During cardiac arrhythmia, the heart frequency is an important physiological parameter that can be identified by analyzing electrocardiogram (ECG) signals. However, the accuracy of the frequency ...

AI-driven process monitoring enhances the qualification of additively manufactured stainless-steel parts. By analysing high-frequency welding current and voltage signals in both the time and frequency ...

Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States Vanderbilt Institute of Chemical Biology, Molecular Design and Synthesis Center, Vanderbilt University, ...

The National Institute of Standards and Technology's new cesium fountain clock is one of the most precise atomic clocks ever created. When you purchase through links on our site, we may earn an ...

Objective: This study aims to develop a multimodal deep learning-based stress detection method (MMFD-SD) using intermittently collected physiological signals from wearable devices, including ...

Abstract: The physiological behavior of the abductor pollicis brevis (APB) muscle during the early stages of fatigue is useful for subsequent clinical assessment of a pathologically altered muscle. In ...

Abstract: Prognostic and health management (PHM) technology is the use of a large amount of condition monitoring data and information, with the help of all kinds of fault model and artificial ...

This repository has been lightly modernized to run on current Python environments (Python 3.11) while preserving the original algorithmic logic from 2011. Key updates include: Environment pins: ...