A Support Vector Machine trained responsive to mean and median values of standard and Shannon energy for a plurality of time and frequency intervals within a heart cycles provides for detecting coronary artery disease (CAD). A quality of an auscultatory sound time-series vector is assessed responsive to a vector distance and angle thereof in relation to a median heart cycle vector.
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
A61B 5/0245 - Measuring pulse rate or heart rate using sensing means generating electric signals
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
A metallic diaphragm disk incorporating a piezoelectric material bonded thereto and operatively coupled to a base rim of a housing provides for closing an open-ended cavity at the first end of the housing. At least one inertial mass is either incorporated in or attached to the housing. A plastic film adhesively bonded to at least one of an outer rim of the housing or an outer-facing surface of the disk provides for receiving an adhesive acoustic interface material to provide for coupling the housing to the skin of a test subject.
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
B06B 1/08 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with magnetostriction
G01H 11/08 - Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means using piezoelectric devices
B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
An auscultatory sound signal from at least one auscultatory sound-or-vibration sensor is filtered with a high-pass filter and then segmented into a plurality of associated heart cycle segments responsive to associated R-peak locations of an electrographic envelope signal representing an envelope response to an even power of an associated electrographic signal from an ECG sensor. A representation an envelope responsive to an even power of said auscultatory sound signal within said at least one heart cycle is locally modeled about at least a second peak to provide for locating the start of diastole of said at least one heart cycle.
At least one swing value is determined responsive to a difference between maximum and minimum amplitude values of an auscultatory sound signal within a temporal region of a heart-cycle segment spanning an entire heart cycle of an auscultatory sound signal, wherein a location of at least one temporal region is responsive to a duration of the heart-cycle segment. S4 sound presence is detected responsive to ratio of S4SWING to S2SWING in relation an associated median value thereof from a population of test-subjects. A Support Vector Machine trained responsive to age, sex, S4 presence and a plurality of heart sound swing measures provides for detecting CAD. Unsupervised classification of an S3swing and median and mean values of a Short Time Fourier Transform within associated frequency intervals, based upon data from a plurality of heart cycles of a plurality of test-subject provides for detecting presence of an S3 sound.
A61B 5/0245 - Measuring pulse rate or heart rate using sensing means generating electric signals
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
A Support Vector Machine trained responsive to mean and median values of standard and Shannon energy for a plurality of time and frequency intervals within a heart cycles provides for detecting coronary artery disease (CAD). S4 sound presence is detected responsive to ratio of S4 swing to S2 swing in relation an associated median value thereof from a population of test- subjects. A Support Vector Machine trained responsive to age, sex, S4 presence and a plurality of heart sound swing measures provides for detecting CAD. Unsupervised classification of an S3 swing and median and mean values of a Short Time Fourier Transform within associated frequency intervals, based upon data from a plurality of heart cycles of a plurality of test-subject provides for detecting presence of an S3 sound.
A Support Vector Machine trained responsive to mean and median values of standard and Shannon energy for a plurality of time and frequency intervals within a heart cycles provides for detecting coronary artery disease (CAD). S4 sound presence is detected responsive to ratio of S4 swing to S2 swing in relation an associated median value thereof from a population of test- subjects. A Support Vector Machine trained responsive to age, sex, S4 presence and a plurality of heart sound swing measures provides for detecting CAD. Unsupervised classification of an S3 swing and median and mean values of a Short Time Fourier Transform within associated frequency intervals, based upon data from a plurality of heart cycles of a plurality of test-subject provides for detecting presence of an S3 sound.
An auscultatory sound-or-vibration sensor electronic test signal applied to a sound generator generates an acoustic sound signal, responsive to which an auscultatory sound-or-vibration sensor in proximity to the sound generator generates a corresponding auscultatory sound signal. The auscultatory sound-or-vibration sensor electronic test signal incorporates a plurality of frequency components, each frequency component of which incorporates an integral number of wavelengths and is terminated following a duration of time corresponding to the integral number of wavelengths after that frequency component is applied to the corresponding sound generator. A determination of whether or not the auscultatory sound-or-vibration sensor is functioning properly is made responsive to an analysis of a Fourier Transform of the auscultatory sound signal.
At least one sound generator operatively coupleable to a corresponding at least one auscultatory sound-or-vibration sensor provides for generating a corresponding at least one sound signal that is applied to the corresponding at least one auscultatory sound-or-vibration sensor. For each sound generator and corresponding auscultatory sound-or-vibration sensor operatively coupled thereto, a communications interface provides for receiving a corresponding auscultatory sound signal from the corresponding auscultatory sound-or-vibration sensor, and at least one computer processor operatively coupled to the communications interface provides for either generating, or causing to be generated, an electronic audio signal that drives the sound generator, causing a corresponding at least one sound signal to be generated thereby, and at least one computer processor provides for analyzing the auscultatory sound signal from the corresponding auscultatory sound-or-vibration sensor responsive thereto for determining whether or not the corresponding at least one auscultatory sound-or-vibration sensor is functioning properly.
Each conductor of a plurality of insulated conductors of a wiring harness extends between, and electrically connects, a corresponding terminal of a first electrical connector to either a corresponding terminal of an electrical connector jack of a plurality of electrical jacks located along the wiring harness, or to a corresponding terminal of a corresponding auscultatory sound-or-vibration sensor of the plurality of auscultatory sound-or-vibration sensors. The plurality of insulated conductors are organized in a plurality of distinct branches, each distinct branch originating either from the first electrical connector or from another portion of the wiring harness, and the locations of the plurality of distinct branches, in cooperation with the plurality of electrical jacks, if present, are implicitly suggestive of a corresponding location of the corresponding auscultatory sound-or-vibration sensor on a thorax of a test subject.
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
B06B 1/08 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with magnetostriction
G01H 11/08 - Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means using piezoelectric devices
B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
An auscultatory sound signal from at least one auscultatory sound-or-vibration sensor is segmented into a plurality of associated heart cycle segments responsive to associated R-peak locations of an electrographic envelope signal representing an envelope response to an even power of an associated electrographic signal from an ECG sensor. A representation an envelope responsive to an even power of said auscultatory sound signal within said at least one heart cycle is locally modeled about at least a second peak to provide for locating the start of diastole of said at least one heart cycle.
An auscultatory sound signal from at least one auscultatory sound-or-vibration sensor is segmented into a plurality of associated heart cycle segments responsive to associated R-peak locations of an electrographic envelope signal representing an envelope response to an even power of an associated electrographic signal from an ECG sensor. A representation an envelope responsive to an even power of said auscultatory sound signal within said at least one heart cycle is locally modeled about at least a second peak to provide for locating the start of diastole of said at least one heart cycle.
An auscultatory sound signal from at least one auscultatory sound-or-vibration sensor is segmented into a plurality of associated heart cycle segments responsive to associated R-peak locations of an electrographic envelope signal representing an envelope response to an even power of an associated electrographic signal from an ECG sensor. A representation an envelope responsive to an even power of said auscultatory sound signal within said at least one heart cycle is locally modeled about at least a second peak to provide for locating the start of diastole of said at least one heart cycle.
An auscultatory sound signal acquired by a recording module is coupled through a high-pass filter having a cut-off frequency in the range of 3 to 15 Hz and subsequently filtered with a low-pass filter, and optionally subject to variable-gain amplification under external control—via a USB or wireless interface—of an associated docking system, responsive to the resulting processed auscultatory sound signal. A sound generator in the docking system generates an associated test signal having an integral number of wavelengths for each of a plurality of frequencies. The test signal is applied to a corresponding auscultatory sound-or-vibration sensor to test the integrity thereof. Resulting sound signals recorded by the recording module are analyzed using a Fourier Transform to determine sensor integrity.
An auscultatory sound signal acquired by a recording module is coupled through a high-pass filter having a cut-off frequency in the range of 3 to 15 Hz and subsequently filtered with a low-pass filter, and optionally subject to variable-gain amplification under external control -- via a USB or wireless interface -- of an associated docking system, responsive to the resulting processed auscultatory sound signal. A sound generator in the docking system generates an associated test signal having an integral number of wavelengths for each of a plurality of frequencies. The test signal is applied to a corresponding auscultatory sound-or-vibration sensor to test the integrity thereof. Resulting sound signals recorded by the recording module are analyzed using a Fourier Transform to determine sensor integrity.
An auscultatory sound signal acquired by a recording module is coupled through a high-pass filter having a cut-off frequency in the range of 3 to 15 Hz and subsequently filtered with a low-pass filter, and optionally subject to variable-gain amplification under external control -- via a USB or wireless interface -- of an associated docking system, responsive to the resulting processed auscultatory sound signal. A sound generator in the docking system generates an associated test signal having an integral number of wavelengths for each of a plurality of frequencies. The test signal is applied to a corresponding auscultatory sound-or-vibration sensor to test the integrity thereof. Resulting sound signals recorded by the recording module are analyzed using a Fourier Transform to determine sensor integrity.
A time-series array of noise data is generated from an inverse frequency transform of the product of the frequency spectrum of an auscultatory sound signal with an associated noise filter generated responsive to a cross-correlation of frequency spectra of auscultatory sound signals from adjacent auscultatory sound-or-vibration sensors on the torso of a test subject. Noise power within at least one range of frequencies of average of frequency spectra from a plurality of windows of the time-series array of noise data is compared with a threshold to determine whether or not the associated auscultatory sound-or-vibration sensor is excessively noisy. In one embodiment, the noise filter is generated by subtracting from unity, a unity-normalized cross-correlation of frequency spectra of the auscultatory sound signals, wherein the resulting values are clipped so as to be no less than an associated noise floor.
An auscultatory sound signal from at least one auscultatory sound-or-vibration sensor is segmented into a plurality of associated heart cycle segments responsive to associated R-peak locations of an electrographic envelope signal representing an envelope response to an even power of an associated electrographic signal from an ECG sensor. An representing an envelope responsive to an even power of said auscultatory sound signal within said at least one heart cycle is locally modeled about at least a second peak to provide for locating the start of diastole of said at least one heart cycle.
A time-series array of noise data is generated from an inverse frequency transform of the product of the frequency spectrum of an auscultatory sound signal with an associated noise filter generated responsive to a cross-correlation of frequency spectra of auscultatory sound signals from adjacent auscultatory sound-or-vibration sensors on the torso of a test subject. Noise power within at least one range of frequencies of average of frequency spectra from a plurality of windows of the time-series array of noise data is compared with a threshold to determine whether or not the associated auscultatory sound-or-vibration sensor is excessively noisy. In one embodiment, the noise filter is generated by subtracting from unity, a unity-normalized cross-correlation of frequency spectra of the auscultatory sound signals, wherein the resulting values are clipped so as to be no less than an associated noise floor.
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
G10L 25/21 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being power information
G10L 25/06 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being correlation coefficients
G10L 21/0364 - Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude for improving intelligibility
19.
METHOD OF DETECTING NOISE IN AUSCULTATORY SOUND SIGNALS OF A CORONARY-ARTERY-DISEASE DETECTION SYSTEM
A time-series array of noise data is generated from an inverse frequency transform of the product of the frequency spectrum of an auscultatory sound signal with an associated noise filter generated responsive to a cross-correlation of frequency spectra of auscultatory sound signals from adjacent auscultatory sound-or-vibration sensors on the torso of a test subject. Noise power within at least one range of frequencies of average of frequency spectra from a plurality of windows of the time-series array of noise data is compared with a threshold to determine whether or not the associated auscultatory sound-or-vibration sensor is excessively noisy. In one embodiment, the noise filter is generated by subtracting from unity, a unity-normalized cross-correlation of frequency spectra of the auscultatory sound signals, wherein the resulting values are clipped so as to be no less than an associated noise floor.
An auscultatory sound signal from at least one auscultatory sound-or-vibration sensor is segmented into a plurality of associated heart cycle segments responsive to associated R-peak locations of an electrographic envelope signal representing an envelope response to an even power of an associated electrographic signal from an ECG sensor. An representing an envelope responsive to an even power of said auscultatory sound signal within said at least one heart cycle is locally modeled about at least a second peak to provide for locating the start of diastole of said at least one heart cycle.
A metallic diaphragm disk (22, 266, 266', 266'') incorporating a piezoelectric material (24, 24', 24.1, 24.2, 24', 24'') bonded thereto and operatively coupled to a base rim (14, 62, 262) of a housing (18, 18', 66, 256) provides for closing an open-ended cavity (20, 20', 270) at the first end (18.1, 18.1') of the housing (18, 18', 66, 256). In one aspect (10', 10'', 10''a, 10''b, 10'''), plastic film (46) adhesively bonded (48, 52) to at least one of an outer rim (47) of the housing (18, 18', 66) or an outer-facing surface (22.2) of the disk (22) provides for receiving an adhesive acoustic interface material (55, 56) to provide for coupling the sound-or-vibration sensor (10', 10'', 10''a, 10''b, 10''') to the skin (36) of a test subject (34). In another aspect (10'''', 10a'''', 10b'''', 10c''''), an outer-facing surface (258.1) of a base portion (258) of the housing (256) provides for receiving an adhesive acoustic interface material (55, 56) to provide for coupling the housing (256) to the skin (36) of a test subject (34), at least one inertial mass (272.1, 272.2) is operatively coupled to a central portion (26, 26.1, 26.2) of the metallic diaphragm disk (266, 266', 266''), and the opening in the first end of the housing (256) is closed with a cover (280).
A metallic diaphragm disk (22, 266, 266', 266'') incorporating a piezoelectric material (24, 24', 24.1, 24.2, 24', 24'') bonded thereto and operatively coupled to a base rim (14, 62, 262) of a housing (18, 18', 66, 256) provides for closing an open-ended cavity (20, 20', 270) at the first end (18.1, 18.1') of the housing (18, 18', 66, 256). In one aspect (10', 10'', 10''a, 10''b, 10'''), plastic film (46) adhesively bonded (48, 52) to at least one of an outer rim (47) of the housing (18, 18', 66) or an outer-facing surface (22.2) of the disk (22) provides for receiving an adhesive acoustic interface material (55, 56) to provide for coupling the sound-or-vibration sensor (10', 10'', 10''a, 10''b, 10''') to the skin (36) of a test subject (34). In another aspect (10'''', 10a'''', 10b'''', 10c''''), an outer-facing surface (258.1) of a base portion (258) of the housing (256) provides for receiving an adhesive acoustic interface material (55, 56) to provide for coupling the housing (256) to the skin (36) of a test subject (34), at least one inertial mass (272.1, 272.2) is operatively coupled to a central portion (26, 26.1, 26.2) of the metallic diaphragm disk (266, 266', 266''), and the opening in the first end of the housing (256) is closed with a cover (280).
A metallic diaphragm disk incorporating a piezoelectric material bonded thereto and operatively coupled to a base rim of a housing provides for closing an open-ended cavity at the first end of the housing. In one aspect, plastic film adhesively bonded to at least one of an outer rim of the housing or an outer-facing surface of the disk provides for receiving an adhesive acoustic interface material to provide for coupling the housing to the skin of a test subject. In another aspect, an outer-facing surface of a base portion of the housing provides for receiving an adhesive acoustic interface material to provide for coupling the housing to the skin of a test subject, at least one inertial mass is operatively coupled to a central portion of the metallic diaphragm disk, and the opening in the first end of the housing is closed with a cover.
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
B06B 1/08 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with magnetostriction
G01H 11/08 - Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means using piezoelectric devices
B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
MAXMINMIN), and is used to determine whether or not the auscultatory-sound sensor (12) is either debonded or detached from the skin (38) of the test-subject (22).
At least one of at least one data-dependent scale factor (SF) or at least one data-dependent detection threshold (DTi) is determined responsive to at least one block of time-series data (S) of an auscultatory-sound signal (16, 16.1, 16.1', 16.1'') generated by an auscultatory-sound sensor (12) operatively coupled to a portion of the skin (38) of a test-subject (22), wherein the at least one data-dependent scale factor (SF) or at least one data-dependent detection threshold (DTi) provides a measure of a range of values of the at least one block of time-series data (S) in relation to a predetermined metric (SFMAX, DT, DTMIN), and is used to determine whether or not the auscultatory-sound sensor (12) is either debonded or detached from the skin (38) of the test-subject (22).
At least one of at least one data-dependent scale factor or at least one data-dependent detection threshold is determined responsive to at least one block of time-series data of an auscultatory-sound signal generated by an auscultatory-sound sensor operatively coupled to a portion of the skin of a test-subject, wherein the at least one data-dependent scale factor or at least one data-dependent detection threshold provides a measure of a range of values of the at least one block of time-series data in relation to a predetermined metric, and is used to determine whether or not the auscultatory-sound sensor is either debonded or detached from the skin of the test-subject.
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
G06F 16/68 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
H04B 1/38 - Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
Goods & Services
Software used to acquire and analyze cardiac acoustic data and provide results. Medical devices used to acquire and analyze cardiac acoustic data and provide results.
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
Goods & Services
Software used to acquire and analyze cardiac acoustic data and provide results. Medical devices used to acquire and analyze cardiac acoustic data and provide results.
32.
Auscul Sciences Sound Hearts Through Sound Technology
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
Goods & Services
Software used to acquire and analyze cardiac acoustic data and provide results. Medical devices used to acquire and analyze cardiac acoustic data and provide results.
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
Goods & Services
(1) Computer software for medical devices used to acquire and analyze cardiac acoustic data and provide results.
(2) Medical devices used to acquire and analyze cardiac data and provide results.
34.
AUSCULSCIENCES SOUND HEARTS THROUGH SOUND TECHNOLOGY
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
Goods & Services
(1) Software used to acquire and analyze cardiac acoustic data and provide results
(2) Medical devices used to acquire and analyze cardiac acoustic data and provide results
A method and system for modeling cardiovascular disease using a probability regression model is provided. A parameter estimate of a probability regression model for cardiovascular disease can be generated using predictors derived from cardiovascular sound signals and disease status information. A probability of cardiovascular disease can be generated using a probability regression model that includes a predictor derived from cardiovascular sound signals.
