The spectral distribution of energy varies between normal ECGs and those from patients post infarct or with ventricular hypertrophies. This suggests that discriminating between normal and abnormal conditions may be possible on the basis of differences in the distribution of spectral energy. We compare a reduced Discrete Wavelet Transform characterisation of an ECG QRS complex using three differ...

A new adaptive Packet algorithm based on Discrete Cosine harmonic wavelet transform (DCHWT), (DCAHWP) has been proposed. This is realized by the Discrete Cosine Harmonic Wavelet transform (DCHTWT) which exploits the good properties of DCT viz., energy compaction (low leakage), frequency resolution and computational simplicity due its real nature, compared to those of DFT and its harmonic wavele...

introduction: spect is a diagnostic imaging technique the main disadvantage of which is the existence of poisson noise. so far, different methods have been used by scientists to improve spect images. the wavelet transform is a new method for de-noising which is widely used for noise reduction and quality enhancement of images. the purpose of this paper is evaluation of noise reduction in spect ...

This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...

Objective. The aim is to research the extraction of R waves and ST segment feature points based on Wavelet Transform (WT), and propose an algorithm used to recognize the shapes of ST segment. Method. First, electrocardiogram (ECG) signals are decomposed by WT algorithm using a dyadic spline wavelet. Based on the relation between the feature points of ECG signals and the maximum pairs of the sig...

In recent years, the dynamic behavior of solid structure defects is extremely important as a small defect that is growing may well be more significant than a larger stable defect. Acoustic Emission (AE) is the method used to investigate the behavior of defects under stress. The importance of the AE is to determine the source location when it occurs. It is a real time monitoring technique. Ident...

The P300 response is conventionally obtained by averaging the responses to the task-relevant (target) stimuli of the oddball paradigm. However, it is well known that cognitive ERP components show a high variability due to changes of cognitive state during an experimental session. With simple tasks such changes may not be demonstrable by the conventional method of averaging the sweeps chosen acc...

The work compares the Raa (Area/Amplitude Ratio) with Instantaneous Mean Scale (IMS) and Instantaneous Median Scale (IMedS) both computed via Wavelet Transform (WT) in a fatiguing contraction (Biceps Brachii, 50% MVC, (six females, six males), computed on different epochs (100, 200, 500 ms) from the surface electromyogram (SEMG) and mechanomyogram (MMG) from same motor territory. All three para...

This paper proposes a novel pavement transverse crack detection model based on time–frequency analysis and convolutional neural networks. The accelerometer smartphone installed in the vehicle collect vibration response between wheel road, such as cracks, manholes, normal pavement. Since original signal can only contain one-dimensional domain (time–acceleration). Time–frequency analysis, includi...