Heart Failure
Studies in this Category
SEISMIC-HF 1: key findings from AHA24 and implications for remote cardiac monitoring
This study shows that a wearable patch can estimate heart pressure in patients with heart failure as accurately as invasive tests, offering hope for better remote care options.
Deep Learning Predicts Cardiac Output from Seismocardiographic Signals in Heart Failure
This study shows that wearable sensors using chest vibrations and heart signals can estimate heart function as accurately as invasive tests, offering a safer and more accessible option for heart failure patients.
Evaluation of seismocardiography in detecting pre-load changes and cardiovascular disease: a comparative study with transthoracic echocardiography
This study shows that SCG, a non-invasive heart vibration monitoring tool, can detect fluid changes and may help identify heart dysfunction, offering a simpler alternative to traditional echocardiography.
Non-exercise estimation of peak oxygen uptake in patients with ischaemic heart disease and heart failure using seismocardiography
This study found that a new heart monitoring method using vibrations (SCG) was not accurate enough to estimate fitness levels or track improvements in heart patients after rehabilitation.
Seismocardiography as a valuable non-exercise method for estimating peak Vo2 in cardiac patients? first experiences in Germany
This research shows that SCG can estimate heart fitness in cardiac patients almost as accurately as traditional exercise tests, but more data is needed to improve reliability for clinical use.
Deep learning-based beat-to-beat delineation of heart sounds and fiducial points in seismocardiography
This study developed an AI tool that accurately detects key heart vibration points, enabling better heart monitoring for patients with or without heart disease.
Non-Invasive Wearable Technology to Predict Heart Failure Decompensation
This study reviews wearable devices like smartwatches and patches that monitor heart and lung health to predict worsening heart failure. These technologies could help doctors intervene earlier and prevent hospitalizations, but more research is needed to make them reliable and easy to use.
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.
Smartphone-Based Recognition of Heart Failure by Means of Microelectromechanical Sensors
This study shows that smartphones can detect heart failure with high accuracy using built-in motion sensors, offering a simple and non-invasive way to monitor heart health remotely.
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.
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.
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.
Point-of-care aid-to-diagnosis for heart failure using artificial intelligence based on seismocardiography acquired with a smartphone in the emergency department
This study shows that a smartphone app using heart vibrations and AI can help diagnose heart failure quickly and accurately in emergency settings.
Detecting Preload Changes Using Seismocardiography
This study shows that chest vibration signals (SCG) can detect heart changes caused by increased blood volume, which could help monitor heart failure in clinical settings.
Correlation between diastolic seismocardiography variables and echocardiography variables
This study shows that chest vibrations (SCG) can reliably measure heart relaxation, similar to echocardiography, offering a simpler and faster way to monitor heart health at home or in clinics.
Estimation of Changes in Intracardiac Hemodynamics Using Wearable Seismocardiography and Machine Learning in Patients With Heart Failure: A Feasibility Study
This study shows that a wearable patch can track heart pressure changes in heart failure patients, offering a cheaper way to monitor their condition remotely and reduce hospital visits.
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.
Cardiac Time Intervals Derived from Electrocardiography and Seismocardiography in Different Patient Groups
This study shows that heart function can be monitored using vibrations from the chest and ECG, offering a simpler alternative to ultrasound for tracking changes after heart valve surgery.
Can Seismocardiogram Fiducial Points Be Used for the Routine Estimation of Cardiac Time Intervals in Cardiac Patients?
This research shows that SCG signals can help monitor heart function but may not work for all patients. A preliminary test is needed to ensure accuracy before using this method in clinical settings.
Computer-Aided Detection of Fiducial Points in Seismocardiography through Dynamic Time Warping
This study shows how advanced algorithms can improve heart monitoring by accurately detecting key heart signals from chest vibrations, helping predict heart failure with over 92% accuracy.
A Comprehensive Review on Seismocardiogram: Current Advancements on Acquisition, Annotation, and Applications
This study reviews how SCG, a method to measure heart vibrations, is advancing with new sensors and AI to monitor heart health more effectively, even at home. It also highlights challenges like reducing noise in signals during movement.
Seismocardiography: Interpretation and Clinical Application
This research shows how heart vibrations (SCG) can help monitor heart health. It links SCG signals to heart events, tracks therapy effects in heart failure patients, and estimates fitness levels without exercise tests, making heart monitoring simpler and more accessible.
Multichannel seismocardiography: an imaging modality for investigating heart vibrations
Researchers developed a new system to map heart vibrations across the chest, revealing patterns tied to heart valve movements. This technology could improve heart failure treatments and diagnostics.
Contactless Seismocardiography via Deep Learning Radars
This research shows how radar and AI can monitor heart vibrations without physical contact, achieving accuracy similar to clinical ultrasound for detecting key heart movements.
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.
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.
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.
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.
Automatic Detection of Seismocardiogram Sensor Misplacement for Robust Pre-Ejection Period Estimation in Unsupervised Settings
This research shows that SCG sensors must be correctly placed on the chest to measure heart function accurately. A machine learning algorithm helps users detect misplacement, improving home-based heart monitoring for heart failure patients.
Universal Pre-Ejection Period Estimation Using Seismocardiography: Quantifying the Effects of Sensor Placement and Regression Algorithms
This study shows that placing heart vibration sensors below the clavicle improves heart function tracking accuracy, and wearable devices can work over thin clothing without losing precision.
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.
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.
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.