Heart Rate
Studies in this Category
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
Amplitude Modulation Effects in Cardiac Signals
This study shows how to better analyze heart signals by using simple techniques to reveal hidden patterns, which could improve heart monitoring methods.
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.