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Studies in this Category
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Seismocardiography: waveform identification and noise analysis
The study examines how to clean and classify heart vibration signals (SCG) for better medical use, focusing on reducing noise and improving accuracy.