Wavelet Transform

Semantic Cluster14 Research Papers

Studies in this Category

ID: severe-aortic-stenosis-detection-using-seismocardiography2026

Severe aortic stenosis detection using seismocardiography

This study shows that chest vibrations measured by a small device can accurately detect severe heart valve disease, offering a low-cost alternative to traditional tests like echocardiography.

#scg#ecg#accelerometer

ID: assessing-the-effectiveness-of-various-filtering-techniques-on-seismocardiography-signals-in-individuals-with-valvular-heart-disease2025

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.

#scg

ID: lubdubdecoder-bringing-micro-mechanical-cardiac-monitoring-to-hearables2025

LubDubDecoder: Bringing Micro-Mechanical Cardiac Monitoring to Hearables

This study shows how regular earbuds can monitor heart health by detecting subtle vibrations linked to heartbeats, offering a convenient way to track cardiovascular health daily.

#scg#wearable#gcg

ID: a-wavelet-based-approach-for-motion-artifact-reduction-in-ambulatory-seismocardiography2024

A Wavelet-Based Approach for Motion Artifact Reduction in Ambulatory Seismocardiography

This study developed a method to clean heart vibration signals for wearable devices, making them more accurate even during walking, without needing extra sensors like ECG. This could improve heart monitoring in daily life and hospitals.

#scg#accelerometer

ID: enhancing-visual-seismocardiography-in-noisy-environments-with-adaptive-bidirectional-filtering-for-cardiac-health-monitoring2024

Enhancing visual seismocardiography in noisy environments with adaptive bidirectional filtering for Cardiac Health Monitoring

This study presents a new method to clean heart vibration signals for wearable devices, making heart monitoring more accurate even during movement, without needing traditional ECG wires.

#scg#accelerometer

ID: pulsatiomech-an-open-source-matlab-toolbox-for-seismocardiography-signal-processing2024

PulsatioMech: An Open-Source MATLAB Toolbox for Seismocardiography Signal Processing

This study presents a free MATLAB tool that helps researchers analyze heart vibrations (SCG signals) to better understand heart health and develop wearable monitoring devices.

#scg

ID: a-deep-learning-approach-to-using-wearable-seismocardiography-for-diagnosing-aortic-valve-stenosis-and-predicting-aortic-hemodynamics-obtained-by-4d-flow-mri2023

A deep learning approach to using wearable seismocardiography (SCG) for diagnosing aortic valve stenosis and predicting aortic hemodynamics obtained by 4D flow MRI

This study shows that wearable heart vibration sensors combined with AI can predict blood flow and diagnose aortic valve problems as accurately as advanced MRI scans, offering a cheaper and faster alternative for heart disease screening.

#scg#accelerometer#deep-learning

ID: introducing-the-electromechanical-risk-factor-score-derived-from-seismocardiography-for-estimating-the-likelihood-of-coronary-artery-disease2023

Introducing the Electromechanical Risk Factor Score Derived from Seismocardiography for Estimating the Likelihood of Coronary Artery Disease

This study developed a new heart vibration-based score that better detects coronary artery disease, reducing false positives compared to current methods.

#scg#accelerometer#deep-learning

ID: the-latest-progress-and-development-trend-in-the-research-of-ballistocardiography-and-seismocardiogram-in-the-field-of-health-care2021

The Latest Progress and Development Trend in the Research of Ballistocardiography (BCG) and Seismocardiogram (SCG) in the Field of Health Care

This study reviews how BCG and SCG technologies are being revived to monitor heart and health conditions, with potential applications in sleep and cardiovascular care. It calls for making these technologies more accessible and standardized for everyday use.

#scg#accelerometer#bcg

ID: discrete-wavelet-transforms-based-analysis-of-accelerometer-signals-for-continuous-human-cardiac-monitoring2021

Discrete Wavelet Transforms-Based Analysis of Accelerometer Signals for Continuous Human Cardiac Monitoring

This study shows how chest vibrations measured by accelerometers can detect heart activity using advanced wavelet algorithms, even without ECG. The methods work well in resting conditions but need improvement for noisy environments like breathing tasks.

#scg#accelerometer

ID: comparison-of-multiple-cardiac-signal-acquisition-technologies-for-heart-rate-variability-analysis2019

Comparison of multiple cardiac signal acquisition technologies for heart rate variability analysis

This study shows that a new sensor technology, PiPG, can measure heart rate variability almost as accurately as an ECG, making it a promising tool for monitoring heart health in various settings.

#scg#ecg#ppg

ID: accurate-and-consistent-automatic-seismocardiogram-annotation-without-concurrent-ecg2015

Accurate and consistent automatic seismocardiogram annotation without concurrent ECG

This study developed a method to analyze heart vibrations without needing ECG data, showing promise for affordable and standalone heart monitoring devices.

#scg#accelerometer

ID: wearable-seismocardiography2007

Wearable Seismocardiography

This study shows that wearable devices can use heart vibrations and AI to diagnose aortic valve problems and predict blood flow metrics as accurately as advanced MRI scans, offering a cheaper and faster alternative for heart health monitoring.

#scg#accelerometer#mri

ID: seismocardiography-waveform-identification-and-noise-analysis1991

Seismocardiography: waveform identification and noise analysis

The study examines how to clean and classify heart vibration signals (SCG) for better medical use, focusing on reducing noise and improving accuracy.

#scg