An efficient ECG signals denoising technique based on the combination of particle swarm optimisation and wavelet transform.

During the recording time, electrocardiogram (ECG) signals are subject to multiple artefact noises, such as muscle activity, white Gaussian noise (WGN), baseline wander, and power line interference (PLI). Therefore, pre-processing of ECG signals is essential to eliminate these artefacts and to obtain efficient ECG features. Many approaches have been proposed for removing ECG noises, including ECG signal denoising using wavelet transform (WT).

Mucocutaneous manifestations in human immunodeficiency virus (HIV)-infected patients in Nouakchott, Mauritania.

Background: Mucocutaneous manifestations are one of the first clinical signs in patients infected with human immunodeficiency virus (HIV). To the best of our knowledge, there has been no previous study describing dermatologic manifestations in Mauritanians infected with HIV. The aim of the present study was to determine the profiles of mucocutaneous manifestations in relation to CD T cell count in HIV-positive Mauritanian patients.