41 results about "Phonocardiogram" patented technology

Methods and systems for simulating a phonocardiogram (PCG) signal that includes an anomalous condition are provided. The method generates pressure and flow signals from a lumped-parameter heart model responsive to anomaly parameters. The anomaly parameters represent the anomalous condition. A timing profile or the timing profile and an amplitude profile are extracted from at least one of the generated pressure and flow signals. An anomalous signal is generated using the anomaly parameters and the extracted timing profile or timing profile and amplitude profile. The anomalous signal is time-aligned and combined with a predetermined non-anomalous signal to represent the PCG signal.

The present invention relates to a method for continuously measuring blood pressure and its equipment. Said method is characterized by that it creates a regression equation between pulse wave conduction time and arterial pressure: BP=a+b*PWTT for measurand person; and utilizes personalization correction technique to define intercept and regression coefficient b of measurand person. Besides, said invention also provides a method for continuously obtaining pulse wave conduction time PWTT by using pulse wave of human body, electrocardiogram signal and phonocardiogram signal and its concrete steps. Said method can raise accuracy for continuously measuring blood pressure, and can be used for measuring head blood pressure.

In a method of noninvasive measurement of parameters of diastolic function of left ventricle and automated evaluation of the measured profile at rest and with exercise, a patient performs an isometric exercise. An external pressure sensor and heart sounds microphone are applied in a non-invasive manner on the thoracic wall to obtain a left ventricular pressure mirroring curve (pressocardiogram) and simultaneously the heart sounds (phonocardiogram). An external unit determines and calculates characteristic diastolic parameters derived from the pressocardiographic curve and phonocardiogram at rest, during and after exercise, converts each said pressocardiogram into a digital waveform in the time domain, and automatically categorizes the mentioned characteristic parameters based on exact categorization criteria for defining several differentialforms of diastolic dysfunction of left ventricle in human beings.

An auscultation training system is disclosed comprising a half-body mannequin with speakers providing heart, lung, bowel and bruit sounds in the correct anatomical positions for student training of auscultation with a standard stethoscope. An integrated computer system provides the tools for training and assessing students. Synchronized phonocardiograms and a palpable carotid pulse accompany heart sounds. Sounds can be played and auscultated simultaneously to simulate a live patient, or played and auscultated separately for teaching purposes. The system may be accessed online using a virtual mannequin and stethoscope for viewing and listening to heart, lung, bowel and bruit sounds.

The invention provides a method of processing at least one heart sound signal, and the method comprises the step of: receiving (11) the at least one heart sound signal, segmenting (12) the heart sound signal into a plurality of segments, identifying (13) attribute information for each segment, annotating (14) each segment with corresponding attribute information, and outputting (15) an annotated Phonocardiogram for the at least one heart sound signal. The invention also provides a processing system for implementing the step of the methods as mentioned above.

The invention relates to a coronary heart disease surveillance and diagnosis device. The coronary heart disease surveillance and diagnosis device comprises a heart-lung signal collection device and aheart-lung signal analyzing device, wherein the heart-lung signal collection device collects heart-lung sound overlapped signals and sends the heart-lung sound overlapped signals to the heart-lung signal analyzing device, and the heart-lung signal analyzing device separates the heart-lung sound overlapped signals according to the short-time Fourier transform method so as to obtain an original heart sound signal; the original heart sound signal is reduced according to the double-threshold method, the peak picking method and the endpoint algorithm so as to obtain a phonocardiogram; the phonocardiogram is subjected to complex wavelet transformation so as to extract a signal envelop of the complex wavelet transformation; the signal envelop is trained according to a trained BP neural network soas to obtain an analysis result, and the analysis result is output. Based on the characteristic that in the early period of the coronary heart disease, high-frequency pathological murmur can occur inthe heart sound signal, the heart-lung sound overlapped signals are analyzed by using the short-time Fourier transform method, it is noninvasively and early diagnosed whether an examinee suffers fromthe coronary heart disease or not, and the diagnosis efficiency is high.

The invention provides a system for characterizing a patient undergoing hemodialysis, featuring: 1) a body-worn biometric sensor, worn on a single location of the patient, and featuring: i) sensing elements for measuring electrocardiogram (ECG), thoracic bio-impedance (TBI), photoplethysmogram (PPG), and phonocardiogram (PCG) waveforms; ii) a processor for collectively analyzing the ECG, TBI, PPG, and PCG waveforms to determine a set of physiological parameters; and iii) a first wireless transceiver configured to transmit the set of physiological parameters; 2) a gateway system comprising a second wireless transceiver configured to receive the set of physiological parameters; and 3) a data-analytics system configured to analyze the set of physiological parameters to determine the patient's status.

The invention provides an electrocardiogram phonocardiogram analysis method. The method comprises following steps: synchronously acquiring and synchronously recording electrocardiogram and phonocardiogram, and using the same timeline for the electrocardiogram and phonocardiogram; determining whether the P wave, R wave and T wave in the electrocardiogram can be identified; if the P wave, the R waveand the T wave in the electrocardiogram can be identified, the phonocardiogram corresponding to the RT interval is intercepted, and as the first waveform to be filtered, the phonocardiogram corresponding to the TP interval is intercepted as the second waveform to be filtered; if there is no pulse waveform in the first wave to be filtered, it is considered that S1 is missing and the heart is abnormal; if there is no pulse waveform in the second wave to be filtered, it is considered that S2 is missing and the heart is abnormal; if the electrocardio feature can not recognized in the electrocardiogram, the S1 waveform and the S2 waveform are identified from the phonocardiogram. If so, each S1 waveform and each S2 waveform are extracted; otherwise, abnormal heart condition signals are output.The invention has the advantages of being able to initially identify the function of the heart by using the matching relationship between the electrocardiographic characteristics and the heart sound characteristics, and is suitable for the advantages of home cardiac monitoring.

A method and system for detection of a coronary artery disease (CAD) in a person using a fusion approach has been described. According to the invention, CAD in the person is detected by capturing of aplurality of physiological signals such as phonocardiogram (PCG), photoplethysmograph (PPG), ECG, galvanic skin response (GSR) etc. from the person. A plurality of features are extracted from the physiological signals. The person is then classified as CAD or normal using each of the features independently. The classification is done based on supervised machine learning technique. The output of the classification is then fused and used for the detection of the CAD in the person using a predefined criterion.

The invention consists of a device and method for the prediction of left ventricular ejection fraction (EF) and other cardiac hemodynamic parameters using systolic time intervals in patients with narrow QRS, right bundle branch block, left bundle branch block, right ventricular and / or left ventricular cardiac pacing and in the presence of arrhythmia, such as atrial fibrillation. The device has three inputs: the ECG, a peripheral pulse and a phonocardiogram. Timing parameters are obtained from these signals to calculate a systolic function index, used for the prediction of ejection fraction. Given the invention's features it would be now possible to assess cardiac performance and specifically left ventricular ejection fraction in ambulatory patients as well as during invasive procedures such as the implant of cardiac rhythm management devices. Also, an implantable embodiment of the invention would allow constant monitoring of cardiac performance, parameter adjustment of cardiac devices and automatic drug infusion.

A system is provided for creating a sound profile that matches sounds produced by a patient during a physical examination, such as a cardiac or pulmonary examination. A user selects multiple sounds from a library and combines them to form the profile which may then be modified by the addition of further sounds, adjustments to their relative timing, duration, loudness, and so forth. The refinement continues iteratively, and after each change the profile is provided by the system to the user, for example, as a phonocardiogram for comparison against the sounds observed during the examination.

Provided is a household cardiac monitoring system based on electrocardio and cardiac sound analysis. The system comprises a portable electrocardio and cardiac sound meter and its disposable application; the disposable application comprises a paster with a viscose layer; the paster is provided with a cardiac sound probe and multiple electrocardio electrodes; the cardiac sound probe and the electrocardio electrodes are exposed from the viscose layer; electrocardiogram and phonocardiogram are input to the electrocardio and cardiac sound meter; a same timeline is used for the real-time synchronously acquired electrocardiogram and phonocardiogram and the user's heart rate is obtained from the electrocardiogram; identifying electrocardio characteristics in the electrocardiogram and locating phonocardiogram using the electrocardio characteristics and finding cardiac sound characteristics; when R wave and first cardiac sound S1 do not appear correspondingly , or T wave and second cardiac soundS2 do not appear correspondingly, or the first cardiac sound S1 is abnormal or the second cardiac sound S2 is abnormal, then outputting cardiac abnormality alarm. The invention has the advantages ofbeing able to simultaneously monitor the electrocardio and the cardiac sound signals, and locating the cardiac sound characteristics by the electrocardiographic characteristics, thereby facilitating the user to monitor the heart state at home.

The present invention refers to a signal processing apparatus and its method of operation. The apparatus comprises a phonocardiogram interface adapted to receive a phonocardiogram signal captured according to a first set of capturing properties, a processor adapted to analyze the phonocardiogram signal to determine an analysis result for the phonocardiogram signal and a confidence value of the determined analysis result, and a flow control adapted to determine, whether a subsequent capture of the phonocardiogram signal according to a second set of capturing properties is likely to improve an accuracy of the determined analysis result. If applicable the flow control coordinates the subsequent capture of the phonocardiogram signal according to the second set of capturing properties The invention also refers to a corresponding computer program product. Also described is a signal processing apparatus comprising a user interface adapted to present the captured phonocardiogram signal to a user and to receive a user correction. Based on the user correction the phonocardiogram signal may be reanalyzed.

The present invention relates to a method for continuously measuring blood pressure and its equipment. Said method is characterized by that it creates a regression equation between pulse wave conduction time and arterial pressure: BP=a+b*PWTT for measurand person; and utilizes personalization correction technique to define intercept and regression coefficient b of measurand person. Besides, said invention also provides a method for continuously obtaining pulse wave conduction time PWTT by using pulse wave of human body, electrocardiogram signal and phonocardiogram signal and its concrete steps. Said method can raise accuracy for continuously measuring blood pressure, and can be used for measuring head blood pressure.

A fetal phonocardiogram system featuring an array of acoustic sensors designed to be temporarily affixed to a pregnant patient to convert the vibrations associated with a fetal heartbeat and / or fetal movement into a signal. The signal can be amplified and transferred to a processing element for filtering non-fetal sounds in order to resolve the fetal heartbeat. The filtered signal can be used in conjunction with an array of multiple acoustic sensors to locate a fetal position relative to the array.

The invention discloses a phonocardiogram and electrocardiogram integrated diagnosis device. The device comprises monitoring devices and a fixing device; at least three holes are formed in the fixingdevice, the number of the monitoring devices corresponds to that of the holes, and the monitoring devices are fixed to the holes. Each monitoring device comprises an energy gathering head, a resonancethin film and a sensor, wherein the energy gathering head is arranged on the resonance thin film, the sensor is arranged below the energy gathering head, and the sensor is electrically connected withthe sensor. The phonocardiogram and electrocardiogram integrated diagnosis device is simple and reasonable in structure, low in cost, capable of simultaneously monitoring phonocardiograms and electrocardiograms, integrated and high in application value.

The invention relates to a synchronous diagnosis method and system based on electrocardio, heart sound and pulse, and mainly relates to the technical field of computer diagnosis. According to the method, the electrocardiogram, the phonocardiogram and the sphygmogram of a to-be-detected case are drawn according to the acquired electrocardio, heart sound and pulse of the to-be-detected case and thesynchronous acquisition time period; feature information of the electrocardiogram, the phonocardiogram and the sphygmogram is extracted according to preset rules, wherein the feature information comprises amplitude, frequency, harmonic delay, harmonic distortion, waveform change and maximum power density value; and the feature information is matched with preset feature information in a preset database to obtain the diagnosis condition of the to-be-detected case. According to the diagnosis method, the feature information of the electrocardiogram, the phonocardiogram and the pulse diagram can becompared with the feature information in the database, so that diseases can be found at the early stage of cardiovascular and cerebrovascular diseases or before the cardiovascular and cerebrovasculardiseases are attacked, and the cardiovascular and cerebrovascular diseases of the to-be-detected case can be diagnosed.

The invention discloses a method and a device for monitoring the pulmonary circulation blood pressure based on body surface phonocardiogram signals. In monitoring, the mechanical closing time of cardiac valves is used as an input parameter; and the parameters are periodically detected, and the change trend of the pulmonary circulation blood pressure is calculated according to the change trend of the parameters, so the noninvasive pulmonary circulation blood pressure is realized. Because the physiological relationship of the mechanical closing time of cardiac valves and pulmonary circulation blood stream dynamics are utilized in the method, the relative change trend of the pulmonary circulation blood pressure can be monitored under an uncalibrated condition. The equipment for monitoring the pulmonary circulation blood pressure is noninvasive, easy to operate, and low in cost.

The invention provides a waiting system based on electrocardio heart sound analysis. The system includes a host computer and a plurality of heart monitoring units, each heart monitoring unit is at least composed of a portable electrocardio heart sound instrument and a disposable plaster, each electrocardio heart sound instrument has a unique code, the disposable plaster includes a paster with a viscose layer, the paster is provided with a heart sound probe and a plurality of electrocardio electrodes, the electrocardio electrodes and the heart sound probe are exposed from the viscose layer, a triangle structure is arranged by three electrocardio electrodes, for each electrocardio heart sound instrument, an electrocardiogram and a phonocardiogram share one timeline, the heart rate of an useris obtained from the electrocardiogram, electrocardio characteristics are identified in the electrocardiogram, the phonocardiogram is positioned by the electrocardio characteristics, heart sound characteristics are searched, when first heart sound S1 and second heart sound S2 transmitted from the electrocardio heart sound instrument reach a severe level, the number of the electrocardio heart sound instrument is recorded, and the visit sequence of a patient who uses the electrocardio heart sound instrument is prioritized.

The present invention relates to a cerebrovascular analysis system which enables early diagnosis of various incurable cerebrovascular diseases such as cerebral thrombosis by measuring an elastic coefficient, blood vessel compliance, blood flow resistance, and blood flow in each cerebrovascular branch. The measurement is achieved by biomechanically analyzing blood vessels in the brain using an electrocardiogram, phonocardiogram, electroencephalogram, pulse wave, and ultrasonic doppler signal as basic data in order to measure biomechanical properties and blood flow properties of blood vessels in the brain for the diagnosis of cerebrovascular diseases.

Various embodiments of the inventions of the present disclosure provide a combination of feature-based approach and deep learning approach for distinguishing between normal heart sounds and abnormal heart sounds. A feature-based classifier (60) is applied to a phonocardiogram (PCG) signal to obtain a feature-based abnormality classification of the heart sounds represented by the PCG signal and a deep learning classifier (70) is also applied to the PCG signal to obtain a deep learning abnormality classification of the heart sounds represented by the PCG signal. A final decision analyzer (80) isapplied to the feature-based abnormality classification and the deep learning abnormality classification of the heart sounds represented by the PCG signal to determine a final abnormality classification decision of the PCG signal.

The invention consists of a device and method for the prediction of left ventricular ejection fraction (EF) and other cardiac hemodynamic parameters using systolic time intervals in patients with narrow QRS, right bundle branch block, left bundle branch block, right ventricular and / or left ventricular cardiac pacing and in the presence of arrhythmia, such as atrial fibrillation. The device has three inputs: the ECG, a peripheral pulse and a phonocardiogram. Timing parameters are obtained from these signals to calculate a systolic function index, used for the prediction of ejection fraction. Given the invention's features it would be now possible to assess cardiac performance and specifically left ventricular ejection fraction in ambulatory patients as well as during invasive procedures such as the implant of cardiac rhythm management devices. Also, an implantable embodiment of the invention would allow constant monitoring of cardiac performance, parameter adjustment of cardiac devices and automatic drug infusion.

The invention provides a method for determining peripheral pressure wave delay time in reconstruction of central arterial pressure. The method is used for reconstruction of central arterial pressure and includes the steps: synchronously measuring heart sound signals and peripheral pressure waves; determining delay time of pressure wave transmission from the center artery to the peripheral artery by taking time of aortic valve close component of a cardiac sound II as a starting point and taking an incision position of the peripheral pressure waves as a terminal point, wherein time of the aortic valve close component of the cardiac sound II is obtained by adopting short-time Fourier transform for processing phonocardiogram signals. In practical reconstruction of central arterial pressure, the method can be directly adopted for non-invasively determining delay time, and low result error and effectiveness in reconstruction can be achieved.

Methods and systems for simulating a phonocardiogram (PCG) signal that includes an anomalous condition are provided. The method generates pressure and flow signals from a lumped-parameter heart model responsive to anomaly parameters. The anomaly parameters represent the anomalous condition. A timing profile or the timing profile and an amplitude profile are extracted from at least one of the generated pressure and flow signals. An anomalous signal is generated using the anomaly parameters and the extracted timing profile or timing profile and amplitude profile. The anomalous signal is time-aligned and combined with a predetermined non-anomalous signal to represent the PCG signal.

The invention discloses a comprehensive heart detection device based on heart sound and electrocardiogram, which includes a signal processing system connected with several heart sound and electrocardiogram two-in-one probes, the signal processing system is connected with a terminal display device, and the heart sound and electrocardiogram two-in-one probe The integrated probe includes a sound sensor and electrodes for collecting heart sounds and electrocardiographic signals; the signal processing system is used for processing the collected heart sounds and electrocardiographic signals, and transmits the processed signals to the terminal display device; the terminal display The device is used to display phonocardiogram and electrocardiogram. The electrocardiographic electrode of the present invention can directly contact with the skin, improve the sensitivity and precision of the probe, detect heart sound and electrocardiogram at the same time, and contribute to disease diagnosis.

The present invention discloses a method and system for detecting abnormal heart sounds in a phonocardiogram of a person. At least one segmented cardiac cycle of the phonocardiogram is received at a processor. The processor decomposes the segmented cardiac cycle into a plurality of frequency sub-bands using a first convolutional neural network having, in particular a plurality of time-convolutionlayers (tConv). The kernel weights of each time-convolution layer are learned in a training process such that the time-convolution layers identify pathologically significant frequency sub-bands. The processor determines a probability that the segmented cardiac cycle contains an abnormal heart sound based on the plurality of frequency sub-band segments using at least one further neural network. Insome embodiments, the time-convolution layers are configured to have a linear phase response (LP-tConv) or a zero phase response (ZP-tConv).

The invention relates to a heart sound total variation filtering method based on pathology self-adaption, and belongs to the technical field of medical calculation biological feature recognition. The method comprises the steps that firstly, additive Gaussian white noise is added to an input original heart sound signal, a noise adding signal meeting the requirement is obtained through screening, then the noise adding signal is subjected to improved empirical mode decomposition, an intrinsic mode function under the maximum similarity is obtained through screening, and the original heart sound signal is segmented; information entropies of different segments of an original heart sound signal are calculated by using a linear coefficient-based tracking evolution algorithm, the information entropies are used as weight values to construct l1 of the heart sound signal and limit l1 regularization total variation equations, and improved Split-Bregman algorithm is used to respectively solve, and finally the heart sound signal fused with the two filtering results is obtained by using a moving average method. Compared with the prior art, the heart sound signal denoising method has the advantages that the original heart sound signal can be denoised more accurately, pathological information can be reserved, and a basis is provided for digital analysis of a phonocardiogram.