PulsatioMech: An Open-Source MATLAB Toolbox for Seismocardiography Signal Processing
Executive Summary
This paper introduces PulsatioMech, an open-source MATLAB toolbox designed for seismocardiography (SCG) signal processing. The toolbox includes modules for signal filtering, beat averaging, spectral analysis, and advanced feature generation, such as multifractal analysis and autoregressive coefficients. It aims to standardize SCG analysis, facilitate reproducibility, and promote research in wearable cardiac monitoring applications.
Answer Machine Insights
Q: What is the primary purpose of the PulsatioMech toolbox?
To assist researchers in analyzing SCG signals with minimal effort in signal processing and coding, while promoting reproducibility.
This toolbox is designed to assist users in analyzing SCG signals without the need to devote significant effort into signal processing and coding tasks.
Q: What advanced signal processing techniques are included in the toolbox?
The toolbox includes multifractal analysis, autoregressive coefficients via Burg's method, and wavelet-based feature extraction.
One of the central innovations in this toolbox is the introduction of multifractal analysis and other advanced signal processing techniques for SCG signals.
Key Results
The toolbox introduces multifractal analysis to distinguish between stressed and relaxed heartbeats based on SCG signals.
It provides a standardized platform for SCG signal processing, including filtering, beat averaging, and spectral analysis.
Clinical Snapshot
Evidence Rating
Relevance
high Priority