Coronary Artery Disease
Studies in this Category
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.