Electromyography (EMG) signal is the muscle electrical activity. Electromyography is a technique for detecting and recording the electrical potential generated by muscle cells. This EMG signals are used in medical professionals to determine specific disorders. This paper basically deals with the analysis of different electromyography signals (NOR & MYO). In this paper, new method for classifica...

introduction: with increasing production of health information, information technologies have been used for better management and usage of such data. this enormous increase in gathering and storing of information and widespread accessibility also concerns individuals regarding privacy and security of information. this research is concerned with this issue due to decisions on establishing indivi...

There exist different methods to analyze and study biomedical signals. Some of these methods are based on medical imaging, involving Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Nuclear Scintigraphy, etc. This techniques show the image of a specific part of the human body. But there exits other methods which study the different signals based in 1-dimensional analysis, such as Ele...

We show that functional near infrared spectroscopy signals can monitor task-related cerebral hemodynamic response. We detect periodicities in the near infared spectroscopy signals and show that the estimated periods are consistent across multiple detectors and subjects, despite the jittered periodicity of the stimuli sequence that is used in a target categorization experiment. ©2003 American So...

Single molecule detection, sequencing and conformational mapping of aptamers are important for improving medical and biosensing technologies and for better understanding of biological processes at the molecular level. We obtain vibrational signals of single aptamers immobilized on gold substrates using tip-enhanced Raman spectroscopy (TERS). We compare topographic and optical signals and invest...

In this paper we will review the pattern recognition by wavelet transform in the way that it is applied in medical diagnosis and we will discuss about the idea of wavelet networks as a classifier of vital signals. For example, this method can be used for resolution of preprocessed signals to determine the people who subject to exacerbation of Ventricular Tachycardia (VT). Keywords-component; wa...

Principal Component Analysis (PCA) is a classical technique in statistical data analysis, feature extraction and data reduction, aiming at explaining observed signals as a linear combination of orthogonal principal components. Independent Component Analysis (ICA) is a technique of array processing and data analysis, aiming at recovering unobserved signals or 'sources' from observed mixtures, ex...

sleep stages classification is one of the most important methods for diagnosis in psychiatry and neurology. in this paper, a combination of three kinds of classifiers are proposed which classify the eeg signal into five sleep stages including awake, n-rem (non-rapid eye movement) stage 1, n-rem stage 2, n-rem stage 3 and 4 (also called slow wave sleep), and rem. twenty-five all night recordings...

background: epilepsy is a severe disorder of the central nervous system that predisposes  the person to recurrent seizures. fifty million people worldwide suffer from  epilepsy; after alzheimer's and stroke, it is the third widespread nervous disorder. objective: in this paper, an algorithm to detect the onset of epileptic seizures  based on the analysis of brain electrical signals (eeg) has be...