System and Method of Extraction, Identification, Marking and Display of Heart Valve Signals
A sensor device and a method using the sensor device includes a portable device (110) configured to capture composite vibration objects from at least one sensor (102b) and further configured to communicate data to a wireless node (105) in some embodiments. The sensor device further includes at least one or more processors (103, 105, or 106) operatively coupled to the portable device and configured to separate and identify separated vibration sources and further configured to identify a plurality of individual heart vibration events (302, 303, 304, 305) from the composite vibration objects where the one or more processors is further configured to mark individual heart events from the plurality of individual heart vibration events. In some embodiments, the one or more processors marks and presents individual heart events from the plurality of individual heart vibration events.
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This Application is a continuation of U.S. patent application Ser. No. 15/397,005 filed Jan. 3, 2017 and further claims the priority benefit of Provisional Application Nos. 62274761, 62274763, 62274765, 62274766, and 62274770, each of which were filed on Jan. 4, 2016, the entire disclosures of each are incorporated herein by reference.
FIELDThe embodiments herein relate generally to cardiac health monitoring and more particularly to analysis software combined with transducers to capture multichannel vibration signals along with an electrocardiogram signal for the measurement of heart functions.
BACKGROUNDHeart disease is the leading cause of death accounting for more than one-third (33.6%) of all U.S. deaths. Overall cardiac health can be significantly improved by proper triage. Low invasive and non-invasive ultrasound techniques (e.g., echocardiogram) are standard procedures, but the requirement of expensive devices and skilled operators limit their applicability. The following are the various types of heart disease that can be diagnosed and treated using the separated signal, namely, Coronary artery disease, Heart murmurs and valve abnormalities, Heart failure, Heart rhythm abnormalities (arrhythmias), Vascular disease, congenital heart disease, Cardiac resynchronization and Risk factor modification. A physician can work with patients to perform a comprehensive evaluation and design a personalized plan of care aimed at keeping them healthy.
The cardiohemic system which consists of the heart walls, valves and blood, creates vibrations during each cardiac cycle. The vibrations are the result of the acceleration and deceleration of blood due to abrupt mechanical opening and closing of the valves during the cardiac cycle.
SUMMARYThe exemplary embodiments herein provide a method and system based on a technique of separating, identifying and marking the heart signals, to extract information contained in cardiac vibration objects. Machine learning, auditory scene analysis, or spare coding are approaches to the source separation problem. Further note that the techniques and methods herein are not limited to acoustic, electrical or vibrational data as might be used in some stethoscopes, but can also be applied to other forms of monitoring such as echo imaging or sonograms, magnetic resonance imaging (MRI), computed tomography (CT) scanning, positron emission tomography (PET) scanning, and monitoring using various forms of catheterization. The techniques and methods herein are primarily applicable to monitoring of heart valve events, but can be alternatively applied to other types of involuntary biological signaling emanating from the brain, intrauterine, pre-natal contractions, or elsewhere within both humans and other species.
Examples of vibration objects are Mitral valve opening and closing, Aortic valve opening and closing, Pulmonary valve opening and closing, Tricuspid valve opening and closing, and heart wall motions. A portion of the energy produced by these vibrations lies in the infra-sound range, which falls in the inaudible and low sensitivity human hearing range. A portion of the energy produced by these vibrations falls in the audible hearing range. For example, the vibration objects from the Mitral, Tricuspid, Aortic, and Pulmonary valve openings fall in a lower range of vibrations such as 0 to 60 Hertz, whereas vibration objects from the Mitral, Tricuspid, Aortic, and Pulmonary valve closings fall in a higher range of vibrations such as 50 to 150 Hertz. Accelerometer transducers placed on the chest capture these vibrations from both these ranges. Data is obtained using a tri-axial accelerometer or multiple tri-axial accelerometers placed on different points of a torso of a subject.
Source separation analysis in accordance with the methods described herein extract individual vibration objects from the composite vibration signal captured on the surface. The individual vibration signals are identified to be from the mitral valve, aortic valve, tricuspid valve, and the pulmonary valve during individual heart beats. Along with separating breathing sounds, and heart wall motion. The identified valve signals are marked to indicate their start and end of the event with respect to the start of the electrocardiogram (EKG). This event corresponds to the opening and closing of each valve. The individual vibration signals are identified to be from the mitral valve, aortic valve, tricuspid valve, the pulmonary valve, coronary artery, murmurs, third sound, fourth sound, respiratory sound, breathing, and snoring during individual heart beats.
The exemplary embodiments may be further understood with reference to the following description and the appended drawings, wherein like elements are referred to with the same reference numerals. The exemplary embodiments describe a system and method of extraction, identification, marking and display of the heart valve signals. Specifically, psychoacoustics are considered in separating cardiac vibration signals captured through the transducers. The system, the psychoacoustics, and a related method will be discussed in further detail below.
The exemplary embodiments provide a novel approach for small, portable, robust, fast and configurable source separation based software with transducer hardware. The use of the vibration signal pattern and novel psychoacoustics help bypass conventional issues faced by linear time invariant systems.
The signals of the biomechanical system show a high clinical relevance when auscultated on the chest. The heart and lung sounds are applied to the diagnosis of cardiac and respiratory disturbances, whereas the snoring sounds have been acknowledged as important symptoms of the airway obstruction. The innovation here provides extraction of all three types of body sounds from the composite vibration captured at the skin. The exemplary embodiments of the system and method proposed here for source separation can use the composite signal capture via different transducers not limited to accelerometer, acoustic, or piezoelectric 102. Any of these act as an electro-acoustic converter to establish a body sound for processing. The source separation provides the capability to extract signals while operating in a medium that is non-linear and time variant.
The exemplary embodiments of the system and method proposed here are shown in
The exemplary embodiments of the system 200 and method proposed here for the source extraction, identification, and marking of the heart valve signals are shown in
The exemplary embodiments of the system and method proposed here for the source extraction, identification, and marking of the heart valve signals from a composite signal 300 are shown in
The exemplary embodiments of the system and method proposed here draw inspirations from biology with respect to the cardiac cycle in-relation with electrocardiogram and accelerometer transducer captured cardiac signal. A timeline chart 400 in
The exemplary embodiments of the system and accompanying method proposed herein provide a source separation analysis algorithm that allows for the separation of the vibrations from the cardiohemic system as illustrated in the system 500 of
The exemplary embodiments of the system and method proposed here provide a source identification algorithm for the vibrations from the cardiohemic system. Referring to
The exemplary embodiments of the system and method proposed here provide a source marking algorithm for the vibrations from the cardiohemic system. Next step is to use PCA to determine which source is associated with which event (Mitral closing & opening, Tricuspid closing & opening, Aortic opening & closing, Pulmonic opening and closing). The following is a description of the architecture for automatic source tagging and timing of valvular events. One way to identify which events are relevant to a source is by manually tagging the sources against the synchronized EKG signal and taking advantage of the timings relative to the QRS wave (identification of the S1 and S2 sounds using the EKG signal as the reference has been widely researched in studies). Another approach is an automatic tagging algorithm. The tagging is composed of a classifier preceded by a feature extraction algorithm. For the timing, we exploit the computations of one of the feature extraction algorithms to obtain an energy contour from which the time location of a given event can be inferred. Because our work builds upon having the ability to capture the signal at different locations simultaneously, we want to exploit the relations among channels to extract additional information about the sources. Likewise some source separation algorithms where channel relations are associated with location, the embodiments herein can leverage on the intrinsic relations among the channels to extract relevant information that helps distinguish among the events. In some embodiments, a system or method can hypothesize that phase information between channels is relevant for distinguishing among cardiac events since valves are located at different positions within the heart. Perhaps, one of the most distinctive features of the cardiac events is their relative order of occurrence, which repeats periodically with each heartbeat. Time information extracted from the set of sources can be utilized to localize the occurrence of each source signal within the heart cycle. Therefore, the features proposed here are conceived to provide three aspects: 1) Spectral information, 2) Relations among channels, and 3) Relations among events in the form of relative times of occurrence.
The exemplary embodiments of the system and method proposed here provide a source marking algorithm that allows from the explanation earlier for the marking of the Mitral valve closing (MC), Mitral valve opening (MO), Aortic valve opening (AO), Aortic valve closing (AC), Tricuspid valve closing (TC), Tricuspid valve opening (TO), Pulmonary valve closing (PC) and Pulmonary valve opening (PO) signals. The extracted individual valve vibration objects are aligned into a signal for each of the four valves across multiple heart beats. The chart 700 in
In the exemplary embodiments, various novel ways of source separating individual heart vibration events from the composite vibration objects captured via multiple transducers can work on a single package that is embodied by an easy-to-use and portable device. Of course, more complicated embodiments using the techniques described herein can use visual sensors, endoscopy cameras, ultrasound sensors, MRI, CT, PET, EEG and other scanning methods alone or in combination such that the monitoring techniques enable improvement in terms of source separation or identification, and/or marking of events such as heart valve openings, brain spikes, contractions, or even peristaltic movements or vibrations. Although the focus of the embodiments herein are for non-invasive applications, the techniques are not limited to such non-invasive monitoring. The techniques ultimately enable diagnosticians to better identify or associate or correlate detected vibrations or signaling with specific biological events (such as heart valve openings and closings, brain spikes, fetal signals, or pre-natal contractions.)
The exemplary embodiments develop novel methods of source identification, which in one embodiment uses the Pulmonary and Aortic auscultation locations, and in addition possibly the Tricuspid and Mitral auscultation locations, enabling the system to identify individual valve events from the vibrations.
In yet other exemplary embodiments, novel methods of source marking can use the Pulmonary and Aortic auscultation locations, and in addition possibly the Tricuspid and Mitral auscultation locations, enabling the time marking of the occurrence of the individual valve events with respect to the electrocardiogram. Such a system capable and suitable of measuring cardiac time intervals in a simple and non-invasive fashion.
Other exemplary embodiments provide tracking of individual valve signals over time. Such novel methods allow for both short-term and long-term discrimination between signals. Short-term pertains to tracking individual stream when they are captured simultaneously as part of the composite signal. Long-term tracking pertains to tracking individual streams across multiple heart beats, tracking valve signals as they transition in and out during each cardiac cycle.
Some of the exemplary embodiments of a system and method described herein includes an embedded hardware system, the main elements to capture body sounds that can include a sensor unit that captures the body sounds, performs digitization, and further digital processing of the body sounds for noise reduction, filtering and amplification.
It will be apparent to those skilled in the art that various modifications may be made in the present embodiments disclosed without departing from the spirit or scope of the claims. Thus, it is intended that the scope of the embodiments cover the modifications and variations within the scope of the claims recited and provided they come within the scope of the methods and systems described and their equivalents.
Claims
1. A sensor array device, comprising: at least one or more processors operatively coupled to the portable device and configured to separate and identify separated vibration sources and further configured to identify a plurality of individual heart vibration events from the composite vibration objects; and
- a portable device configured to capture composite vibration objects from at least one sensor and further configured to communicate with a wireless node;
- an electrode for sensing an electrocardiogram signal;
- wherein the at least one or more processors is further configured to mark individual heart events from the plurality of individual heart vibration events with respect to each other or with respect to the electrocardiogram signal.
2. The sensor array device of claim 1, wherein the at least one sensor is configurable for measuring a lower frequency range vibration signal and a higher frequency range vibration signal.
3. The sensor array device of claim 1, wherein the at least one or more processors is operatively coupled to the at least one sensor, the at least one or more processors further being configured for separating the plurality of individual heart vibration events from the composite vibration objects.
4. The sensor array device of claim 1, wherein the at least one or more processors is further configured to transmit the composite vibration signals or the plurality of individual heart vibration events to a remote device.
5. The sensor array device of claim 1, wherein the at least one or more processors is further configured to mark and present individual valve events from the plurality of individual heart vibration events with respect to a QRS of an electrocardiogram signal.
6. The sensor array device of claim 1, wherein the at least one sensor comprises a sensor configured for placement near a pulmonary location, or a sensor configured for placement near an aortic location, or a sensor configured for placement near a tricuspid location or for placement near a mitral location.
7. The sensor array device of claim 1, wherein the at least one or more processors is configured to separate the plurality of individual heart vibration events from the composite vibration objects from multichannel signals using source separation approaches selected among one or more of Determined Models, Principal Component Analysis (PCA), Independent Component Analysis ICA, Singular Value Decomposition (SVD), Bin-wise Clustering and Permutation posterior probability Alignment, Undetermined Models, Sparseness condition, Dictionary learning, Convolutive models, K-SVD, Matching Pursuit.
8. The sensor array device of claim 1, wherein the one or more processors is configured to separate the plurality of individual heart vibration events from the composite vibration objects from multichannel signals by decomposing the multichannel signals into sparse activation patterns that appear sparsely across a time chart using a sparse coding module, clustering the sparse activation patterns, and recomposing a plurality of source streams by applying an activation mask to the sparse activation patterns assigned to a cluster using basis elements where time locations of activation patterns are clustered together and assigned to the same source.
9. The sensor array device of claim 1, wherein the sensor array device is portable and captures synchronized sensor data to a memory and wherein the operatively coupled processor is configurable in the process of separating the plurality of individual heart vibration events from the composite vibration objects into separate vibration sources and further identifying the individual heart vibration events among at least one of a mitral valve closing, mitral valve opening, a tricuspid valve closing, a tricuspid valve opening, an aortic valve closing, an aortic valve opening, a ventricle event, an atrium event, a heart wall vibration event, or a pulmonary valve closing, or a pulmonary valve opening or a breathing event.
10. The sensor array device of claim 1, further comprising a wireless connection for transmission of sensor data or processed sensor data to a remote computing device or a cloud computing device.
11. The sensor array device of claim 1, wherein the one or more processors generates signals enabling the presentation of the individual heart vibration events on a visual display extracted from body sounds from the composite vibration objects to aid in diagnosing one or more among pulmonary disease, respiratory disease, coronary artery disease, heart murmurs, valve abnormalities, heart failure, heart rhythm abnormalities or arrhythmias, vascular disease, congenital heart disease, apnea, cardiac resynchronization and risk factor modification.
12. The sensor array device of claim 1, wherein the composite vibration signal capture is performed via vibration sensing sensors.
13. The sensor array device of claim 12, wherein the one or more processors are configured to present the individual heart events with respect to a QRS of the electrocardiogram enabling diagnosticians to correlate detected vibrations or signaling with specific biological events selected among heart valve openings and closings, valve abnormalities, murmurs, breathing events, heart wall motion events, ventricle events, atrium events, heart rhythm abnormalities or arrhythmias, apnea signals, biological signaling emanating from the brain, intrauterine, pre-natal contractions, or fetal signals using the sensor array device.
14. The sensor array device of claim 1, wherein the one or more processors are further configure to separate sources from the composite signals by source estimation using at least one among machine learning, auditory scene analysis, or sparse coding, or source separation.
15. A method of measuring cardiac time intervals using a sensor array device, comprising:
- capturing an electrocardiogram signal synchronized with composite vibration objects using at least one sensor and wherein an electrode is used for sensing the electrocardiogram signal;
- communicating with a wireless node using one or more transceivers coupled to the at least one vibration sensor;
- separating and identifying separate vibration sources and further identifying a plurality of individual heart vibration events from the composite vibration objects using at least one or more processors operatively coupled to the sensor array device; and
- marking individual heart events from the plurality of individual heart events with respect to each other or with respect to the electrocardiogram signal using the at least one or more processors.
16. The method of measuring cardiac time intervals of claim 15, wherein the one or more processors transmit the composite vibration signals or the plurality of individual heart vibration events to a remote device.
17. The method of measuring cardiac time intervals of claim 15, further comprising presenting the individual heart vibration events on a visual display extracted from body sounds from the composite vibration objects to aid in diagnosing one or more among pulmonary disease, respiratory disease, coronary artery disease, heart murmurs, valve abnormalities, heart failure, heart rhythm abnormalities or arrhythmias, apnea, vascular disease, congenital heart disease, cardiac resynchronization and risk factor modification.
18. A sensor device, comprising:
- a portable device configured to capture composite vibration objects from at least one sensor and further configured to communicate data to a wireless node;
- at least one or more processors operatively coupled to the portable device and configured to separate and identify separated vibration sources and further configured to identify a plurality of individual heart vibration events from the composite vibration objects;
- wherein the at least one or more processors is further configured to mark individual heart events from the plurality of individual heart vibration events.
19. The sensor device of claim 18, wherein the sensor device is a sensor array device and the portable device has at least two vibration sensing sensors.
20. The sensor device of claim 18, wherein the sensor device further comprises one or more electrodes for sensing an electrocardiogram signal and wherein the at least one or more processors is configured to mark the individual heart events from the plurality of individual heart vibration events with respect to each other or to the electrocardiogram.
Type: Application
Filed: Jul 24, 2019
Publication Date: Nov 14, 2019
Applicant: AventuSoft, LLC (Boca Raton, FL)
Inventors: Kaustubh Kale (Royal Palm Beach, FL), Luis Gonzalo Sanchez Giraldo (Miami, FL)
Application Number: 16/521,027