Abstract: A monitoring apparatus for a human body includes a node network with at least one motion sensor and at least one acoustic sensor. A processor is coupled to the node network, and receives motion information and acoustic information from the node network. The processor determines from the motion information and the acoustic information a source of acoustic emissions within the human body by analyzing the acoustic information in the time domain to identify an event envelope representing an acoustic event, determining a feature vector related to the event envelope, calculating a distance between the feature vector and each of a set of predetermined event silhouettes, and identifying one of the predetermined event silhouettes for which the distance is a minimum.

Abstract: A non-invasive, passive, and fully automated heart-sound-based system and method that provides estimates for blood velocity, tissue motion, and cardiac chamber size parameters for cardiac assessment is provided. The system uses a computer processor and software to receive PCG acoustic signals from one or more sensors and simultaneously receive electrocardiogram (ECG) signals from one or more sensors that are attached to a patient. The phonocardiogram (PCG) processing system and methods compute proxy metrics for echocardiographic parameters of cardiac tissue motion and valvular blood flow for evaluation.

Abstract: A monitoring apparatus for a human body includes a node network with at least one motion sensor and at least one acoustic sensor. A processor is coupled to the node network, and receives motion information and acoustic information from the node network. The processor determines from the motion information and the acoustic information a source of acoustic emissions within the human body by analyzing the acoustic information in the time domain to identify an event envelope representing an acoustic event, determining a feature vector related to the event envelope, calculating a distance between the feature vector and each of a set of predetermined event silhouettes, and identifying one of the predetermined event silhouettes for which the distance is a minimum.

Abstract: Systems and methods are provided for the non-invasive computation of Pulmonary Artery Pressure (and its components of mean, systolic and diastolic) (PAP) as well as Pulmonary Capillary Wedge Pressure (and its components of mean, A-Wave and V-Wave) (PCWP) using a wearable sensor device. Cardiac acoustic and electrocardiogram sensor signals are obtained and multiple temporal, amplitude-based, and spectral features are extracted from the signals. Extracted features from a subject are used as inputs for pre-trained classification, regression, or advanced machine learning models to provide an accurate computation of PAP and PCWP and their associated component values without surgery.

Abstract: An Integrated CardioRespiratory (ICR) System is provided for continuous Ejection Fraction (EF) measurement using a wearable device comprising a plurality of acoustic sensors. The ICR system performs signal processing computations to characterize cardiac acoustic signals that are generated by cardiac hemodynamic flow, cardiac valve, and tissue motion, and may use advanced machine learning methods to provide accurate computation of EF.

Abstract: An Integrated CardioRespiratory (ICR) System is provided for continuous Stroke Volume (SV) measurement using a wearable device comprising a plurality of acoustic sensors. The ICR system performs signal processing computations to characterize cardiac acoustic signals that are generated by cardiac hemodynamic flow, cardiac valve, and tissue motion, and may use advanced machine learning methods to provide accurate computation of SV.

Abstract: A monitoring apparatus for a human body includes a node network with at least one motion sensor and at least one acoustic sensor. A processor is coupled to the node network, and receives motion information and acoustic information from the node network. The processor determines from the motion information and the acoustic information a source of acoustic emissions within the human body by analyzing the acoustic information in the time domain to identify an event envelope representing an acoustic event, determining a feature vector related to the event envelope, calculating a distance between the feature vector and each of a set of predetermined event silhouettes, and identifying one of the predetermined event silhouettes for which the distance is a minimum.

Abstract: An Integrated CardioRespiratory (ICR) System is provided for continuous Ejection Fraction (EF) measurement using a wearable device comprising a plurality of acoustic sensors. The ICR system performs signal processing computations to characterize cardiac acoustic signals that are generated by cardiac hemodynamic flow, cardiac valve, and tissue motion, and may use advanced machine learning methods to provide accurate computation of EF.

Abstract: An Integrated CardioRespiratory (ICR) System is provided for continuous Stroke Volume (SV) measurement using a wearable device comprising a plurality of acoustic sensors. The ICR system performs signal processing computations to characterize cardiac acoustic signals that are generated by cardiac hemodynamic flow, cardiac valve, and tissue motion, and may use advanced machine learning methods to provide accurate computation of SV.

Abstract: A monitoring apparatus for a human body includes a node network with at least one motion sensor and at least one acoustic sensor. A processor is coupled to the node network, and receives motion information and acoustic information from the node network. The processor determines from the motion information and the acoustic information a source of acoustic emissions within the human body by analyzing the acoustic information in the time domain to identify an event envelope representing an acoustic event, determining a feature vector related to the event envelope, calculating a distance between the feature vector and each of a set of predetermined event silhouettes, and identifying one of the predetermined event silhouettes for which the distance is a minimum.