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A novel wearable device integrating ECG and PCG for cardiac health monitoring.
Microsyst Nanoeng
January 2025
Key Laboratory of Instrumentation Science and Dynamic Measurement Ministry of Education, North University of China, 030051, Taiyuan, China.
The alarming prevalence and mortality rates associated with cardiovascular diseases have emphasized the urgency for innovative detection solutions. Traditional methods, often costly, bulky, and prone to subjectivity, fall short of meeting the need for daily monitoring. Digital and portable wearable monitoring devices have emerged as a promising research frontier.
View Article and Find Full Text PDFCoronary Artery Disease Detection Based on a Novel Multi-Modal Deep-Coding Method Using ECG and PCG Signals.
Sensors (Basel)
October 2024
Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, China.
Coronary artery disease (CAD) is an irreversible and fatal disease. It necessitates timely and precise diagnosis to slow CAD progression. Electrocardiogram (ECG) and phonocardiogram (PCG), conveying abundant disease-related information, are prevalent clinical techniques for early CAD diagnosis.
View Article and Find Full Text PDFPCG-based exercise fatigue detection method using multi-scale feature fusion model.
Comput Methods Biomech Biomed Engin
September 2024
School of Sports Engineering, Beijing Sports University, Beijing, China.
Accurate detection of exercise fatigue based on physiological signals is vital for reasonable physical activity. Existing studies utilize widely Electrocardiogram (ECG) signals to achieve exercise monitoring. Nevertheless, ECG signals may be corrupted because of sweat or loose connection.
View Article and Find Full Text PDFBeat-by-Beat Estimation of Hemodynamic Parameters in Left Ventricle Based on Phonocardiogram and Photoplethysmography Signals Using a Deep Learning Model: Preliminary Study.
Bioengineering (Basel)
August 2024
School of Biomedical Engineering, Dalian University of Technology, Dalian 116024, China.
Beat-by-beat monitoring of hemodynamic parameters in the left ventricle contributes to the early diagnosis and treatment of heart failure, valvular heart disease, and other cardiovascular diseases. Current accurate measurement methods for ventricular hemodynamic parameters are inconvenient for monitoring hemodynamic indexes in daily life. The objective of this study is to propose a method for estimating intraventricular hemodynamic parameters in a beat-to-beat style based on non-invasive PCG (phonocardiogram) and PPG (photoplethysmography) signals.
View Article and Find Full Text PDFArtificial intelligence-based screening for cardiomyopathy in an obstetric population: A pilot study.
Cardiovasc Digit Health J
June 2024
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota.
Article Synopsis
- Cardiomyopathy significantly contributes to pregnancy-related deaths, especially during the late postpartum period, highlighting the need for timely diagnosis.* -
- A study evaluated AI-enhanced ECG and digital stethoscope technologies to detect left ventricular dysfunction in pregnant and postpartum women, showing impressive diagnostic accuracy.* -
- The AI-ECG achieved a perfect accuracy (AUC: 1.0), while the digital stethoscope also performed strongly (AUC: 0.98-0.97), suggesting these technologies could improve cardiac screening in obstetric care.*
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