English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, proposed a new approach of combining the hybrid soft computing  technique called Adaptive Symlet Wavelet Transform (ASWT) filter. The  baseline wanders (BW) noise removal from an ECG signals to minimize  distortion of the S-T segment of the ECG signal specially that have high  sampling frequencies. Therefore, when using Symlet Wavelet Transform (SWT)  to analysis the ECG signal can cause problems to analysis, exclusively when  examining the content of the ECG signal at low-frequency such as S-T  segment. The corresponding frequency components of the approximation  coefficients at level number seven are (0-3.9) Hz. Since the BW frequency is  below 0.5 Hz and ST segment frequency between (0.67-4) Hz. The adaptive  filter with a unity reference signal used to remove the BW noise below 0.5  Hz from the lowest level of the approximation coefficient of the decomposed  ECG signal. The denoising output from adaptive filter and the output from  SWT (the other detail coefficients) will use as an input to ISWT for  reconstruction ECG signals with the remove BW signal. This method represents  a very effective filter for BW noise removal, as it does not need for any  computation process of reference point.

Adaptive Symlet filter based on ECG baseline wander removal