313 results about "Cardiac sounds" patented technology

Apparatus for use detection of apnea includes a microphone mounted in the ear of the patient for detecting breathing sounds and a second external microphone together with an oximetric sensor. A transmitter at the patient compresses and transmits the signals to a remote location where there is provided a detector module for receiving and analyzing the signals to extract data relating to the breathing. The detector uses the entropy or range of the signal to generate an estimate of air flow while extracting extraneous snoring and heart sounds and to analyze the estimate of air flow using Otsu's threshold to detect periods of apnea and / or hypopnea. A display provides data of the detected apnea / hypopnea episodes and related information for a clinician.

Apparatus for use detection of apnea includes a microphone mounted in the ear of the patient for detecting breathing sounds and a second external microphone together with an oximetric sensor. A transmitter at the patient compresses and transmits the signals to a remote location where there is provided a detector module for receiving and analyzing the signals to extract data relating to the breathing. The detector uses the entropy or range of the signal to generate an estimate of air flow while extracting extraneous snoring and heart sounds and to analyze the estimate of air flow using Otsu's threshold to detect periods of apnea and / or hypopnea. A display provides data of the detected apnea / hypopnea episodes and related information for a clinician.

The present invention relates to a heart disease automatic classification system based on heart sound analysis. It includes the following several portions: heart sound sensor, it is used for converting heart sound vibration signal of tested person into electric signal and outputting said electric signal; computer with multimedia function, it is connected with heart sound sensor by means of data acquisition card and can be used for recording the heart sound signal of tested person which is outputted by heart sound sensor and storing said signal in storage unit; and heart sound sectionalization program, heart sound characteristics extraction program and classification device which are mounted in the computer. Said invention also provides its working principle and its concrete operation method.

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.

The invention discloses a fiber-optic sensing intelligent garment and heart sound and blood pressure parameter processing methods thereof. The fiber-optic sensing intelligent garment comprises a garment body, a fiber Bragg grating pulse sensor, a fiber Bragg grating heart sound / breath sensor, an optical signal processing unit and an information processing terminal; the optical signal processing unit is used for wavelength demodulation and signal transmission; the information processing terminal is used for parameter information displaying, storage and remote communication. The heart sound parameter processing method of the fiber-optic sensing intelligent garment is a method of judging mathematical morphological peaks of heart sounds and mathematical morphological start-stop points through linear structure elements and cosine structure elements. The blood pressure parameter processing method of the fiber-optic sensing intelligent garment includes blood pressure model establishing and blood pressure estimating. The fiber-optic sensing intelligent garment has high electromagnetic interference resistance and high detection sensitivity, is applicable to places with strong magnetic field, high electromagnetic noise, strong radiation or the like and is applicable to body sign monitoring in magnetic resonance imaging, safety monitoring for physical conditions of mine workers, clothing of astronauts, safety clothing of fire fighters and the like.

A handheld auscultatory scanner continuously obtains a heart sound signal from a patient, using a noninvasive passive acoustic sensor, allowing free-form protocol, analysis and display of the heart sound signal on a handheld processing unit in a graphical manner such that a single heart cycle is displayed in a synchronized manner, along with summary results of the processing of the acoustic signal. The results are presented in terms of standard auscultatory findings. The combination of summary findings, heart sound display and audible signal provides a method for assisting in patient screening for heart conditions and for teaching auscultation techniques.

Methods and systems are disclosed that characterize cardiac function using an acceleration sensor to acquire and analyze the frequency dynamics associated with the isovolumic contraction phase (“ICP”). This information can be used to characterize heart function; optimize therapy for cardiomyopathy, including CRT therapy (including pacing intervals and required pharmacologic therapy); and to optimize CCM therapy. In addition, this information can be used to identify target pacing regions for CRT lead placement. Further, analyzing the frequency dynamics can be used to characterize pathologic heart vibrational motion, such as mitral regurgitation and the third or fourth heart sound, and the response of this motion to therapy for cardiomyopathy.

A method for acquiring, externally or internally, for utility purposes a subject's anatomical heart-sound information including (a) for a selected time period, applying continuous, near-sensor-mechanical-resonance, vibratory stimulation to an acoustic sensor placed on or within the subject's anatomy, and (b) during that time period, detecting, as direct indications of heart sounds, changes in the sensor's physical resonance properties produced by heart sounds arriving at the sensor.

A computer method, employable during an at-rest period of a pacemaker patient, for controlling the operation of the pacemaker so as maximally to support the patient's hemodynamic behavior in a context involving inhibiting fluid overload. The method involves (a) collecting simultaneously occurring ECG and heart-sound information, (b) processing the collected information to obtain at least S3 data, and in certain instances also EMAT and / or % LVST data, (c) utilizing such obtained data, and during the at-rest period, applying (a) pacing rate, (b) pacing intensity, (c) atrio-ventricular delay, and (d) inter-ventricular delay control to the pacemaker. Processing involves (a) calculating from the obtained data an actual, real-time, acoustic cardiographic therapy (AC) value which is to be employed in relation to controlling pacemaker activity, and (b) comparing the actual AC value to a pre-established, related, rest-period-associated, reference AC value to detect differences therebetween, with the utilizing and applying steps being implemented so as to minimize such differences.

An intelligent clothing based on MEMS technique for acquiring human physiological parameters including cardioelectric signals and cardiac sound features the integration of a flexible film containing sensor array with fabric. Its preparing process includes such steps as using MEMS technique to prepare sound / electricity transducers and electric interconnection on a wafer, etching to generate Si-island pattern on the back of wafer, coating polymer on both surfaces of wafer, photoetching to form sensor windows and sewing holes on a film, and integrating it with fabric by sewing.

The present invention is computerized multifunctional medical detecting and monitoring method and apparatus. Various signals of human body are first acquired by means of different kinds of sensors, such as electrocardiac sensor, temperature sensor, cardiac sound sensor, etc; and then amplified, filtered, shaped, A / D converted and transmitted to the computer via the data communication interface. The computer with human body detecting and monitoring application program performs analysis and calculation on the signals, shows the results in the display, stores selectively in the fixed disk, and sends out alarm signal in case of finding abnormal human body parameters via the Internet and computer network. The present invention is suitable for household medical monitoring and remote diagnosis.

The invention relates to segmentation of cardiac acoustic signals, such as the heart sound signal, based on statistical algorithms. A duration-dependent Hidden Markov Model is disclosed which models the shifting states of the heart, based on the cardiac acoustic signal and the time spent in the given states relating to physiological events, e.g. the various states of the heart during the heart beat cycle.

The invention relates to a method and a system for identifying heart-lung sound signals. The method includes the steps of acquiring heart / lung sounds initial detection signals, acquiring correspondingenvironment sound signals, and subjecting the heart / lung sounds initial detection signals to differential noise reduction processing, so as to prevent the influence of the peripheral environment on the cardio-pulmonary sound signals, prevent influence of signals irrelevant to the cardio-pulmonary sound signals on the identification precision, and effectively improve the collection and identification precision of the cardio-pulmonary sound signals. The heart sound simulation signals is processed through combination of EMD (Empirial Mode Decomposition) and a high-order shannon entropy algorithm, and a wavelet decomposition is used for processing the lung sound digital signals. Accurate recognition of the characteristics of the heart sound signals and the lung sound signals is achieved, andthe identification steps of the cardio-pulmonary sound signals are effectively simplified. The real-time performance is higher, and the cost is low.

A system, operatively connectable both to a cardiac-rhythm-management (CRM) subject, and to a CRM device associated with that subject, and an associated method, operable, in relation to received-and-processed, real-time, CRM-subject-specific, simultaneous ECG and heart-sound information, and other information including measurement time markers where available, for blocking, under all circumstances during the ventricular relative refractory period lying within each of successive CRM-subject cardiac cycles occupying a span of such cycles, the ventricular pacing activity of the subject-associated CRM device—the beginning and ending of such blocking in each cardiac cycle being system-defined to lie preferably, and respectively, (a) within the real-time, ventricular depolarization window in the cycle, and (b) at the time of the real-time, S2 heart-sound, plus or minus any user-defined time-delta.

The invention discloses a cardiac sound diagnostic system based on a depth confidence network and a diagnostic method of the cardiac sound diagnostic system. The cardiac sound diagnostic system comprises a cardiac sound diagnostic terminal, a network interface module, a database module, a data analyzing module, and a data management module; the data management module is connected with the database module, the data analyzing module and the network interface module at the same time, and the database is connected with the data analyzing module at the same time; the network interface module is in signaling connection with the cardiac sound diagnostic terminal. The diagnostic method is based on a depth confidence network model consisting of restricted Boltzmann machine layering; the diagnostic method comprises the steps: using a patient's cardiac sound file database; training the established depth confidence network by using a layer-by-layer greedy algorithm; inputting the cardiac sound signal to be diagnosed to the depth confidence network model after training; obtaining the final diagnostic result at an output layer and returning to the cardiac sound diagnostic terminal. The cardiac sound diagnostic system based on the depth confidence network and the diagnostic method can realize the remote diagnosis of patient's cardiac sound signals; the operation is convenient and simple, the diagnostic accuracy is high, the cost is low; besides, the device is convenient to maintain and upgrade.

A method employable during a tachycardia-tachyarrhythmia condition in a person for detecting, verifying and distinguishing ventricular and supra-ventricular tachyarrhythmias, including ventricular fibrillation, including (a) confirming the presence of a tachyarrhythmia heart rate, (b) on such confirmation, collecting time-frame-simultaneous ECG and heart-sound information, (c) following such collecting, choosing selected ECG time-span, and heart-sound intensity, data, and (d) utilizing the chosen, selected ECG time-span, and heart-sound intensity, data, characterizing the defined condition as resulting from one of (a) supra-ventricular tachyarrhythmia, (b) ventricular tachyarrhythmia, and (c) ventricular fibrillation.

The invention discloses a wearable cardiac sound monitoring device. The wearable cardiac sound monitoring device comprises a wearable cardiac sound acquiring and sensing module, a mobile phone cardiac sound signal receiving and processing information module and a central server, wherein the wearable cardiac sound acquiring and sensing module consists of a microphone, a signal amplifying and transmitting circuit, a microprocessor, a wireless transmission module, an earphone shell and a wearable fixing device; a cardiac sound signal of a user is collected through the wearable cardiac sound acquiring and sensing module, and passes through the signal amplifying and transmitting circuit, namely, a circuit amplifying circuit and an A / D (Analog to Digital) sampling circuit to obtain a cardiac sound electronic signal; the cardiac sound electronic signal is transmitted to mobile phone equipment through wireless transmission equipment; the corresponding cardiac sound signal receiving and processing information module is arranged on a mobile phone; the received cardiac sound electronic signal is subjected to digital filtration and computation to obtain corresponding cardiac sound information; the acquired cardiac sound information is transmitted to the central server through the mobile phone. An algorithm is implemented through an algorithm, an entropy relation between a fuzzy signal and a signal is used for predicting the future health state of heart through computation, and the user is promoted of matters needing attention in advance.

The invention provides a method for recognizing ultrasonic spectrum enveloped peaks by combining cardiac sound, which comprises the following steps: synchronously acquiring cardiac output signals and cardiac sound signals in relevant positions of human bodies by simultaneously adopting a Doppler ultrasonic probe and a cardiac sound probe, and inputting the cardiac output signals and the cardiac sound signals into a computer for processing; combining the cardiac output signals and the cardiac sound signals by the computer to automatically analyze effective peaks, and enveloping the effective peaks; and then, computing cardiac output parameters and cardiac sound parameters. The invention can more effectively extract real peaks, simultaneously can acquire relevant parameters capable of reflecting cardiac functions by computing effective enveloped peaks, can effectively acquire multiple parameters of spectrum enveloped peaks, and can really reflect basic physical conditions and changes of cardiac functions of human bodies.

The invention relates to a method for detecting the pulmonary artery blood pressure by using a heart sound analysis method of a multilayer feedforward network. The method comprises the steps of: extracting a heart sound signal; preprocessing the heart sound signal by fast Fourier transform and normalized average Shannon energy distribution to obtain heart sound signal features; filtering the heart sound signal features by using a principal component analysis method; and performing training learning on the filtered hear sound signal features by using a perceptron neural network or a multilayer perceptron feedforward neural network to obtain an optimal neural network between the heart sound signal features and a pulmonary artery blood pressure value. The heart sound signal features are signal features of a first heart sound and a second heart sound; the heart sound signal features comprise crest frequency, average frequency, crest amplitude, average amplitude, duration and time interface of heart sounds. By adopting the method for detecting the pulmonary artery blood pressure by using the heart sound analysis method of the multilayer feedforward network, provided by the invention, the pulmonary artery blood pressure can be easily and conveniently detected at low cost in a non-intrusive and no risk manner.

The invention discloses a health reserve evaluation method. The health reserve evaluation method comprises the following steps: a system converts received human pulse beat signals, heart sound signalsand ECG signals into point process signal data; the system performs composite variable analysis of a health reserve value on the point process signal data, and forms a monotonic function reflecting the healthy reserve state; and the system performs qualitative and quantitative determination of human health according to statistical distribution parameters of the health reserve values of the population. A health reserve evaluation system / device includes a data acquisition unit, a data conversion unit, a data analysis unit, a health status evaluation unit, and a health reserve evaluation application. The evaluation method of the health state and change thereof is simple and reliable, is easy to implement, can perform repeat measurement and evaluation, can be widely used in many fields such as health evaluation, health guidance, exercise rehabilitation guidance and the like of the general population.

The invention provides a Doppler fetal cardiac sound instantaneous heart rate detecting method based on blind separation. The detection method comprises the following steps that the Doppler fetal cardiac sound is subjected to denoising preprocessing through a low-pass filter; the processed ultrasonic Doppler fetal cardiac sound is subjected to time-frequency analysis, and the short-time Fourier transform is utilized for solving the time-frequency diagram of the ultrasonic Doppler fetal cardiac sound signals; several characteristic frequency bands are selected from the time-frequency diagram according to the priori knowledge of the periodic characteristic of the time-frequency diagram of the fetal cardiac sound signals, then, different selected frequency band signals are subjected to Fast ICA analysis, independent components are worked out, then, the independent component IC which is most matched with the fetal cardiac sound signals is determined, next, a self-correlation function of the most matched independent component IC is calculated, the peak value is detected, and finally, the fetal cardiac sound heart rate is calculated. The Doppler fetal cardiac sound instantaneous heart rate detecting method is used for calculating the instantaneous heart rate on the clinically collected ultrasonic Doppler fetal cardiac sound signals and has the advantages that the method is simple, the calculation speed is high, the flexibility is good, and the accuracy is high.

The invention discloses a blue tooth wireless heart function parameter monitoring system comprising a embed blue tooth wireless patient monitor, a blue tooth switch-in terminal, and a platform of medical monitoring system, wherein, the embedded blue tooth wireless monitor is connected to the platform of medical monitoring system via the blue tooth switch-in terminal. The invention also discloses the application of said blue wire heart function parameter monitoring system for the patient side monitoring, the short-range central monitoring and the remote medical monitoring. In addition, the invention can reflects the physical status of human body in reality with lower cost and higher reliability; and the invention can collect variable physiological parameters as electro-cardio-signal, heart rate, cardiophonogram, the blood oxygen saturation and the body temperature to be wireless transmitted by the blue tooth technique. So it can help the medical staff monitor the state of patient and prevent the exacerbation of the condition.

The invention relates to a portable wireless electrocardiogram, cardiac sound and breath sound acquisition, display and storage device which comprises a cardiac sound / breath sound sensor, a first low-noise amplifier, a second low-noise amplifier, a signal conditioning circuit, an electrocardiogram sensor, a low and high pass filter, an A / D (Analog to Digital) converter, a CPU (Central Processing Unit) processor, a keyboard, a wireless transmitting / receiving module and an LED indicator light, wherein the cardiac sound / breath sound sensor is connected with the signal conditioning circuit through the first low-noise amplifier and then connected with the CUP processor through the A / D converter; the electrocardiogram sensor is connected with the low and high pass filter through the second low-noise amplifier and then connected with the CPU processor through the A / D converter; and the CPU processor is used for carrying out wireless transmission of signals through the wireless transmitting / receiving module. The device has the characteristics of synchronously acquiring physiological parameter data such as electrocardiograms, cardiac sound, breath sound, and the like of a human body and transmitting the data to a display and storage machine in real time through the wireless transmitting / receiving module, displaying and storing or replaying the electrocardiograms and frequency spectrograms of the cardiac sound and the breath sound and playing the cardiac sound and the breath sound, and providing more visual diagnostic data for doctors; and the device can provide quick diagnosis information of common diseases such as arrhythmia, structural heart diseases, lung diseases, and the like.

The invention provides an abnormal heart sound recognition method based on sub-band energy envelope autocorrelation characteristics and relates to an abnormal heart sound recognition method. The abnormal heart sound recognition method is used for solving the problems in heart sound recognition that heart sound segmentation is depended, longer signals cannot be processed, and adaption to the characteristic extraction and classified recognition in a real noise environment cannot be realized. The method comprises the steps: carrying out energy standardization on input heart sound signals, then, carrying out down-sampling, and carrying out band-pass filtering; respectively computing an autocorrelation sequence of approximate sub-band energy envelope signals and an autocorrelation sequence of detailed sub-band energy envelope signals, and respectively intercepting first M values, which serve as approximate sub-band energy envelope autocorrelation characteristics and approximate sub-band energy envelope autocorrelation characteristics of the input heart sound signals, from the two sequences; respectively constructing two RM-space-to-Re-space scattering mappings, which act on the energy envelope autocorrelation characteristics, according to the energy envelope autocorrelation characteristics; carrying out dimensionality reduction, and then, merging to obtain the energy envelope autocorrelation characteristics of the heart sound signals; carrying out characteristic extraction on test data, and classifying the data by imputing the test data in a classification model. According to the method, a heart sound segmentation process is avoided, and the robustness in a noise environment is improved.

The present invention relates to A system for monitoring the cardiovascular system using a heart sound, which comprises a heart sound receiving means(100) for receiving a heart sound(HS); DSP (Digital Signal Processor) module(200) for converting the heart sound(HS) received from said heart-sound receiving means(100) to a digital signal; and an arithmetic section(300) for calculating phonocardiogram(PCG) from the digital signal converted in the DSP module (200) and calculating information related to a preload or information related to a cardiac contractile force or information related to a respiratory change.

According to the embodiment, the invention discloses a method and equipment for transmitting cardiac sound data. The method comprises the following steps: collecting cardiac sound signals by virtue ofa sensor at a configurable sampling frequency; and in accordance with configurable signal processing parameters, processing the collected cardiac sound signals, so that the cardiac sound data is generated, wherein the cardiac sound data includes at least one of a heart rate, a first cardiac sound amplitude, a second cardiac sound amplitude, diastole time limit and systole time limit. The method further comprises the following steps: packaging the cardiac sound data into a data package, and transmitting the data package to electronic equipment by virtue of a low-power-consumption Bluetooth channel, wherein the data package at least includes identification fields and cardiac sound data fields. According to the embodiment, the cardiac sound signals are collected and processed by virtue of the configurable processing parameters, and the cardiac sound data package in a preset format is transmitted through low-power-consumption Bluetooth, so that the cardiac sound data can be transmitted efficiently with low power consumption.

The invention discloses a heart sound, lung sound and fetal heart sound acquisition and health management system, which comprises an acquisition terminal, a transmission system, a platform processing system and a storage and display system, wherein the acquisition terminal is used for acquiring the heart sound or lung sound or fetal heart sound condition of a human body, and converting the heart sound or lung sound or fetal heart sound condition into an electric signal; the acquisition terminal is in communication connection with the transmission system through a wired network or a wireless network, and the transmission system is a mobile phone; the transmission system is in communication connection with the platform processing system through the wireless network, and the platform processing system is a health management service cloud platform; the storage and display system is a mobile phone, and is in communication connection with the platform processing system through the wireless network. According to the system, the heart sound, the lung sound and the fetal heart sound of the human body are acquired by the acquisition terminal or a microphone, are transmitted to the mobile phone after being subjected to processing such as data conversion and amplification filtration, and are transmitted to the health management service cloud platform through the mobile phone, and a health management report of the human body is obtained for the timely query of the human body through the mobile phone.

The invention discloses a non-negative matrix factorization-based heart and lung sound separation method. The method comprises the steps of firstly filtering a mixed signal of heart and lung sounds in a time domain to obtain a priori heart sound signal and a priori lung sound signal; secondly performing short-time Fourier transform and sparse non-negative matrix factorization on the priori heart sound signal and the priori lung sound signal; and finally obtaining a basis matrix of the mixed signal. The sparse non-negative matrix factorization process is equivalent to a learning process of the basis matrix, and has a clustering effect; the basis matrix can be mined effectively from the priori heart sound signal and the priori lung sound signal; and a heart sound signal and a lung sound signal are accurately separated from the mixed signal of the heart and lung sounds in the time domain according to the basis matrix in the subsequent steps. The invention furthermore discloses a non-negative matrix factorization-based heart and lung sound separation apparatus, which has the abovementioned beneficial effects.