Fiducial Point Detection
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.
Multi-site cardiac rhythm monitoring via multi-channel SCG system and exercise-induced physiological analysis
This research developed a system to monitor heart vibrations at multiple chest locations, showing how exercise changes heart valve timing. It could help detect heart issues without invasive tests.
SCG With Your Phone: Diagnosis of Rhythmic Spectrum Disorders in Field Conditions
This study shows that smartphones can reliably monitor heart rhythms using vibrations from the chest, thanks to advanced AI that works even in noisy, real-world conditions.
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.
Fully automated template matching method for ECG-free heartbeat detection in cardiomechanical signals of healthy and pathological subjects
This study developed a new method to detect heartbeats from chest vibrations without needing ECG, showing high accuracy even for patients with heart diseases. It could enable long-term heart monitoring using wearable devices.
Monitoring of respiration and cardiorespiratory interactions from multichannel seismocardiography signals
This study shows that chest vibrations measured by accelerometers can accurately track breathing and heart-lung interactions, regardless of sensor placement. It introduces a new method to analyze these signals for better health monitoring.
A Forcecardiography dataset with simultaneous SCG, Heart Sounds, ECG, and Respiratory signals
This study provides a groundbreaking dataset combining heart and breathing signals, enabling researchers to improve non-invasive heart and lung monitoring technologies.
From video to vital signs: a new method for contactless multichannel seismocardiography
This study shows that smartphone videos can track heart vibrations using QR stickers on the chest, offering a low-cost way to monitor heart health and detect issues early, with accuracy comparable to clinical tools.
Estimation of cardiorespiratory fitness in healthy using seismocardiography
This study shows that a chest vibration sensor can accurately measure fitness levels without exercise, offering a simple and affordable way to track heart health.
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.
Design of synchronous seismocardiography-ballistocardiography monitoring system
Researchers developed a wearable device that captures heart vibrations from the chest and body simultaneously, showing promise for use in clinics and at home to monitor heart health effectively.
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.
Robustness of Persistence Diagrams to Time-Delay for Seismocardiogram Signal Quality Assessment*
This study shows that a new method using persistence diagrams can assess heart vibration signal quality without needing ECG, making it more reliable for wearable heart monitors in noisy environments.
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.
Echocardiography Correlation with Seismocardiography—Systematic Review
This review highlights how SCG and ECHO can work together to improve heart monitoring, but calls for better standardization to make studies more reliable and comparable.
Developing a Protocol for Aligning and Correlating Seismocardiography with Echocardiography
This study developed a reliable ultrasound protocol to match heart vibration signals with cardiac events, improving research consistency and paving the way for better heart monitoring technologies.
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.
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.
Noncontact Multipoint Vital Sign Monitoring With mmWave MIMO Radar
This study shows how radar technology can monitor heart and lung movements at multiple chest points without physical contact, offering accurate and comfortable health tracking compared to traditional methods.
Investigating Seismocardiogram Patterns: A Computational Modeling of Cardiac Wall Motion Propagation to the Chest Surface
This study uses advanced modeling to simulate heart vibrations on the chest, helping improve non-invasive heart monitoring methods like SCG.
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.
Porcine Model for Validation of Noninvasive Estimation of Pulmonary Hypertension
This study shows that chest vibrations measured by SCG can detect pulmonary hypertension in pigs, suggesting it could be a simpler, cheaper alternative to echocardiography for humans in the future.
Evaluating Seismocardiography as a Non-Exercise Method for Estimating Maximal Oxygen Uptake
This study shows that the Seismofit® device can estimate fitness levels (VO2MAX) without exercise, offering a simpler alternative to traditional lab tests with good accuracy and reliability.
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.
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.
Deep Learning for identifying systolic complexes in SCG traces: a cross-dataset analysis
This study shows how deep learning can identify heart activity from chest vibrations, even in real-world conditions, by using data from multiple sensors and personalizing the model for each user.
ECG-Free Assessment of Cardiac Valve Events Using Seismocardiography
This study shows that heart valve events can be detected using body vibrations alone, without the need for ECG, making heart monitoring simpler and more accessible.
Seismocardiography for Emotion Recognition: A Study on EmoWear with Insights from DEAP
This study shows that a single wearable accelerometer on the chest can track emotions by measuring heart and breathing vibrations, offering a simpler and cheaper way to integrate emotion recognition into daily life.
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.
Non-contact heart vibration measurement using computer vision-based seismocardiography
This study shows that a smartphone camera can measure heart vibrations as accurately as traditional sensors, paving the way for affordable heart monitoring at home.
Postural and longitudinal variability in seismocardiographic signals
This study shows that SCG signals, which measure heart vibrations, change with posture but remain stable over time, making them promising for long-term heart monitoring.
Waveform Similarity Analysis Using Graph Mining for the Optimization of Sensor Positioning in Wearable Seismocardiography
This study shows that placing a wearable heart sensor near the mitral valve while lying down gives the most consistent readings, helping improve heart monitoring accuracy for future clinical use.
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.
Analysis of Non-Contact Multichannel Recording of Cardiac Vibration: Visual Seismocardiogram
This study uses ultrasound to record heart vibrations without touching the body, offering better accuracy and visualization for heart event detection compared to traditional methods.
Revolutionizing smartphone gyrocardiography for heart rate monitoring: overcoming clinical validation hurdles
This study highlights how smartphone gyroscopes can accurately monitor heart rate, offering a practical and non-invasive alternative to traditional methods like ECG and PPG, even during daily activities.
Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms of Healthy Volunteers and Patients with Valvular Heart Diseases
This study shows that heart vibrations measured by chest sensors (SCG and GCG) can reliably track heart rate variability, even in patients with heart valve diseases, offering a simpler alternative to traditional ECG tests.
Mechanical deconditioning of the heart due to long-term bed rest as observed on seismocardiogram morphology
This study shows how prolonged bed rest weakens the heart and stiffens arteries, using chest vibrations measured by SCG. It suggests SCG could help monitor heart health in space and hospitals with simple wearable devices.
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.
End-to-end sensor fusion and classification of atrial fibrillation using deep neural networks and smartphone mechanocardiography
This study shows that smartphones can detect atrial fibrillation (AFib) using vibrations from the chest with high accuracy, offering a practical and affordable heart monitoring solution.
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.
Heartbeat Detection in Seismocardiograms with Semantic Segmentation
This study shows that a deep learning model can accurately detect heartbeats from chest vibrations, offering a promising alternative to traditional ECG-based methods for heart monitoring.
Toward Wearable Estimation of Tidal Volume via Electrocardiogram and Seismocardiogram Signals
This research shows how a wearable chest patch can estimate lung air volume using heart signals and machine learning, offering a step toward easy, continuous respiratory health monitoring.
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.
BIOWISH: Biometric Recognition using Wearable Inertial Sensors detecting Heart Activity
This research shows how wearable sensors can use heart vibrations to identify people with high accuracy, even weeks after enrollment. It also demonstrates how these sensors can recognize activities like walking or lying down, making them useful for secure health monitoring.
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.
Beat to BEAT – Non-Invasive Investigation of Cardiac Function on the International Space Station
This study tests a smart shirt that monitors astronauts' heart health in space, aiming to improve wearable health technology for both space and earth use.
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.
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.
A multi-point heart rate monitoring using a soft wearable system based on fiber optic technology
This study developed a wearable device that uses advanced fiber optics to monitor heart rate more accurately by measuring chest vibrations. It could help doctors track heart health in clinical and daily settings.
Quantifying preload alterations using a sensitive chest-mounted accelerometer
This study shows that chest vibrations measured by a sensitive sensor can track heart function changes caused by fluid infusion, offering a new way to monitor heart health remotely.
Enabling Wearable Pulse Transit Time-Based Blood Pressure Estimation for Medically Underserved Areas and Health Equity: Comprehensive Evaluation Study (Preprint)
This study shows that a wearable device can accurately measure blood pressure without a cuff, helping underserved communities monitor hypertension remotely and conveniently.
Detecting Aortic Stenosis Using Seismocardiography and Gryocardiography Combined with Convolutional Neural Networks
This study shows that heart vibrations measured by wearable sensors and analyzed with AI can detect aortic stenosis with over 98% accuracy, offering a simpler alternative to traditional echocardiography.
Determination of Maximal Oxygen Uptake Using Seismocardiography at Rest
This study explores using chest vibrations (SCG) to estimate fitness levels without exercise. While the method shows potential, it needs refinement to match clinical accuracy standards.
Detecting Coronary Artery Disease Using Rest Seismocardiography and Gyrocardiography
This study shows that chest vibrations measured by a wearable sensor can detect heart disease with high accuracy, offering a potential at-home screening tool for coronary artery disease.
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.
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.
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.
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.
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.
Motion artifact cancellation from a single channel SCG using adaptive forgetting factor recursive least square filter
This study developed a new method to clean heart vibration signals from motion noise, achieving near-perfect accuracy compared to ECG readings, even during activities like jogging and jumping.
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.
High-Accuracy, Unsupervised Annotation of Seismocardiogram Traces for Heart Rate Monitoring
This study shows how chest vibrations can be used to monitor heartbeats accurately without needing traditional ECG sensors, paving the way for wearable heart monitors in daily life.
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.
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.
Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers
This study shows that heart vibrations measured with simple sensors can reliably track heart rate variability, even in patients with heart valve diseases, making heart monitoring more accessible and affordable.
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.
Heart Beat Detection from Smartphone SCG Signals: Comparison with Previous Study on HR Estimation
This study shows that smartphones can accurately detect heartbeats using vibrations from the chest, with improved algorithms achieving near-perfect accuracy.
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.
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.
A seismocardiography system and a possibility of its use for diagnosis of internal organs diseases using seismocardiogram information analysis
This research shows how heart vibrations measured by a new device can help diagnose internal organ diseases, offering a simpler alternative to traditional heart monitoring methods like ECGs.
A Low-Cost System for Seismocardiography-Based Cardiac Triggering: A Practical Solution for Cardiovascular Magnetic Resonance Imaging at 3 Tesla
This study shows that a new low-cost heart monitoring system using vibrations (SCG) works as well as traditional ECG systems during MRI scans, while being easier to use and more reliable in high magnetic fields.
Design and Development of a Portable Recording System for Simultaneous Acquisition of SCG and ECG Signals
This research developed a portable device that uses vibrations from the chest to monitor heart and breathing activity, showing promise for easier heart health tracking alongside traditional ECG tests.
A Unified Framework for Quality Indexing and Classification of Seismocardiogram Signals
This study shows how a new method can improve the quality and analysis of heart vibration signals, helping detect issues like misplaced sensors with high accuracy. It could make heart monitoring more reliable and automated for patients and clinicians.
Visualization of the Multichannel Seismocardiogram
This study explores ways to visualize chest vibrations caused by heart activity using data from 16 sensors. The methods help researchers better understand how these vibrations relate to heart function.
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.
Identifying Patients With Coronary Artery Disease Using Rest and Exercise Seismocardiography
This study shows that heart vibrations measured during rest and exercise can detect coronary artery disease as accurately as advanced imaging tests, offering a cheaper and faster alternative for diagnosis.
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.
Influence of Gravitational Offset Removal on Heart Beat Detection Performance from Android Smartphone Seismocardiograms
This study shows that smartphones can accurately detect heartbeats using vibrations from the chest, even without removing gravitational effects, thanks to advanced signal processing techniques.
Multiclass Classifier based Cardiovascular Condition Detection Using Smartphone Mechanocardiography
This study shows that smartphones can detect heart conditions like AFib and heart attacks using built-in sensors and machine learning, offering a promising tool for global heart health monitoring.
Definition of Fiducial Points in the Normal Seismocardiogram
This research shows how chest vibrations (SCG) can accurately track heart valve movements, offering a simple, non-invasive way to monitor heart health using accelerometers.
Comprehensive Analysis of Cardiogenic Vibrations for Automated Detection of Atrial Fibrillation Using Smartphone Mechanocardiograms
This study shows that a smartphone can detect atrial fibrillation (AFib) with high accuracy using chest vibrations, making heart monitoring accessible and easy for everyone without extra devices.
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.
Determining the Respiratory State From a Seismocardiographic Signal--A Machine Learning Approach
This study shows that chest vibrations from the heart (SCG signals) can predict breathing patterns using advanced machine learning, with neural networks being the most accurate method. This could help monitor breathing and heart health more easily and affordably.
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.
A Hidden Markov Model for Seismocardiography
This study shows that heart vibrations can be analyzed using a mathematical model to measure heart rate and other metrics with high accuracy, even using inexpensive sensors at home.
Contactless Mapping of Thoracic and Abdominal Movements: Applications for Seismocardiography
This study shows that a new ultrasound device can measure heart vibrations without touching the body, offering a faster and less invasive alternative to traditional methods.
Challenges in Using Seismocardiography for Blood Pressure Monitoring
This study explored using heart vibrations and pulse signals to estimate blood pressure but found inconsistent results, showing the method needs improvement before clinical use.
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.
Echocardiography as an indication of continuous-time cardiac quiescence
This research shows that ultrasound can help identify heart motion phases for better CT scans, potentially reducing radiation and improving accuracy in diagnosing heart disease.
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.
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.
A new algorithm for segmentation of cardiac quiescent phases and cardiac time intervals using seismocardiography
This study shows how chest vibrations can measure heart mechanics and identify resting phases of the heart, which could improve imaging and early disease detection without expensive equipment.
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.
Application of Acceleration Sensors in Physiological Experiments
This study shows how accelerometers can monitor heart activity and breathing, paving the way for wearable health devices that track fitness and medical conditions more effectively.
Three-dimensional apex-seismocardiography
This study used a 3D accelerometer to measure heart vibrations at the chest's apex, revealing complex movement patterns that could help in diagnosing heart conditions like heart failure in the future.
Combined measurement of ECG, Breathing and Seismocardiograms DataBase (CEBSDB)
This dataset combines heart, breathing, and vibration signals to study how breathing affects heart rate measurements and improve vibration-based heart monitoring technologies.
A System for Seismocardiography-Based Identification of Quiescent Heart Phases: Implications for Cardiac Imaging
This study shows that SCG, a chest vibration signal, can better identify heart motion phases for clearer CT scans, potentially reducing radiation and improving heart disease diagnosis.
A trimodal system for the acquisition of synchronous echocardiography, electrocardiography, and seismocardiography data
This study developed a system that combines ultrasound, heart electrical signals, and chest vibrations to better understand heart function and improve imaging techniques like CT and MRI.
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.
Autonomic function testing aboard the ISS using “PNEUMOCARD”
This study shows that where SCG sensors are placed on the chest affects the accuracy of heart function measurements, highlighting the need for consistent placement standards to improve heart disease diagnosis.
Comparative analysis of three different modalities for characterization of the seismocardiogram
This study explores three methods to analyze heart vibrations, showing how imaging and modeling can help understand heart mechanics and improve non-invasive diagnostics.
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.
Usefulness of Seismocardiography for the Diagnosis of Ischemia in Patients with Coronary Artery Disease
This study shows that SCG is better than traditional stress tests at detecting heart issues caused by blocked arteries, helping doctors decide when to perform further tests like angiography.
The seismocardiogram as magnetic-field-compatible alternative to the electrocardiogram for cardiac stress monitoring
This study shows that SCG can monitor heart function during MRI without interference, offering a safer and more reliable way to detect heart issues like ischemia compared to ECG.
Seismocardiographic changes associated with obstruction of coronary blood flow during balloon angioplasty
This study shows that seismocardiography can detect heart muscle changes during coronary angioplasty, offering a new way to monitor heart health noninvasively.