WO2019079786A1 - Procédé de détection de bruit dans des signaux sonores d'auscultation d'un système de détection de maladie artérielle coronaire - Google Patents

Procédé de détection de bruit dans des signaux sonores d'auscultation d'un système de détection de maladie artérielle coronaire Download PDF

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Publication number
WO2019079786A1
WO2019079786A1 PCT/US2018/056840 US2018056840W WO2019079786A1 WO 2019079786 A1 WO2019079786 A1 WO 2019079786A1 US 2018056840 W US2018056840 W US 2018056840W WO 2019079786 A1 WO2019079786 A1 WO 2019079786A1
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Prior art keywords
auscultatory sound
noise
data
auscultatory
vibration sensor
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PCT/US2018/056840
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English (en)
Inventor
Brady LASKA
Md Shahidul Islam
Jikang ZENG
Jun Zhou
Daniel LABONTÉ
Simon Martin
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Ausculsciences, Inc.
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Priority to CA3079674A priority Critical patent/CA3079674A1/fr
Publication of WO2019079786A1 publication Critical patent/WO2019079786A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/02—Stethoscopes
    • A61B7/04—Electric stethoscopes

Definitions

  • FIG. 1 illustrates a block diagram of a coronary-artery-disease detection system
  • FIG. 2 illustrates a first aspect of a data recording module and a first aspect of an associated docking system, in accordance with a first aspect of the coronary-artery-disease detection system illustrated in FIG. 1;
  • FIG. 3 illustrates a fragmentary view of a human thorax and associated prospective locations of auscultatory sound sensors associated right, sternum and left, second, third, fourth and fifth, inter-costal spaces, left posterior locations at the second and third inter-costal spaces, and locations proximate to the heart apex;
  • FIG. 4 illustrates a second aspect of a data recording module and a second aspect of an associated docking system, in accordance with a second aspect of the coronary-artery- disease detection system illustrated in FIG. 1;
  • FIG. 5a illustrates an auscultatory sound sensor coupled to the skin of a test-subject, by bonding via associated adhesive layers or surfaces on both sides of an adhesive interface;
  • FIGS. 5b and 5c each illustrate an auscultatory sound sensor that is detached, and therefore fully decoupled, from the skin of a test-subject, wherein FIG. 5b illustrates the associated adhesive interface detached from the skin of the test-subject, and FIG. 5c illustrates the associated adhesive interface detached from the auscultatory sound sensor;
  • FIGS. 5d through 5g each illustrate an auscultatory sound sensor that is partially coupled to, but debonded from, the skin of a test-subject;
  • FIG. 6 illustrates a test-subject reclined on a surface, with their torso inclined while capturing auscultatory sound signals from a plurality of auscultatory sound sensors attached to the thorax of the test-subject;
  • FIG. 7 illustrates a flowchart of a first aspect of an associated auscultatory-sound- sensing process that incorporates a process for detecting a decoupling of the associated auscultatory sound sensors from the skin of the thorax of a test-subject being diagnosed for a prospective abnormal cardiovascular condition, wherein the decoupling-detection process occurs after each block of breath-held auscultatory sound time-series data is acquired, and is based upon scaled time-series data and responsive to an associated pre-determined debond- detection threshold;
  • FIG. 8 illustrates a flowchart of a first aspect of a process for acquiring auscultatory sound signals from the associated auscultatory sound sensors coupled to the skin of the thorax of the test-subject being diagnosed for a prospective abnormal cardiovascular condition;
  • FIG. 9 illustrates a plurality of six blocks of breath-held, auscultatory-sound-sensor time-series data recorded from an auscultatory sound sensor coupled to the skin of the thorax of a test-subject being diagnosed for a prospective abnormal cardiovascular condition;
  • FIGS. 10a- lOf respectively illustrate a simulation of successively recorded blocks of breath-held, sensor time-series data illustrated in FIG. 9, each illustrated with an expanded time scale, wherein FIGS. lOa-lOe illustrates a condition for which the auscultatory sound sensor is coupled to the skin of the test-subject, and FIG. lOf illustrates a condition for which the auscultatory sound sensor is decoupled from the skin of the test-subject;
  • FIG. 11 illustrates a flowchart of a process for determining a scale factor used to scale auscultatory-sound-sensor time-series data, the latter of which is analyzed to detect whether or not the associated auscultatory sound sensor is decoupled from the skin of the test-subject, wherein the scale factor provides for directly determining if the associated auscultatory sound sensor is detached from the skin of the test-subject;
  • FIGS. 12a-12f respectively illustrate time-series of the absolute values of the corresponding time-series data illustrated in FIGS. 10a- lOf, further illustrating a division of the block of breath-held, sensor time-series data into a plurality of associated data segments, with each data segment of sufficient width to nominally include sound from a single heartbeat, and with the peak values in each data segment marked, wherein FIGS. 12a-12e illustrates a condition for which the auscultatory sound sensor is coupled to the skin of the test-subject, and FIG. 12f illustrates a condition for which the auscultatory sound sensor is decoupled from the skin of the test-subject;
  • FIG. 13 illustrates an accelerometer on the thorax of a test-subject during a respiration cycle of the test-subject
  • FIG. 14 illustrates a breath-hold detection process
  • FIG. 15 illustrates a flowchart of a first aspect of a process for detecting whether or not an auscultatory sound sensor is debonded from the skin of a test-subject
  • FIG. 16 illustrates an organization of data from an auscultatory sound sensor recorded by an auscultatory coronary-artery-disease detection system from a test subject
  • FIG. 17 illustrates a flowchart of a noise detection process
  • FIG. 18 illustrates a flowchart of a process for generating a matched noise filter
  • FIG. 19 illustrates a flowchart of a process for evaluating the noise content in a spectral signal of an auscultatory sound signal
  • FIG. 20 illustrates a flowchart of a process for logging results from the noise- evaluation process of FIG. 19.
  • an auscultatory coronary-artery-disease detection system 10 incorporates at least one auscultatory sound sensor 12 that is operatively coupled to a recording module 13 running at least a first portion 14.1 of a Data Recording Application (DRA) 14, 14.1 on a first specialized computer or electronic system comprising a first computer processor or FPGA (Field Programmable Gate Array) 15 and first memory 17 powered by a first power supply 19, which provides for recording and preprocessing auscultatory sound signals 16 from the at least one auscultatory sound sensor 12.
  • DRA Data Recording Application
  • the at least one auscultatory sound sensor 12 comprises a first group 12' of three auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' physically interconnected end-to-end with one another, and physically and electrically interconnected with a first wireless transceiver 18; and a second group 12" of three auscultatory sound sensors 12, 12 1 ", 12 2 “, 12 3 " physically interconnected end-to-end with one another, and physically and electrically interconnected with the first wireless transceiver 18, with both groups 12% 12" of auscultatory sound sensors placed on the skin of the thorax 20 of a test-subject 22, in acoustic communication therewith.
  • the placement of the first group of auscultatory sound sensors 12' in FIG. 1 is illustrated with the respective associated auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' in substantial alignment with the corresponding respective third R3, fourth R4 and fifth R5, inter-costal spaces on the right side 20 R of the thorax 20, and the placement of the second group of auscultatory sound sensors 12" in FIG. 1 is illustrated with the respective associated auscultatory sound sensors 12, 12 1 ", 12 2 ", 12 3 " in substantial alignment with the corresponding respective third L3, fourth L4 and fifth L5, inter-costal spaces on the left side 20 L of the thorax 20.
  • prospective left-side posterior sensor locations LP2 and LP3 illustrated in FIG. 3 respectively refer to at the second LP2 and third LP3 intercostal spaces locations on the posterior of the thorax 20.
  • prospective sensor locations HA-1 and HA-2 are proximate to the apex of the heart, either on the anterior or the posterior of the thorax 20.
  • the auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ", 12 1 ", 12 2 “, 12 3 " are located at the second S2, L2, third S3, L3 and fourth S4, L4 inter-costal spaces at the sternum S2-S4 and leftside L2-L4 of the thorax 20.
  • the term "auscultatory sound” is intended to mean a sound originating from inside a human or animal organism as a result of the biological functioning thereof, for example, as might be generated by action of the heart, lungs, other organs, or the associated vascular system; and is not intended to be limited to a particular range of frequencies ⁇ for example, not limited to a range of frequencies or sound intensities that would be audible to a human ear, ⁇ but could include frequencies above, below, and in the audible range, and sound intensities that are too faint to be audible to a human ear.
  • the term “auscultatory-sound sensor” is intended to mean a sound sensor that provides for transducing auscultatory sounds into a corresponding electrical or optical signal that can be subsequently processed.
  • the auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " provide for transducing the associated sounds received thereby into corresponding auscultatory sound signals 16 that are preprocessed and recorded by an associated hardware-based signal conditioning/preprocessing and recording subsystem 25, then communicated to the first wireless transceiver 18, and then wirelessly transmitted thereby to an associated second wireless transceiver 26 of an associated wireless interface 26' of an associated docking system 27, possibly running a second portion 14.2 of the Data Recording Application (DRA) 14, 14.2 on a corresponding second specialized computer or electronic system comprising an associated second computer processor or FPGA (Field Programmable Gate Array) 28 and second memory 30, both of which are powered by an associated second power supply 32, which together provide for recording and preprocessing the associated auscultatory sound signals 16 from the auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 "
  • the hardware-based signal conditioning/preprocessing and recording subsystem 25 includes an amplifier ⁇ either of fixed or programmable gain, ⁇ a filter and an analog-to-digital converter (ADC).
  • the analog-to-digital converter (ADC) is a 16-bit analog-to-digital converter (ADC) that converts a -2.25 to +2.25 volt input to a corresponding digital value of - 32, 768 to + 32, 767.
  • the amplifier gain is programmable to one of sixteen different levels respectively identified as levels 0 to 15, with corresponding, respective gain values of 88, 249, 411, 571, 733, 894, 1055, 1216, 1382, 1543, 1705, 1865, 2027, 2188, 2350 and 2510, respectively for one set of embodiments.
  • the amplifier gain is fixed at the lowest above value, i.e., for this example, 88, so as to provide for avoiding the relative degradation of the associated signal-to-noise ratio (SNR) that naturally occurs with the relatively high gain levels of the programmable-gain set of embodiments.
  • SNR signal-to-noise ratio
  • DRA Data Recording Application
  • either or both the recording module 13 or docking system 27 may be constructed and operated in accordance with the disclosure of U.S. Provisional Application No. 62/575,364 filed on 20 October 2017, entitled CORONARY ARTERY DISEASE DETECTION SYSTEM, which is incorporated by reference in its entirety.
  • the auscultatory coronary-artery-disease detection system 10 may further incorporate an ECG sensor 34, for example, in one set of embodiments, an ECG sensor 34' comprising a pair of electrodes incorporated in a corresponding pair of auscultatory sound sensors 12, wherein the signal from the ECG sensor 34' is also preprocessed and recorded by a different signal channel of the same hardware-based signal conditioning/preprocessing and recording subsystem 25 of the recording module 13 that is used to preprocess the signals from the one or more auscultatory sound sensors 12.
  • an ECG sensor 34 for example, in one set of embodiments, an ECG sensor 34' comprising a pair of electrodes incorporated in a corresponding pair of auscultatory sound sensors 12, wherein the signal from the ECG sensor 34' is also preprocessed and recorded by a different signal channel of the same hardware-based signal conditioning/preprocessing and recording subsystem 25 of the recording module 13 that is used to preprocess the signals from the one or more auscultatory sound sensors 12.
  • the ECG sensor 34 may comprise a separate set of a pair or plurality of electrodes that are coupled to the skin of the test subject, for example, in one set of embodiments, a pair of signal electrodes 35, 35 + ⁇ in cooperation with a ground electrode 35°, wherein, referring to FIG. 3 (illustrating the locations of the electrodes 35, 35 + " , 35°), the signal electrodes 35, 35 + " span the heart from diametrically-opposed quadrants of the torso 44, and the ground electrode 35° is located in a different quadrant, orthogonally displaced from a midpoint of a baseline connecting the signal electrodes 35, 35 + " .
  • the recording module 13 and docking system 27 may each incorporate a corresponding respective USB interface 36.1, 36.2 to provide for transferring corresponding auscultatory sound signals 16 and or an ECG signal 37 from the recording module 13 to the docking system 27, for example, rather than relying upon the first 18 and second 26 wireless transceivers of an associated wireless interface 26'.
  • data may be transferred from the recording module 13 to the docking system 27 via a portable memory element, for example, either an SD memory card or a Micro SD memory card.
  • the functionality of the Data Recording Application (DRA) 14 is distributed across the recording module 13 and the docking system 27.
  • the Data Recording Application (DRA) 14 spans across the recording module 13 and the docking system 27, with a first portion 14.1 comprising the hardware- based signal conditioning/preprocessing and recording subsystem 25 operative on the recording module 13, and a remaining second portion 14.2 operative on the docking system 27.
  • the Data Recording Application (DRA) 14 is operative entirely on the recording module 13
  • the auscultatory sound sensor 12 provides for sensing sound signals that emanate from within the thorax 20 of the test-subject 22 responsive to the operation of the test- subject's heart, and the resulting flow of blood through the arteries and veins, wherein an associated build-up of deposits therewithin can cause turbulence in the associated blood flow that can generate associated cardiovascular-condition-specific sounds, the latter of which can be detected by a sufficiently-sensitive auscultatory sound sensor 12 that is acoustically coupled to the skin 38 of the thorax 20 of the test-subject 22.
  • the sound level of these cardiovascular-condition-specific sounds can be below a level that would be detectable by a human using a conventional stethoscope.
  • these sound levels are susceptible to detection by sufficiently sensitive auscultatory sound sensor 12 that is sufficiently acoustically coupled to the skin 38 of the thorax 20 of the test-subject 22.
  • the auscultatory sound sensor 12 may be constructed in accordance with the teachings of U.S. Provisional Application No. 62/568,155 filed on 04 October 2017, entitled AUSCULTATORY SOUND SENSOR.
  • the auscultatory sound sensor 12 may be constructed in accordance with the teachings of U.S. Pat. Nos. 6,050,950, 6,053,872 or 6,179,783, which are incorporated herein by reference. Referring also to FIG.
  • the auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " are acoustically coupled to the skin 38 of the thorax 20 of the test-subject 22 via an acoustic interface 40, for example, via a hydrogel layer 40', that also functions as an associated adhesive interface 42that is attached to the associated auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " with a first adhesive layer 42.1, for example, either a first surface 40.1' of the hydrogel layer 40' or a first layer of double-sided tape 42.1' on a first side of the acoustic/adhesive interface 40, 42, and that is attached to the skin 38 of the thorax 20 of the test-subject 22 with a second adhesive layer 42.2, for example, either a second surface 40.2' of the hydrogel layer 40' or a second layer of double-
  • the auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " is fully attached to the acoustic/adhesive interface 40, 42 via the first adhesive layer 42.1, 42.1', 40.1', and the acoustic/adhesive interface 40, 42 is fully attached to the skin 38 of the thorax 20 of the test-subject 22 via the second adhesive layer 42.2, 42.2', 40.2', so that sound signals from within the thorax 20 of the test-subject 22 can propagate otherwise unimpeded to the auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 ", thereby providing for a maximum achievable level of the corresponding associated auscultatory sound signals 16, and thereby improving the prospect of detecting an associated abnormal cardiovascular condition - if present - therefrom.
  • the auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " is partially attached to the skin 38 of the thorax 20 of the test-subject 22, and thereby partially decoupled therefrom - i.e., in a condition referred to herein as being debonded therefrom ⁇ the resulting auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " would be only partially responsive to sound signals from within the thorax 20 of the test-subject 22, but not sufficiently responsive to provide for an associated auscultatory sound signal 16 of sufficient amplitude to provide for reliably detecting a prospective associated abnormal cardiovascular condition.
  • FIGS. 5d and 5e respectively illustrate an acoustic/adhesive interface 40, 42 partially detached from skin 38, and an acoustic/adhesive interface 40, 42 partially detached from an auscultatory sound sensor 12, respectively.
  • FIG. 5f illustrates an auscultatory sound sensor 12 attached to a wrinkled acoustic/adhesive interface 40, 42
  • FIG. 5g illustrates an acoustic/adhesive interface 40, 42 attached to wrinkled skin 38.
  • the Data Recording Application (DRA) 14 is provided with a means - described more fully hereinbelow ⁇ for detecting if one or more auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " is, or are, either detached or debonded from the skin 38 of the thorax 20 of the test-subject 22, so as to provide for excluding data from auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " that are either detached or debonded, from the skin 38 of the thorax 20 of the test-subject 22 from being used to diagnose a prospective abnormal cardiovascular condition.
  • the adhesive interface 42 could comprise either a hydrogel layer 40', for example, P-DERM® Hydrogel; a silicone material, for example, a P-DERM® Silicone Gel Adhesive; an acrylic material, for example, a P-DERM® Acrylic Adhesive; a rubber material; a synthetic rubber material; a hydrocolloid material; or a double-sided tape, for example, with either rubber, acrylic or silicone adhesives.
  • the quality of the auscultatory sounds acquired from a test-subject 34 can be improved if the torso 44 of the test-subject 34 is inclined, for example, in one set of embodiments, at an inclination angle ⁇ of about 30 degrees above horizontal ⁇ but generally, as close to upright (i.e.
  • ⁇ 90 degrees) as can be accommodated by the associated adhesive interface(s) 42 of the associated auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " ⁇ which imposes a transverse component of gravitational force on each of the auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " that is resisted by the associated adhesive interface(s) 42.
  • an auscultate ry- sound-sensing process 700 provides for first determining a scale factor SF from an initially- acquired block of auscultatory-sound-sensor time-series data S, and initially determining from the scale factor SF whether one or more of the auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " is detached from the skin 38 of the thorax 20 of the test-subject 22, wherein when multiplied by the scale factor SF, the values of the associated auscultatory-sound-sensor time-series data S are nominally within a range that is a predetermined percentage of the dynamic range of the associated data acquisition system (for example, that provides 76-bit signed digital values).
  • the auscultatory-sound-sensing process 700 provides for acquiring successive blocks of auscultatory-sound-sensor time-series data S while the test-subject 22 is holding their breath, and determining from each block of auscultatory-sound-sensor time-series data S - using an associated predetermined debond-detection threshold - whether or not one or more auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " is debonded from the skin 38 of the thorax 20 of the test-subject 22, or whether there is excessive noise in the auscultatory-sound-sensor time-series data S.
  • the auscultatory-sensor time-series data S is rejected if excessive noise is detected, and the test is aborted if one or more auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " has become decoupled from the skin 38 of the thorax 20.
  • the first aspect 700 of the auscultatory- sound-sensing process 700 commences with step (702) by initializing a data-block counter I to a value of zero, and then, in step (704), acquiring a block of Ns contiguous samples of auscultatory-sound-sensor time-series data S in accordance with a first aspect 800 of a data acquisition process 800.
  • This initially-acquired data is then used to determine a scale factor SF that is used to determine whether or not one or more auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " is/are detached from the skin 38 of the thorax 20 of the test-subject 22, and then subsequently to scale subsequent blocks of time-series data S.
  • the initial block of auscultatory-sound-sensor time-series data S may be acquired either with, or without, the test-subject 22 holding their breath, but typically with the test-subject 22 allowed to breath normally ⁇ for their comfort and convenience.
  • the number of samples Ns to be acquired is given by the product of an acquisition period Si in seconds, times a sampling frequency Fs in Hz.
  • the data acquisition process 800 commences with step (802) by pre-filtering the electronic signal from the associated auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " with an analog anti-aliasing filter, for example, an analog second-order band-pass filter having a pass band in the range of 20 Hz to 1 KHz, for which the upper-cutoff frequency is sufficiently below the sampling frequency (i.e. no more than half) so as to prevent high frequency components in the signal being sampled from appearing as low frequency components of the sampled signal.
  • an analog anti-aliasing filter for example, an analog second-order band-pass filter having a pass band in the range of 20 Hz to 1 KHz, for which the upper-cutoff frequency is sufficiently below the sampling frequency (i.e. no more than half) so as to prevent high frequency components in the signal being sampled from appearing as low frequency components of the sampled signal.
  • step (804) the test-subject 22 need not necessarily hold their breath - as is the case for the initially-acquired block of auscultatory-sound-sensor time-series data S, ⁇ then, in step (806), the pre-filtered auscultatory sound signal 16 is sampled at the sampling frequency Fs and converted to digital form by the associated analog-to-digital (ADC) converter.
  • ADC analog-to-digital
  • step (808) the auscultatory sound signal 16 continues to be sampled in step (806) until Ns samples of the block of auscultatory-sound-sensor time-series data S have been acquired, after which, in step (810), the Ns samples of auscultatory-sound-sensor time- series data S are retumed to step (704) of the auscultatory-sound-sensing process 700.
  • FIGS. 9 and 10a each illustrate a first block of auscultatory-sound-sensor time- series data S of duration ⁇ that was recorded from one of the auscultatory sound sensors
  • the scale factor SF is determined from the initially-acquired block of auscultatory-sound-sensor time-series data S, in accordance with an associated scale-factor-determination process 1100. More particularly, referring to FIGS. 11 and 12a, the scale-factor-determination process 1100 commences with step (1102), wherein the block of auscultatory-sound-sensor time-series data S is divided into a plurality of data segments 46, for example, each of the same data- segment duration SD that nominally spans a single heartbeat, for example, about one second. For example, in Fig.
  • FIG. 12a illustrates a time series
  • step (1106) the scale factor SF is determined, as given by:
  • DRo-p is the nominal zero-to-peak dynamic range of the auscultatory-sound-sensor time-series data S after scaling, i.e. after multiplying the acquired values by the scale factor
  • the nominal zero-to-peak dynamic range is set to be about 80 percent - more broadly, but not limiting, 80 percent plus or minus 15 percent - - of the zero-to-peak range of the associated analog-to-digital converter ⁇ for example, in one set of embodiments, a 16-bit signed analog-to-digital converter ⁇ used to digitize the auscultatory-sound-sensor time-series data S in step (806).
  • the scale factor SF is integer-valued that, for an attached and bonded auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 ", ranges in value between 1 and 28.
  • the associated level of the auscultatory sound signals 16 will be low - for example, at a noise level - resulting in a relatively large associated scale factor SF from step (1106).
  • step (1108) the scale factor SF is in excess of an associated threshold SFMAX
  • the Data Recording Application (DRA) 14 is aborted in step (1110), and the operator 48 is alerted that the one or more auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " is/are detached, so that this can be remedied.
  • the value of the threshold SFMAX is 28 for the above-described fixed-gain embodiment, i.e.
  • step (1108) if the value of the scale factor SF does not exceed the associated threshold SFMAX, in step (1112), the scale factor SF is returned to step (706) for use in scaling subsequently-recorded breath-held auscultatory sound signals 16.1.
  • ADC analog-to-digital converter
  • step (708) the value of the data- block counter i is incremented, so as to point to the next block of auscultatory-sound- sensor time-series data S to be recorded. If, while this next block is recorded, the auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " remain attached and bonded to the skin 38 of the thorax 20 of the test-subject 22, and the associated breath-held auscultatory sound signals 16.1 are not corrupted by excessive noise, then this next block of auscultatory-sound-sensor time-series data S will then be subsequently used to detect a prospective abnormal cardiovascular condition therefrom.
  • the auscultatory sound signals 16 used to detect prospective abnormal cardiovascular conditions are recorded while the test- subject 22 holds their breath, the latter to prevent the resulting cardiovascular-based auscultatory sound signals 16 from being overwhelmed by breathing-related sounds that are substantially louder than cardiovascular-based sounds, thereby providing for improving the associated signal-to-noise ratio of the cardiovascular-based auscultatory sound signals 16.
  • a next block of Ns contiguous samples of auscultatory- sound-sensor time-series data S is acquired over an acquisition period Si in accordance with a first aspect 800 of a data acquisition process 800, during which time the test-subject 22 is instructed to hold their breath.
  • the data acquisition process 800 commences with step (802) by pre-filtering the electronic signal from the associated auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 , 12 1 ", 12 2 ", 12 3 " with the above-described analog anti-aliasing filter. Then, from step (804), because breath-held data is to be acquired, in step (812), the test-subject 22 is instructed by the operator 48 to hold their breath.
  • ADC analog-to-digital
  • step (820) if one or more addition samples remain to be acquired, and if the operator 48 continues to observe that the test-subject 22 is holding their breath, or, additionally or alternatively, if this is confirmed by a below-described breath-hold detection process 1400, then, in step (822) the sample counter j is incremented, and the next sample is acquired in step (818).
  • the pre-filtered auscultatory sound signals 16 are also separately-recorded while waiting for the test-subject 22 to hold their breath, or resume doing so.
  • the auscultatory sound signals 16 typically continue to be recorded between breath-held segments, that latter of which are identified by associated recorded start and stop times with respect to the associated continuous recording.
  • the auscultatory coronary-artery-disease detection system 10 may further incorporate an accelerometer 50 operatively coupled to the thorax 20 of the test-subject 22 to provide an associated acceleration signal responsive to the motion of the thorax 20.
  • an accelerometer 50 operatively coupled to the thorax 20 of the test-subject 22 to provide an associated acceleration signal responsive to the motion of the thorax 20.
  • the associated acceleration signal - operatively coupled to recording module 13 and possibly transmitted to the docking system 27— may be twice integrated either in recording module 13 or the docking system 27 to generate a measure of the peak-to-peak displacement of the thorax 20, which if greater than a threshold would be indicative of breathing by the test-subject 22.
  • an acceleration signal 52 therefrom may alternatively or additionally be processed by an associated breath-hold detection process 1400 to provide for automatically determining - for example, in step (814) of the data acquisition process 800 illustrated in FIG. 8 - whether or not the test-subject 22 is breathing, responsive to the determination, from the acceleration signal 52, of a peak-to-peak displacement of the thorax 20 of the test-subject 22.
  • the respective previous/initial values of thorax displacement Yo and thorax velocity Vo are each initialized to values of zero; a sample counter i is initialized to an initial value, for example, zero; the respective minimum YMIN and maximum YMAX values of thorax displacement are each set equal to the (initial) value of thorax displacement Yo; the values of the sample counter IMIN and IMAX at which the corresponding minimum YMIN and maximum YMAX values of thorax displacement occur are set equal to the initial value of the sample counter i; and a BreathingFlag is set to indicate that the test-subject 22 is breathing.
  • step (1404) the current sample of thorax acceleration A is acquired.
  • step (1412) the current value of thorax velocity F is calculated by integrating the previous Ao and current A measurements of thorax acceleration, for example, using a trapezoidal rule, as follows: V ⁇ dt + V n (4)
  • step (1414) the current value of thorax displacement Y is calculated by integrating the above-calculated previous Vo and current V values of thorax velocity, for example, again using a trapezoidal rule, as follows:
  • step (1416) the respective previous values of thorax acceleration Ao, thorax displacement Yo and thorax velocity Vo are respectively set equal to the corresponding current values of thorax acceleration A, thorax velocity V and thorax displacement Y, respectively, that will each be used in subsequent iterations of steps (1412) and (1414).
  • step (1418) if the current value of thorax displacement F is greater than then current maximum value of thorax displacement FMAX - for example, as would result during a phase of chest expansion by the test-subject 22, ⁇ then, in step (1420), the current maximum value of thorax displacement YMAX is set equal to the current value of thorax displacement Y and the corresponding value of the sample counter IMAX associated therewith is set to the current value of the sample counter i.
  • step (1422) if, in step (1422), the amount by which the current value of the sample counter i exceeds the value of the sample counter IMAX associated with the maximum value of thorax displacement YMAX is not equal to a threshold value A (the relevance of which is described more fully hereinbelow), then in step (1424), if the current value of thorax displacement Y is less than then current minimum value of thorax displacement YMIN - for example, as would result during a phase of chest contraction by the test-subject 22, ⁇ then, in step (1426), the current minimum value of thorax displacement YMIN is set equal to the current value of thorax displacement Y and the corresponding value of the sample counter IMIN associated therewith is set to the current value of the sample counter i.
  • a threshold value A the relevance of which is described more fully hereinbelow
  • step (1428) if the amount by which the current maximum value of thorax displacement YMAX is greater the current minimum value of thorax displacement YMIN meets or exceeds a displacement threshold ⁇ , then, in step (1430), the BreathingFlag is set to indicate that the test-subject 22 is breathing, after which, in step (1410), the sample counter i is incremented, after which the breath-hold detection process 1400 repeats with step (1404). Similarly, from step (1428), if the displacement threshold ⁇ is not exceeded, in step (1410), the sample counter i is incremented, after which the breath-hold detection process 1400 repeats with step (1404).
  • step (1432) the amount by which the current value of the sample counter i exceeds the value of the sample counter IMIN associated with the minimum value of thorax displacement YMIN is not equal to the threshold value A, in step (1410), the sample counter i is incremented, after which the breath-hold detection process 1400 repeats with step (1404).
  • step (1432) If, from step (1432), the amount by which the current value of the sample counter i exceeds the value of the sample counter IMIN associated with the minimum value of thorax displacement YMIN is equal to the threshold value A — following a minimum chest contraction of the test-subject 22, in anticipation of subsequent chest expansion, wherein the threshold value A is greater than or equal to one, ⁇ then, in step (1434), the peak-to-peak thorax displacement AY is calculated as the difference between the current maximum YMAX and minimum YMIN values of thorax displacement, and, in step (1436), the maximum value of thorax displacement YMAX is set equal to the current value of thorax displacement Y, and the value of the sample counter IMAX at which the corresponding maximum value of thorax displacement YMAX occurred is set equal to the current value of the sample counter i, in anticipation of subsequently increasing magnitudes of the current value of thorax displacement Fto be tracked in steps (1418) and (1420).
  • step (1422) the amount by which the current value of the sample counter i exceeds the value of the sample counter IMAX associated with the maximum value of thorax displacement YMAX is equal to the threshold value A -- following a maximum chest expansion of the test-subject 22, in anticipation of subsequent chest contraction, wherein the threshold value A is greater than or equal to one, ⁇ then, in step (1438), the peak-to-peak thorax displacement AY is calculated as the difference between the current maximum YMAX and minimum YMIN values of thorax displacement, and, in step (1440), the minimum value of thorax displacement YMIN is set equal to the current value of thorax displacement Y, and the value of the sample counter IMIN at which the corresponding minimum value of thorax displacement YMIN occurred is set equal to the current value of the sample counter i, in anticipation of subsequently decreasing magnitudes of the current value of thorax displacement Fto be tracked in steps (1424) and (1426).
  • step (1442) if the amount of the peak-to-peak thorax displacement AY calculated in steps (1434) or (1438), respectively, meets or exceeds the displacement threshold ⁇ , then, in step (1444), the BreathingFlag is set to indicate that the test-subject 22 is breathing. Otherwise, from step (1442), if the amount of the peak- to-peak thorax displacement AY calculated in steps (1434) or (1438), respectively, does not exceed the displacement threshold ⁇ , then, in step (1446), the BreathingFlag is reset to indicate that the test-subject 22 is not breathing. Following either step (1444) or (1446), in step (1410), the sample counter i is incremented, after which the breath-hold detection process 1400 repeats with step (1404).
  • a corresponding block of scaled auscultatory-sound-sensor time-series data S is calculated by multiplying the acquired block of auscultatory-sound-sensor time-series data S by the scale factor SF, and in step (714), the scaled auscultatory-sound-sensor time-series data S is analyzed by an associated debond detection process 1500 to determine whether or not any of the auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " was debonded from skin 38 of the thorax 20 of the test-subject 22 during the associated data acquisition process 800.
  • the debond detection process 1500 commences with step (1502) by initializing a sample counter j to a value of one, and initializing a threshold counter TC to a value of zero, wherein the threshold counter TC is a count of the number of contiguous successive samples for which the value of the scaled auscultatory-sound-sensor time-series data S is less than an associated predetermined debond-detection threshold DT.
  • the debond- detection threshold DT is set to a value that is about 20% of the achievable maximum value of the output from the analog-to-digital converter (ADC).
  • step (1504) if the absolute value of the sample of scaled auscultatory-sound-sensor time-series data S, i.e.
  • step (1510) if the sample counter j does not exceed the number of samples Ns in the block of scaled auscultatory-sound-sensor time-series data S, then, in step (1512), the sample counter j is incremented, and the process continues again with step (1504). Otherwise, from step (1504), if the absolute value of the current sample of scaled auscultatory-sound-sensor time-series data S, i.e.
  • step (1510) if the sample counter j exceeds the number of samples Ns in the block of scaled auscultatory-sound-sensor time- series data S or auscultatory-sound-sensor time-series data S ⁇ indicating that the entire block of scaled auscultatory-sound-sensor time-series data S or auscultatory-sound- sensor time-series data S has been screened, ⁇ then the debond detection process 1500 is terminated with step (1516) by returning an indication to step (714) of the auscultatory- sound-sensing process 700 that the associated auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " is not debonded from the skin 38 of the thorax 20 of the test-subject 22.
  • step (1518) the debond detection process 1500 is terminated with step (1518) by returning an indication to step (714) of the auscultatory- sound-sensing process 700 that the associated auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " is debonded from the skin 38 of the thorax 20 of the test-subject 22.
  • the value of ND is equal to 4
  • the value of SD is equal to 1 second.
  • step (716) if, from step (714), the debond detection process 1500 detected that the associated auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " was debonded while acquiring the block of auscultatory-sound-sensor time-series data S, then the Data Recording Application (DRA) 14 is aborted in step (718), and the operator 48 is alerted that one or more auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " are debonded, so that this can be remedied.
  • DRA Data Recording Application
  • step (720) if, from step (714), the debond detection process 1500 did not detect that the associated auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " was debonded while acquiring the block of auscultatory-sound-sensor time-series data S, then, in step (720), if sufficient noise- screened data has not been gathered - for example, in one set of embodiments, a total duration of at least 65 seconds of recorded data, ⁇ then the auscultatory-sound-sensing process 700 continues with step (708).
  • an associated noise detection (i.e. noise-screening) process - operating on either the block of scaled auscultatory-sound-sensor time-series data S, or the block of auscultatory-sensor time-series data S, in parallel with the debond detection process 1500 - provides for detecting if the block of auscultatory-sound-sensor time-series data S has been corrupted by excessive noise, and if so, from step (726), that block of auscultatory- sound-sensor time-series data S is ignored, and the auscultatory-sound-sensing process 700 continues by repeating step (710) to acquire a new block of auscultatory-sound-sensor time-series data S. Otherwise, from step (726), if the block auscultatory-sound-sensor time-series data S has not been corrupted by excessive noise, the process continues with the above-described step (720).
  • noise detection i.e. noise-screening
  • step (720) if sufficient noise-screened data has been gathered for which the associated one or more auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " were not debonded from the skin 38 of the thorax 20 of the test-subject 22 - for example, in one set of embodiments, a total duration of at least 65 seconds of recorded data, ⁇ then, in step (722), at least the composite set of blocks of breath-held auscultatory-sound-sensor time- series data S acquired in step (710) are subsequently analyzed by an associated Data Analysis Application (DAA) 54 operative on the docking system 27 - as illustrated in FIGS.
  • DAA Data Analysis Application
  • DAA Data Analysis Application
  • all data may be recorded and provided to the Data Analysis Application (DAA) 54, along with an associated index that provides for identifying the corresponding associated breath-held portions thereof for which the associated auscultatory sound sensors 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 ", 12 3 " were neither detached nor debonded from the skin 38 of the thorax 20 of the test-subject 22, nor corrupted by noise.
  • FIGS. 9 and lOa-lOf illustrate a simulation of six blocks of breath-held auscultatory-sound-sensor time-series data S recorded in accordance with the first aspect 700 of auscultatory-sound-sensing process 700, with respective durations of ⁇ 3 ⁇ 4, &, ⁇ 1 ⁇ 4, t3 ⁇ 4, Ss, and ⁇ during which time periods the test-subject 22 was holding their breath, separated by periods Ai, ⁇ 2, A3, A4, and As of normal breathing, wherein FIGS.
  • FIGS. 10a- lOe illustrate breath-held auscultatory sound signals 16.1, 16.1' from a normally -bonded auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 " as illustrated in FIG. 5a
  • FIG. lOf illustrates a breath-held auscultatory sound signal 16.1, 16.1" from a debonded auscultatory sound sensor 12, 12 1 ', 12 2 ', 12 3 ' , 12 1 ", 12 2 “, 12 3 ", for example, as illustrated in any of FIGS.
  • FIGS. 10b- lOe are identical to FIG. 10a. However, it should be understood that typically the amplitude of the auscultatory sound signals 16, 16.1 varies from heartbeat to heartbeat, and from one breath-held segment to another.
  • one or more of the auscultatory-sound-sensing process 700, the data acquisition process 800, the scale-factor-determination process 1300, or the de-bond detection process 1500 could be implemented with corresponding alternative processes disclosed in U.S. Application Serial No. 16/136,015 filed on 19 September 2018 - with particular reference to FIGS. 16 through 22 - which is incorporated by reference herein in its entirety.
  • index pointer arrays io[] and ii[] are used to identify locations of associated events, for example, index pointer arrays io[] and ii[] to store the sample locations at the beginning and end of breath-held data segments of the corresponding sampled auscultatory sound data S m [] from the m th auscultatory sound sensor 12, and later-used index pointer arrays isi[] and is2[] to store the sample locations of the SI sound at the beginning of each heart cycle, and the S2 sound at the beginning of diastole respectively, wherein in FIG.
  • a status array Status [m, k] indicates the measurement status of the k th breath-held data segment of the m th auscultatory sound signal 16, i.e. the sampled auscultatory sound data S m () from the m th auscultatory sound sensor 12. Accordingly, step (728) that provides for ignoring data may be implemented by setting the corresponding value of the status array Status(m, k) to a value of IGNORE.
  • a noise detection process 1700 called from step (724) provides for determining whether or not a particular segment of breath-held auscultatory sound signal 16.1 is corrupted by excessive noise, and if so, provides for flagging that segment as being excessively noisy so as to be prospectively excluded from subsequent processing.
  • the noise detection process 1700 generates, in step (1714), frequency-domain noise filters FH[] responsive to cross-correlations of frequency spectra of pairs of adjacent auscultatory sound sensors 12.
  • sensor-index pointers ml[p] and m2[p] provide for identifying the associated auscultatory sound sensors 12, ml[p], ni2[p] of each pair, the latter of which is identified by pair pointer p.
  • the noise detection process 1700 For each pair of adjacent auscultatory sound sensors 12 in a set of adjacent pairs ⁇ selected by sensor- index pointers ml[p] and m2[p] in steps (1706) and (1710), respectively, wherein p is a pair-pointer initialized to 1 in step (1704) ⁇ the noise detection process 1700 generates, in step (1714), a frequency-domain noise filter FH[] by cross-correlating in step (1802) the frequency spectra FS A [] and FS B [] (generated in steps (1708) and (1712) of each associated breath-held auscultatory sound signal 16.1: S A [] and S B [], wherein the values of the frequency-domain noise filter FH[] are generated by normalizing the frequency spectra of the cross-correlation function to a range of 0 to 1 in step (1804), then subtracting these values from unity, and then setting resulting values that are less than a noise floor to the value of the noise floor in step (1806).
  • the frequency-domain noise filter FH[] provides for attenuating the components of the breath-held auscultatory sound signal 16.1: S A [] and S B [] that are correlated with one another. Accordingly, the operation of step (1904) provides for a matched filtering process to accentuate the underlying noise in the associated breath- held auscultatory sound signal 16.1: S A [] or S B [] .
  • the average powers PLOW, PMID, PHIGH in three respective frequency ranges 20 Hz to 200 Hz, 200 Hz to 800 Hz, and 800 Hz to 1,500 Hz, respectively, is calculated in steps (1922), (1924) and (1926), respectively, wherein each average power PLOW, PMID, PHIGH is compared with a corresponding threshold ⁇ for example, in one set of embodiments, -20 dB, -50 dB and -30 dB, respectively - in step (1928).
  • the corresponding breath-held auscultatory sound signal 16.1: S A [] or S B [] is then flagged in steps (1930) as being noisy if any of the associated noise power thresholds are exceeded. Referring to FIG.
  • the process of steps (1706) through (1722) repeats for each of NPAIRS pairs of adjacent auscultatory sound sensors.
  • the process of steps (1704) through (1726) is repeated until all the breath-held segments k of data have been processed.
  • the noise detection process 1700 commences with step (1702) by initializing a breath-held-segment pointer A to a value of 1, so as to provide for pointing to the first breath-held segment of data.
  • the breath-held- segment pointer k provides for pointing to the kth breath-held segment of data, of duration Sk, extending between sample locations io fkj and ii [k], as illustrated in FIG. 16.
  • the pair pointer p is initialized to a value of 1
  • a noise counter NNOISY is initialed to a value of 0.
  • step (1714) the frequency-domain noise filter FH[] generated by a matched-noise-filter generation process 1800 that ⁇ referring also to FIG. 18 ⁇ commences in step (1802) with the cross correlation of the frequency spectra FS A [], FS B [] of the sampled auscultatory sound data S A [], S B [] of the first ml[p] and second m2[p] auscultatory sound sensors 12 of the pair p, wherein the resulting cross-correlation is stored in array FH[] and then normalized to a range of 0 to 1 in step (1804), and then inverted in step (1806), wherein each element of the normalized array FH[] is subtracted from 1, and if the result is less than a noise floor, is set to the value of the noise floor NoiseFloor.
  • step (1808) the resulting frequency-domain noise filter FH[] is returned and subsequently used in steps (1716) and (1718) of the noise detection process 1700 to evaluate the noise in the frequency spectra FS A [], FS B [] of the sampled auscultatory sound data S A [], S B [] of the first ml[p] and second m2[p] auscultatory sound sensors 12 of the pair p, respectively, in accordance with an associated noise-content-evaluation process 1900, the latter of which is called from step (1716) to evaluate the noise content of the frequency spectrum FS A [] of the sampled auscultatory sound data S A [] of the first auscultatory sound sensor 12, ml[p] of the pair p, and which is called from step (1718) to evaluate the noise content of the frequency spectrum FS A [] of the sampled auscultatory sound data S A [] of the second auscultatory sound sensor 12, m2[p] of the pair p.
  • the noise-content-evaluation process 1900 commences with step (1902) with receipt of the index m of the associated auscultatory sound sensor 12, m, the associated frequency spectrum FS [] of the associated auscultatory sound sensor 12, m, and the associated frequency-domain noise filter FH[] . Then, in step (1904), the time domain noise signal SN[] - containing a total of NPTS data points, i.e.
  • the number of data points in the breath-held sampled auscultatory sound data S m [ io [k] : ii [k]] ⁇ is given by the inverse Fourier Transform of the product of the associated frequency spectrum FS [] with the associated frequency-domain noise filter FH[] , corresponding to a time-domain cross-correlation of the corresponding associated time-domain signals.
  • each of the NFFT summation data points of a frequency-domain summation array FXSUM [] is initialized to zero, as is an associate summation counter NSUM, wherein the number of summation data points NFFT is a power of 2, for example, 1024, and substantially less than the total number of data points NPTS in the time domain noise signal SN[] .
  • an index jMi ⁇ to the first sample of an NFFT-point window of samples to be analyzed from the time domain noise signal SN[] - is initialized to a value of 1.
  • step (1910) an index jMAx ⁇ to the last sample of the NFFT-point window of samples to be analyzed from the time domain noise signal SN[] - is set to the value of jMi + NFFT - 1.
  • step (1912) if the end of the time domain noise signal SN[] has not been reached, then, in step (1914), the square of values - i.e. corresponding to noise power ⁇ of an NFFT Fourier Transform of the data form the NFFT-point window of samples from the time domain noise signal SN[] over the range of samples SN[JMIN] to SN[jMAx], is added to the frequency-domain summation array FXSUM[] .
  • step (1916) the summation counter NSUM is incremented, and in step (1918), the index jMi is incremented by half the width of the NFFT-point window, i.e. by a value of NFFT 12, so as the provide for the next NFFT-point window to be analyzed to overlap the current NFFT-point window by half the window width.
  • the above noise-content-evaluation process 1900 repeats beginning with step (1910), until, in step (1912), the index jMAx exceeds the end of the time domain noise signal SN[] , after which, in step (1920), each of the values of the frequency-domain summation array FXSUM [] is divided by the value of the summation counter NSUM SO as to calculate an associated average noise power FX[] . Then, in steps (1922), (1924) and (1926), respectively, the noise power is summed in three different corresponding respective frequency ranges, for example, 20 Hz to 200 Hz, 200 Hz to 800 Hz, and 800 Hz to 1,500 Hz, respectively, to give three corresponding respective power levels, PLOW, PMID and PHIGH, respectively.
  • step (1928) if any of the power levels, PLOW, PMID or PHIGH exceeds a corresponding respective power threshold value ThresholdLow, ThresholdMiD or ThresholdfflGH, then, in step (1930), the noise threshold is considered to have been exceed for the particular auscultatory sound sensor 12, m and the particular associated segment k of breath-held sampled auscultatory sound data S m [ io [k] : ii [k]] with indication of an associated status in a NoiseStatus flag.
  • step (1932) the noise threshold is considered to have not been exceed for the particular auscultatory sound sensor 12, m and the particular associated segment of breath-held sampled auscultatory sound data S m [ io [k] : ii [k]], with indication of an associated status in the NoiseStatus flag.
  • the results from either steps (1930) or (1932) are then logged by an associated results-logging process 2000 which is called from step (1934).
  • the results-logging process 2000 commences with receipt in step (2002) of the index m of the associated auscultatory sound sensor 12, m and the associated NoiseStatus flag. If, in step (2004), the NoiseStatus flag indicates a noisy auscultatory sound sensor 12, m, then, in step (2006), the noise counter NNOISY is incremented, and, in step (2008), the corresponding element of the status array Status [m, k] for the associated auscultatory sound sensor 12, m and breath-held segment k is updated to activate an associate noisy flag, so as to indicate the associated auscultatory sound sensor 12, m being noisy for the associated breath-held segment k.
  • step (2010) if the value of the noise counter NNOISY is greater than 1, then, step (2012), the corresponding elements of the status array Status [m, k] for each of the auscultatory sound sensors 12, m is updated to activate the Ignore flag, so as to provide for ignoring each of the auscultatory sound sensors 12, m for the associated breath-held segment k.
  • step (2014) if the noisy flag of the status array Status [m, k] is activated for at least NFAII breath-held segments k for the associated auscultatory sound sensor 12, m, then, in step (2016), status array Status [m] for the associated auscultatory sound sensor 12, m is updated to activate the Bad flag for the associated auscultatory sound sensor 12, m, so as to indicate that the associated auscultatory sound sensor 12, m is bad. Then, or otherwise from either step (2004) or step (2014), results-logging process 2000 terminates by returning to the noise detection process 1700.
  • step (1720) if all of the pairs of adjacent auscultatory sound sensors 12 have not been processed, then, in step (1722), the pair pointer p is incremented, and the noise detection process 1700 is repeated for the next pair of auscultatory sound sensors 12, ml[p], m2[p], beginning with step (1706) for the same breath-held segment k.
  • step (1724) If in step (1724), additional segments of breath-held sampled auscultatory sound data S m [ io [k] : ii [k]] remain to be processed, then, in step (1726), the breath-held-segment pointer k is incremented, and the noise detection process 1700 is repeated beginning with step (1704) for the next segment of breath-held sampled auscultatory sound data S m [ io [k] : ii [k]] . Otherwise, from step (1724), the noise detection process 1700 terminates with step (1728).
  • the results from the docking system 27 may be transferred to a server computer system 56, for example, for subsequent transfer to an external data storage or processing system 58, for example, to provide for either viewing or analyzing the results at a remote location.
  • a server computer system 56 for example, for subsequent transfer to an external data storage or processing system 58, for example, to provide for either viewing or analyzing the results at a remote location.
  • the composite set of blocks of breath-held auscultatory-sound-sensor time-series data S are screened prior to analysis by the associated Data Analysis Application (DAA) 54, for example, by first segmenting the set of blocks of breath-held auscultatory-sound-sensor time-series data S by heart cycle with an associated segmentation process 60, and then validating the associated heart cycle data with an associated heart cycle validation process 62, for example, to provide for additional screening for heart-phase associated noise.
  • DAA Data Analysis Application
  • any reference herein to the term “or” is intended to mean an “inclusive or” or what is also known as a “logical OR”, wherein when used as a logic statement, the expression “A or B” is true if either A or B is true, or if both A and B are true, and when used as a list of elements, the expression “A, B or C” is intended to include all combinations of the elements recited in the expression, for example, any of the elements selected from the group consisting of A, B, C, (A, B), (A, C), (B, C), and (A, B, C); and so on if additional elements are listed.

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Abstract

Un réseau chronologique de données de bruit est généré à partir d'une transformée de fréquence inverse du produit du spectre de fréquence d'un signal sonore d'auscultation avec un filtre de bruit associé généré en réponse à une corrélation croisée de spectres de fréquence de signaux sonores d'auscultation provenant de capteurs de sons ou de vibrations d'auscultation adjacents sur le torse d'un sujet de test. La puissance de bruit dans au moins une plage de fréquences de moyenne de spectres de fréquence à partir d'une pluralité de fenêtres du réseau chronologique de données de bruit est comparée à un seuil pour déterminer si le capteur de son ou de vibration d'auscultation associé est excessivement bruyant. Dans un mode de réalisation, le filtre de bruit est généré par soustraction d'une unité, d'une corrélation croisée normalisée unitaire de spectres de fréquence des signaux sonores d'auscultation, les valeurs résultantes étant écrêtées de manière à ne pas être inférieures à un plancher de bruit associé.
PCT/US2018/056840 2017-10-21 2018-10-22 Procédé de détection de bruit dans des signaux sonores d'auscultation d'un système de détection de maladie artérielle coronaire WO2019079786A1 (fr)

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WO2021225977A1 (fr) * 2020-05-03 2021-11-11 Ausculsciences Canada, Inc. Système d'auscultation
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CN114176623B (zh) * 2021-12-21 2023-09-12 深圳大学 声音降噪方法、系统、降噪设备及计算机可读存储介质

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