Every heartbeat sets the body, and the environment around it, into mechanical vibrations that can be recorded using different sensor technologies such as accelerometers, gyroscopes, pressure and transduces and microphones. These vibrations can be detected directly, by placing sensors on the body, or indirectly from the surfaces on which the body lies, such as weight scales, chairs or beds. These vibration signals can be in very low inaudible frequencies all the way up to audible ones, resembling the opening and closure sounds of the heart. These signals have been recorded for more than a century and have been called different names such as ballistocardiography, seismocardiography, phonocardiography, gyrocardiography, mechanocardiography, apexcardiography and few others.
Despite the differences in names and recordings means, what is common between all these signals is the window they open to us into the mechanical performance of the heart versus the one provided by electrocardiography to the electrical performance of the heart. They have also been used to extract or estimate hemodynamic parameters such as heart rate, stroke volume, systolic time intervals and cardiac contractility. The advances in sensors and data processing has created a new wave of research in these signals.
This Research Topic intends to collect recent findings in the cardiac vibrations realm and address the current challenges to take these techniques to actual use, clinical or non-clinical. This article collection will cover (but is not limited to) the following areas of research:
• Clinical applications of these signals in heart failure, coronary artery disease, myocardial ischemia, cardiac valve dysfunction, hemorrhage, etc.
• Non clinical application of the cardiac signals in assessment of health and exercise.
• Proposing novel signal processing algorithms and advancing feature dependent machine learning (ML) models and feature independent ML methodologies (Deep learning) to identify cardiac abnormalities from these signals.
• Developing mobile and wearable technologies for recording these signals and also new instrumentations for recording the signals.
• Modeling of the signals and investigating the genesis of waves in these vibration signals and their correspondence to hemodynamic parameters.
Topic Editor Kouhyar Tavakolian belongs to the board of directors of Heart Force Medical Inc. Topic Editor Omer Inan has co-founded Cardiosense, receives research funding from Hill-Rom Services, Inc. and Murata Americas, and has IP licensed by Physiowave, TandemLaunch, and Cardiosense. Topic Editor Samuel Schmidt has co-founded VentriJect, has co-founded Acarix, has co-founded Heart View Medical, and receives research funding from Acarix, VentriJect, and ViewCare. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
Every heartbeat sets the body, and the environment around it, into mechanical vibrations that can be recorded using different sensor technologies such as accelerometers, gyroscopes, pressure and transduces and microphones. These vibrations can be detected directly, by placing sensors on the body, or indirectly from the surfaces on which the body lies, such as weight scales, chairs or beds. These vibration signals can be in very low inaudible frequencies all the way up to audible ones, resembling the opening and closure sounds of the heart. These signals have been recorded for more than a century and have been called different names such as ballistocardiography, seismocardiography, phonocardiography, gyrocardiography, mechanocardiography, apexcardiography and few others.
Despite the differences in names and recordings means, what is common between all these signals is the window they open to us into the mechanical performance of the heart versus the one provided by electrocardiography to the electrical performance of the heart. They have also been used to extract or estimate hemodynamic parameters such as heart rate, stroke volume, systolic time intervals and cardiac contractility. The advances in sensors and data processing has created a new wave of research in these signals.
This Research Topic intends to collect recent findings in the cardiac vibrations realm and address the current challenges to take these techniques to actual use, clinical or non-clinical. This article collection will cover (but is not limited to) the following areas of research:
• Clinical applications of these signals in heart failure, coronary artery disease, myocardial ischemia, cardiac valve dysfunction, hemorrhage, etc.
• Non clinical application of the cardiac signals in assessment of health and exercise.
• Proposing novel signal processing algorithms and advancing feature dependent machine learning (ML) models and feature independent ML methodologies (Deep learning) to identify cardiac abnormalities from these signals.
• Developing mobile and wearable technologies for recording these signals and also new instrumentations for recording the signals.
• Modeling of the signals and investigating the genesis of waves in these vibration signals and their correspondence to hemodynamic parameters.
Topic Editor Kouhyar Tavakolian belongs to the board of directors of Heart Force Medical Inc. Topic Editor Omer Inan has co-founded Cardiosense, receives research funding from Hill-Rom Services, Inc. and Murata Americas, and has IP licensed by Physiowave, TandemLaunch, and Cardiosense. Topic Editor Samuel Schmidt has co-founded VentriJect, has co-founded Acarix, has co-founded Heart View Medical, and receives research funding from Acarix, VentriJect, and ViewCare. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
