Stroke Volume
Studies in this Category
Seismocardiography Pig Hypovolemia Dataset for Signal Quality Indexing and Validated Cardiac Timings
This study provides a high-quality dataset of heart vibrations from pigs, helping researchers develop better tools for tracking heart health using wearable sensors.
Seismocardiography-based estimation of hemodynamic parameters during submaximal ergometer test
This study shows that a wearable chest sensor can estimate heart function during exercise recovery, but struggles with accuracy during active cycling due to motion. It highlights the potential for simple, non-invasive heart monitoring in low-motion settings.
Digital Twin-Based Investigation of Seismocardiogram Sensitivity to Tissue Mechanics and Myocardial Motion
This study shows how personalized computer models based on CT scans can simulate heart vibrations (SCG) and improve non-invasive heart monitoring by accounting for individual anatomy and tissue properties.
Seismocardiograph Monitoring Using SMS Fiber Structure with PDMS Enclosure
This study developed a fiber-optic heart monitoring system that is highly accurate and protected by a special material, making it more reliable and practical for detecting heart vibrations.
Seismocardiography and echocardiography: the correlation in the systolic complex
This study shows that chest vibrations (SCG) can detect heart function changes and correlate with ultrasound results, offering a simpler way to monitor heart health at home or in clinics.
Smartphone-Derived Seismocardiography: Robust Approach for Accurate Cardiac Energy Assessment in Patients with Various Cardiovascular Conditions
This study shows that smartphones can reliably measure heart vibrations to assess cardiac energy, making it easier for patients to monitor their heart health at home.
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.
Synthetic Seismocardiography Signal Generation by a Generative Adversarial Network
Researchers used AI to create realistic heart vibration signals, helping scientists train heart-monitoring systems without needing expensive patient data collection.
Accuracy of a Clinical Applicable Method for Prediction of VO2max Using Seismocardiography
This study shows that a chest vibration-based method (SCG) can accurately predict fitness levels (VO2max) in healthy adults, potentially offering a simpler alternative to traditional exercise tests.
Wearable Seismocardiography‐Based Assessment of Stroke Volume in Congenital Heart Disease
This study shows that a wearable device using chest vibrations and heart signals can estimate blood flow in children with heart defects, offering a way to monitor heart health remotely and affordably.
Assessment of left ventricular twist by 3D ballistocardiography and seismocardiography compared with 2D STI echocardiography in a context of enhanced inotropism in healthy subjects
This research shows that vibrations from the heart, measured using wearable sensors, can predict heart function and twisting motion more accurately than traditional methods, offering a new way to monitor heart health remotely.
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.
Detecting Aortic Valve-Induced Abnormal Flow with Seismocardiography and Cardiac MRI
This research shows that chest vibrations measured by SCG can detect abnormal heart valve flow, offering a quick and affordable way to identify heart issues compared to MRI scans.
Cardiovascular adaptation to simulated microgravity and countermeasure efficacy assessed by ballistocardiography and seismocardiography
This research shows that portable devices using body vibrations can track heart health changes during simulated space conditions and prove the benefits of exercise in preventing heart deconditioning.
Non-Invasive Wearable Patch Utilizing Seismocardiography for Peri-Operative Use in Surgical Patients
This study shows that a wearable patch can accurately monitor heart function during and after surgery, offering a non-invasive alternative to traditional methods.
Influence of sympathetic activation on myocardial contractility measured with ballistocardiography and seismocardiography during sustained end-expiratory apnea
This study shows that heart vibrations measured during breath-holding can reveal changes in nerve activity linked to sleep disorders, offering a new way to monitor heart health non-invasively.
Quantification of cardiac kinetic energy and its changes during transmural myocardial ischemia assessed by multi-dimensional seismocardiography
This research shows how a vibration-based heart monitoring system can track heart damage during a heart attack and recovery, offering a new way to measure heart function remotely and non-invasively.
Accurate Detection of Dobutamine-induced Haemodynamic Changes by Kino-Cardiography: A Randomised Double-Blind Placebo-Controlled Validation Study
This study shows that a wearable device measuring body vibrations can accurately track heart function changes caused by medication, offering a new way to monitor heart health non-invasively.
Comparison of Different Methods for Estimating Cardiac Timings: A Comprehensive Multimodal Echocardiography Investigation
This study shows that chest vibrations (SCG) can measure heart function more accurately than traditional methods, paving the way for wearable heart monitors.
Recent Advances in Seismocardiography
This study reviews how SCG, a method to measure heart vibrations, is improving with new sensors and AI, showing promise for diagnosing heart conditions like atrial fibrillation and heart failure noninvasively.
Novel Wearable Seismocardiography and Machine Learning Algorithms Can Assess Clinical Status of Heart Failure Patients
This study shows that a wearable device can track heart failure severity by analyzing chest vibrations during exercise, potentially helping doctors monitor patients remotely and adjust treatments effectively.
High-Resolution Seismocardiogram Acquisition and Analysis System.
This study developed a portable device that uses vibrations from the chest to monitor heart health, showing promising results in detecting heart function metrics similar to hospital-grade echocardiograms.
Quantifying and Reducing Motion Artifacts in Wearable Seismocardiogram Measurements During Walking to Assess Left Ventricular Health
This research shows how wearable chest sensors can measure heart function during walking by reducing motion noise, potentially helping doctors monitor heart health during daily activities.
A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health
This study shows how wearable sensors can monitor heart health by combining electrical and mechanical heart signals, offering an affordable and reliable early warning system for heart disease.
Automatic Identification of Systolic Time Intervals in Seismocardiogram
This research shows how wearable sensors can accurately track heart function by analyzing vibrations from the chest, even in noisy conditions, paving the way for continuous heart health monitoring.
A 3D model of the thorax for seismocardiography
This study creates a 3D model of the chest to better understand heart vibrations, helping doctors use SCG for heart health monitoring.
Ballistocardiography and Seismocardiography: A Review of Recent Advances
This paper reviews how new technologies like wearable sensors and advanced signal processing make heart monitoring through vibrations (BCG and SCG) more practical and clinically useful, even outside hospitals.
Estimating Cardiac Stroke Volume from the Seismocardiogram Signal
This study shows that heart vibrations measured on the chest (SCG) can estimate the amount of blood pumped by the heart (stroke volume) almost as accurately as ultrasound methods, using machine learning techniques.
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.