Development of a Novel Contactless Mechanocardiograph Device [PDF]
International Journal of Telemedicine and Applications, 2008 A novel method of detecting mechanical movement of the heart, Mechanocardiography (MCG), with no connection to the subject's body is presented. This measurement is based on radar technology and it has been proven through this research work that the ...
Kouhyar Tavakolian +4 more
doaj +6 more sources
Classification of Atrial Fibrillation and Acute Decompensated Heart Failure Using Smartphone Mechanocardiography: A Multilabel Learning Approach [PDF]
Acta cardiologica, 2020 Timely diagnosis of cardiovascular diseases (CVD) is crucial to prevent morbidity and mortality. Atrial fibrillation (AFib) and heart failure (HF) are two prevalent cardiac disorders that are associated with a high risk of morbidity and mortality ...
Saeed Mehrang +13 more
semanticscholar +8 more sources
Heartbeat Detection in Gyrocardiography Signals without Concurrent ECG Tracings [PDF]
Sensors, 2023 A heartbeat generates tiny mechanical vibrations, mainly due to the opening and closing of heart valves. These vibrations can be recorded by accelerometers and gyroscopes applied on a subject’s chest.
Salvatore Parlato +4 more
doaj +2 more sources
An Overview of the Sensors for Heart Rate Monitoring Used in Extramural Applications [PDF]
Sensors, 2022 This work presents an overview of the main strategies that have been proposed for non-invasive monitoring of heart rate (HR) in extramural and home settings. We discuss three categories of sensing according to what physiological effect is used to measure
Alessandra Galli +4 more
doaj +2 more sources
Detection of heart rate using smartphone gyroscope data: a scoping review. [PDF]
Front Cardiovasc Med, 2023 Heart rate (HR) is closely related to heart rhythm patterns, and its irregularity can imply serious health problems. Therefore, HR is used in the diagnosis of many health conditions. Traditionally, HR has been measured through an electrocardiograph (ECG),
Wu W +6 more
europepmc +3 more sources
Non-Invasive Wearable Technology to Predict Heart Failure Decompensation. [PDF]
J Clin MedHeart failure (HF) remains a leading cause of recurrent hospitalisations worldwide, largely driven by acute episodes of decompensation. Early identification of impending decompensation could enable timely intervention and potentially prevent costly ...
Devin J +9 more
europepmc +3 more sources
Digital Cardiovascular Twins, AI Agents, and Sensor Data: A Narrative Review from System Architecture to Proactive Heart Health [PDF]
SensorsCardiovascular disease remains the world’s leading cause of mortality, yet everyday care still relies on episodic, symptom-driven interventions that detect ischemia, arrhythmias, and remodeling only after tissue damage has begun, limiting the ...
Nurdaulet Tasmurzayev +7 more
doaj +2 more sources
Stroke and digital technology: a wake-up call from COVID-19 pandemic. [PDF]
Neurol Sci, 2021 Iodice F +9 more
europepmc +3 more sources
A Powerful Paradigm for Cardiovascular Risk Stratification Using Multiclass, Multi-Label, and Ensemble-Based Machine Learning Paradigms: A Narrative Review. [PDF]
Diagnostics (Basel), 2022 Background and Motivation: Cardiovascular disease (CVD) causes the highest mortality globally. With escalating healthcare costs, early non-invasive CVD risk assessment is vital. Conventional methods have shown poor performance compared to more recent and
Suri JS +15 more
europepmc +4 more sources
Identification of Cardiac Patients Based on the Medical Conditions Using Machine Learning Models. [PDF]
Comput Intell Neurosci, 2022 Chronic diseases are the most severe health concern today, and heart disease is one of them. Coronary artery disease (CAD) affects blood flow to the heart, and it is the most common type of heart disease which causes a heart attack. High blood pressure, high cholesterol, and smoking significantly increase the risk of heart disease. To estimate the risk
Kumar K +10 more
europepmc +2 more sources