still recall the first program written by one of the classmates. We were just a
bunch of young students listening to the professor teaching us how to program a problem for …

The Electrocardiogram is a tool used to access the electrical recording and muscular
function of the heart and in last few decades it is extensively used in the investigation and …

In this paper, a convenience healthcare monitoring system and a real-time arrhythmia or
abnormal ECG detection algorithm are developed. Performance analysis on R-peak …

The electrocardiogram (ECG) is the most clinically accepted diagnostic tool used by
physicians for interpreting the functional activity of the heart. The existing ECG machines …

In this paper, a packet generator using a pattern matching algorithm for real-time abnormal
heartbeat detection is proposed. The packet generator creates a very small data packet …

In this research a new approach for human action recognition is proposed. At first, local
space-time features extracted which recently becomes a popular video representation …