Empirical Mode Decomposition
Studies in this Category
Assessing the Effectiveness of Various Filtering Techniques on Seismocardiography Signals in Individuals with Valvular Heart Disease
This study tested different methods to clean heart vibration signals for better diagnosis of valve diseases, finding ICA to be the most effective at reducing noise while keeping the signal intact.
Advanced Fusion and Empirical Mode Decomposition-Based Filtering Methods for Breathing Rate Estimation from Seismocardiogram Signals
This study shows how heart vibration signals can be used to estimate breathing rate accurately without invasive procedures, using advanced signal processing techniques like EMD and fusion methods.
Comparison of Seismocardiography Based Heart Rate Measurement Method
This study shows that using advanced signal processing techniques, like jerk analysis, can make heart rate monitoring with chest vibrations more accurate, offering a simpler alternative to traditional methods like ECG.
Wearable ballistocardiogram and seismocardiogram systems for health and performance
This study shows how wearable sensors can track heart health by measuring vibrations caused by heartbeats, offering a low-cost way to monitor conditions like heart failure and optimize physical performance in challenging environments.