We performed a comparative study to select the efficient mother wavelet (MWT) basis
functions that optimally represent the signal characteristics of the electrical activity of the …

Background. The most common and successful technique for signal denoising with
nonstationary signals, such as electroencephalogram (EEG) and electrocardiogram (ECG) …

Stroke survivors are more prone to developing cognitive impairment and dementia.
Dementia detection is a challenge for supporting personalized healthcare. This study …

Nowadays, wavelet transform (WT) is widely used in the realm of signal denoising, has
proven a high effectiveness in terms of time and quality concerning denoising methods …

Electro Encephalo Gram (EEG) is a monitoring method used in biomedical and computer
science to understand brain activity. Therefore, the analysis and classification of these …

Characterizing dementia is a global challenge in supporting personalized health care. The
electroencephalogram (EEG) is a promising tool to support the diagnosis and evaluation of …

Abstract This study proposes Information Quality Ratio (IQR) as a new metric for mother
wavelet selection in real-world applications. In mother wavelet selection, common metrics …

Novelty detection scheme in bearing vibration signals of rotating system is investigated in
this article. One class support vector machine (OC-SVM) is used for novelty detection. It …

The design of multiple human activity recognition applications in areas such as healthcare,
sports and safety relies on wearable sensor technologies. However, when making decisions …

Denoising of a cargo-plane jet engine compressor vibration signal is investigated in this
article. Discrete wavelet transform and two families of Donoho–Johnston and parameter …