Validation
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.
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.
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.
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.
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.
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.
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.
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.
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.
The acceptability of a novel seismocardiography device for measuring VO2 max in a workplace setting: a mixed methods approach
This study shows that a new heart vibration device can measure fitness at work more comfortably than exercise tests, but better training for practitioners is needed to make it widely usable.
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.
Accuracy of the Instantaneous Breathing and Heart Rates Estimated by Smartphone Inertial Units
This study shows that smartphones can accurately measure heart and breathing rates using built-in sensors, offering a simple and affordable way to monitor health without extra devices.
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.
Contactless seismocardiography via Gunnar-Farneback optical flow
This research shows that smartphone videos can track heart vibrations as accurately as traditional sensors, offering a comfortable and contactless way to monitor heart health.
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.
Extracting Cardiovascular-Induced Chest Vibrations from Ordinary Chest Videos: A Comparative Study
This study shows that smartphone videos can accurately track heart vibrations using advanced computer vision methods, offering a comfortable and non-invasive way to monitor heart health.
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.
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.
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.
Publicly available signal databases containing seismocardiographic signals — the state in early 2023
This study highlights the limited availability of SCG signal databases, which are crucial for advancing heart monitoring research. It identifies gaps in gender balance and disease representation in existing datasets.
Effect of the Airway Pressure on the Frequency Domain of Seismocardiographic Signal
This study shows how changes in breathing pressure affect heart vibrations, which could help monitor heart muscle health in the future.
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.
Cross-Domain Detection of Pulmonary Hypertension in Human and Porcine Heart Sounds
This study shows that heart sound recordings from pigs can help train AI models to detect pulmonary hypertension in humans, offering a non-invasive and accurate alternative to invasive procedures like catheterization.
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.
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.
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.
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.
Detection of heart rate using smartphone gyroscope data: a scoping review
This study reviews how smartphone gyroscopes can measure heart rate, showing promise but needing better methods and standards for accuracy and usability in real-life scenarios.
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.
ECG-Free Heartbeat Detection in Seismocardiography Signals via Template Matching
This study shows that heartbeats can be accurately detected from chest vibrations without needing an ECG, using a simple and efficient algorithm. This could enable wearable devices to monitor heart health more easily.
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.
Respiratory Modulation of Sternal Motion in the Context of Seismocardiography
This study shows how chest vibrations (SCG) can track breathing and heart activity using a single wearable sensor, paving the way for simpler health monitoring devices.
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.
Comparison of Heart Rate Variability Indices Based on Seismocardiograms from Healthy Volunteers and Patients with Valvular Heart Diseases
This research shows that heart vibrations measured from the chest can help detect differences in heart rate patterns between healthy people and those with heart valve diseases, offering a new way to monitor heart health outside clinics.
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.
Seismocardiography with Smartphones: No Leap from Bench to Bedside (Yet)
This study shows that while smartphones can measure heart vibrations, the technology isn’t ready for clinical use due to lack of validation and standardization compared to other methods like PPG.
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.
A Comparison of Heart Pulsations Provided by Forcecardiography and Double Integration of Seismocardiogram
This study shows that heart vibrations measured by accelerometers can mimic a novel sensor's output, but improvements are needed for accurate heart rate tracking during breathing and apnea.
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.
Driver Cardiovascular Disease Detection Using Seismocardiogram
This research shows how vibrations from the heart, measured through a car's safety belt, can monitor drivers' heart health and prevent accidents caused by sudden heart issues.
86057 High Screening Efficacy Using Wearable Seismocardiography to Identify Aortic Valve Disease Patients, Potential to Tailor MRI Exams to Patient Needs
This research shows that chest vibration signals can accurately identify heart valve disease, offering a quick and affordable alternative to MRI for screening patients.
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.
Validity and reliability of a clinical non-exercise method for assessment of cardiorespiratory fitness using seismocardiography
This study shows that seismocardiography can reliably measure cardiorespiratory fitness without exercise, though it slightly underestimates results compared to traditional methods.
Heart Rate and Respiratory Rate Monitoring Using Seismocardiography
This study shows that SCG can accurately measure heart and breathing rates, offering a non-invasive alternative to traditional methods like ECG and respiratory belts.
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.
Smart Seismocardiography: A Machine Learning Approach for Automatic Data Processing
This research shows how a low-cost sensor and machine learning can track heart vibrations to monitor cardiac health, paving the way for affordable wearable devices.
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.
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.
Seismocardiography on Infants and Kids
This research shows how SCG can track heart activity in infants and kids, revealing unique signal patterns compared to adults. It sets the stage for better heart monitoring tools for children.
Trodden Lanes or New Paths: Ballisto- and Seismocardiography Till Now
This study reviews research on heart vibration methods (BCG and SCG) and finds growing interest due to better sensors and technology, paving the way for improved heart diagnostics.
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.
A Novel Adaptive Recursive Least Squares Filter to Remove the Motion Artifact in Seismocardiography
This study developed a new method to clean heart vibration signals from motion noise, achieving 98% accuracy in detecting heartbeats during walking and standing, using a single wearable sensor.
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.
Heart Rate Variability Analysis on Reference Heart Beats and Detected Heart Beats of Smartphone Seismocardiograms
This study shows that smartphones can accurately measure heart rate variability using chest vibrations, paving the way for affordable heart monitoring at home.
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.
Performance Analysis of Gyroscope and Accelerometer Sensors for Seismocardiography-Based Wearable Pre-Ejection Period Estimation
This study shows that combining gyroscope and accelerometer data improves heart health monitoring, making wearable devices more accurate for tracking cardiac function.
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.
Near Real-Time Implementation of An Adaptive Seismocardiography – ECG Multimodal Framework for Cardiac Gating
This research shows that combining heart vibration signals (SCG) with ECG improves the accuracy of heart imaging, making it safer and more effective for diagnosing heart diseases.
Seismocardiography and 4D flow MRI reveal impact of aortic valve replacement on chest acceleration and aortic hemodynamics
This study shows how chest vibration measurements and advanced MRI can track improvements in blood flow after heart valve surgery, offering a quick and affordable way to monitor recovery.
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.
Machine Learning Based Classification of Myocardial Infarction Conditions Using Smartphone-Derived Seismo- and Gyrocardiography
Researchers used smartphone sensors to track heart changes in heart attack patients before and after treatment, achieving promising accuracy with machine learning methods.
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.
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.
A Machine Learning Approach to Assess the Separation of Seismocardiographic Signals by Respiration
This study shows that machine learning can classify heart vibrations based on breathing patterns, with lung volume proving to be a better grouping method than respiratory phases for reducing signal variability.
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.
BCG Artifact Removal Using Improved Independent Component Analysis Approach
This research presents a new method to clean heart vibration signals (BCG) by removing noise caused by movement, using advanced mathematical techniques like ICA and clustering. It improves signal quality for better health monitoring.
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.
Heart Rate Variability Estimation with Joint Accelerometer and Gyroscope Sensing
This study shows how combining accelerometer and gyroscope sensors can improve heart rate variability tracking, paving the way for better wearable heart monitors.
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.
Beat-to-beat estimation of LVET and QS2 indices of cardiac mechanics from wearable seismocardiography in ambulant subjects
This study shows that smartphones can accurately detect heartbeats using vibrations from the chest, with improved algorithms achieving near-perfect accuracy.
History of space medicine: Academician Vasily V. Parin, founder of space cardiology
This study explores how Vasily V. Parin's innovations in heart monitoring during space missions have shaped modern cardiology and space medicine, including tools now used in everyday healthcare.
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.
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.
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This study shows that seismocardiography (SCG) can estimate fitness levels reliably, though it slightly underestimates compared to the gold standard method. It offers a simpler, non-exercise alternative for assessing heart and lung health.
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.