Patent Description:
Coronary Artery Disease (CAD) is a condition in which plaque builds up inside the coronary arteries. These arteries supply the heart muscle with oxygen-rich blood. Plaque narrows the arteries and reduces blood flow to the heart, which may cause angina or a heart attack. Over time, CAD may weaken the heart muscle and lead to heart failure and arrhythmias. CAD is one of the most common types of heart disease, and efficient and accurate tools for estimating or indicating the risk of CAD are therefore important.

Historically, detection of CAD has involved patient history, physical examination, stress testing, and possibly analysis of coronary angiograms. During physical examination, a stethoscope is often used to examine the sound of the heart. Although the role of the stethoscope in the modern clinic seems to be fading, new electronic stethoscopes with integrated diagnostic algorithms may alter the trend and expand the clinical potential of the stethoscope. There is therefore a need for developing efficient and accurate diagnostic algorithms for estimating a risk for CAD.

A number of distinct heart sounds are generated during a heartbeat. The sounds are produced by blood turbulence and vibration of cardiac structures, primarily due to the closing of the valves within the heart. Four sounds can typically be identified, which are commonly called S1, S2, S3 and S4.

The S1 sound is usually the loudest heart sound and is the first heart sound during ventricular contraction. S1 is often described as a "lubb" sound. S1 occurs at the beginning of ventricular systole and relates to the closure of atrioventicular valves between the atria and the ventricles.

The S2 sound is often described as a "dubb" sound. S2 occurs at the beginning of the diastole and relates to the closing of the semilunar valves separating the aorta and pulmonary artery from the left and right ventricles, respectively. S1 and S2 sounds are "normal heart sounds" that can easily be heard with a stethoscope.

However, the S3 and S4 sounds can usually not be heard in the normal heart of a person over <NUM> years old. These are typically attributed "abnormal heart sounds". The S3 sound, also referred to as "ventricular gallop", occurs in the early diastolic period and is caused by the ventricular wall distending to the point it reaches its elastic limit. The S4 sound, also referred to as "atrial gallop", occurs near the end of atrial contraction and is also caused by the ventricular wall distending until it reaches its elastic limit.

Heart sounds can be used to augment the diagnosis and to help assess the severity of important types of a cardiac disease. For example, after age <NUM>, S3 can indicate congestive heart failure, and S4 can indicate hypertension, acute myocardial infarction, or CAD. Unfortunately, studies have shown that even highly experienced physicians do not reliably detect important heart sounds. Therefore various diagnostic tools have been developed to support physicians in detecting possible heart diseases. For example, such tools are described in <CIT> and <CIT>. <CIT>) discloses a relevant blood pressure cuff comprising auscultatory measurement means. It fails to disclose an adaptive filter based on a detected diastolic period.

There is a problem with existing electronic stethoscopes using algorithms to detect or estimate the risk of CAD. The CAD related murmurs are weak and the difference between CAD and non-CAD sounds are typically small and hard to detect. The algorithms used are likely to be sensitive to other types of noise, such as ambient noise and physiological noise originating from a patient. This limits the usability of the electronic stethoscopes, since the environment has to be controlled to avoid ambient noise. Ambient noise may be hard to control and the practical use of an electronic stethoscope, in particular a portable electronic stethoscope, is therefore limited. There is a need for reducing the sensitivity of electronic stethoscopes, in particular those for estimating the risk for CAD, to ambient noise. There is also a need for improving the efficiency and accuracy when determining or classifying the risk for CAD.

It is therefore an object to address some of the problems and technical challenges outlined above.

Covered by the diastolic period is here understood to encompass the first portion and the second portion corresponding in extent to the diastolic period, or the first portion and the second portion being located within the diastolic period. The first portion and the second portion may be of equal length. The first portion and the second portion may be concurrent, or correspond to the same period in time. Throughout these specifications, each individual occurrence of sound level may be understood as the power or the amplitude, such as the power or amplitude of the first sound recording or the second sound recording.

Noise in a first sound recording that originates from the ambient background typically has travelled through the chest of the person, which may cause a time delay and a frequency shift of the noise with respect to the noise in the corresponding second sound recording.

The overall effect of the adaptive filter or filtering is that the effect of ambient noise on the indication of the risk for CAD is reduced or removed, which gives a more robust and accurate result. Further, the adaptive filtering allows for an optimization with respect to the noise reduction or removal. Large variations in sounds levels may cause artefacts in an adaptive filter. By letting the first portion and the second portion to be covered by the diastolic period, the strong S1 and S2 sounds are excluded when forming the adaptive filter, thus enabling weaker CAD related heart sounds to be detected, which leads to an improved accuracy in determining the indication of a risk for CAD.

Subtracting ambient sounds recorded in the second sound recordings directly from heart sounds in the first sound recording would introduce errors, since the noise in the heart sounds corresponding to the ambient sounds are delayed and have an altered frequency distribution due to passage through the chest. Thus, the adaptive filtering will improve the accuracy of the determining of the indication of the risk for CAD.

The transfer function of the chest of a person varies with time. By limiting the time interval of the first and second periods as described above, the transfer function can be assumed to be time-invariable, which allows for a more accurate modeling of the chest and a more accurate adaptive filter.

One alternative way to avoid noise is to remove the first sound recordings that are noisy. The adaptive filter allows for the noise of the first sound recordings to be reduced or removed in an efficient and accurate manner, which means that more first sound recordings can be used in the determining of the indication of the risk for CAD. In a noisy environment, less first sound recordings are required for determining the risk of CAD, and quicker indication of CAD is achieved.

In the filtering (c) of each first sound recording. the second step (ii) of performing an adaptive filtering includes: (ii) determining a first portion of the first sound recording and a second portion of the simultaneously recorded second sound recording, wherein the first portion and the second portion are covered by the diastolic period. The filtering (c) then continues with: (iii) determining an adaptive filter for the first sound recording, wherein the adaptive filter is based on the first portion and the second portion and configured for reducing noise originating from the ambient background that is present in both the first sound recording and in the simultaneously recorded second sound recording, and (iv) employing the adaptive filter to the first sound recording.

A processor is here understood to encompass a processor that is dedicated for the described function. Alternatively, the processor may be a general purpose processor. A processor is here understood to also encompass a single processor that individually handles a process, or a group of processors that cooperate to handle a process. The processor may encompass a transient memory for performing its function or running the program code instructions. The system may be portable electronic stethoscope.

Additional or alternative features of the above aspects are explained in the detailed description below or in the appended claims. Further objects may also be construed from the detailed description.

Any method referred to in the description is not part of the claimed invention.

In the different aspects of the exemplary configuration, step (d) of determining an indication may comprise: (d1) determining one or more first heart sound levels from the filtered first sound recordings, wherein each first heart sound level is determined from a first period within a filtered first sound recording, and (d2) determining the risk for coronary artery disease based on the one or more first heart sound levels. The first period may correspond to the diastolic period, or a period within the diastolic period, or the first portion of the first sound recording, or a portion within the first portion.

The step (d) of determining an indication of the risk for coronary artery disease based on the filtered first sound recordings of the first plurality may comprise: performing one of the methods described in <CIT> for diagnosing of coronary artery disease with the filtered first sound recordings of the first plurality as the recorded acoustic data.

In the step (ii), the adaptive filtering may be performed on the complete first sound recording, or on a period corresponding to the diastolic period, or on a period within the diastolic period, or on the first portion of the first sound recording, or on a portion within of the first portion, or on the first period.

As described above, there are great variations of the amplitude of a heartbeat sound, which may cause artefacts in the adaptive filtering and reduce the accuracy of when determining the indication of the risk for CAD. The amplitude of the of the sounds that may indicate CAD in the diastolic period may be several orders of magnitude smaller than the "normal heart sounds", such as the S1 and S2 sounds. Thus, the limiting the of first portion to, the second portion, and the first period to the diastolic period, or a period within the diastolic period, synergetically contributes an improved accuracy of the determining the risk of CAD, which in turn gives a more accurate indication of CAD.

The first portion of the first sound recording and the second portion of the simultaneously recorded second sound recording may start between <NUM> and <NUM>, or at <NUM>, subsequent to the start of the diastolic period. The first portion of the first sound recording and the second portion of the simultaneously recorded second sound recording may have a length that is less than <NUM>, or a length that is less than <NUM>. The step (i) of determining the diastolic period may also comprise determining the onset of the S2 sound, and the first portion of the first sound recording and the simultaneously recorded second portion of the second sound recording may start between <NUM> and <NUM>, or at <NUM>, subsequent to the onset of the S2 sound. The step (i) of determining the diastolic period may also comprise determining the onset of the S4 sound, and the first portion of the first sound recording and the second portion of the simultaneously recorded second sound recording may end before the onset of the S4 sound. The above limitations of the extent of the first and second portions contribute to avoiding strong heart sounds, which improves the adaptive filtering. If the first period is limited by the first portion, as described above, a more accurate indication of CAD can thus be achieved. The limitations are particularly advantageous if the first period correspond to the first portion, since they allow for a filtered length of first period that is sufficiently long for obtaining a strong signal of the sounds possibly relating to CAD.

In the step (ii), the adaptive filtering may be based on a Wiener filter. This allows for a fast filtering that can be applied to the whole first sound recording. Alternatively or additionally, in the step (ii), the adaptive filtering may be based on a recursive least square adaptive filter, a Least Mean Squares (LMS) adaptive filters, and/or a normalized LMS adaptive filter.

The method according to the first aspect may further comprise prior to the step (c) of performing the filtering: (e) determining a first noise level of each second sound recording of the second plurality, and (f) discarding the first sound recordings having a simultaneously recorded second recording with a first noise level above a first determined noise level. The processor in the second aspect may be further be configured to perform the above steps (e) and (f) prior to the step (c). Similarly, the computer program product of the third aspect may comprise program code instructions configured to cause the processor to perform the above steps (e) and (f) prior to the step (c).

In step (e), the first noise level may be based on a variance of the sound level of the complete second sound recording, or at least of a period corresponding to or covering a complete heartbeat in the second sound recording. In step (e), a first band-pass filtering of the complete second sound recording, or at least of a period corresponding to or covering a complete heartbeat in the first sound recording, may be performed prior to determining the first noise level. The first band-pass filtering may allow passage within <NUM>-<NUM>. In step (f), the first determined noise level may be approximately <NUM> dB.

With the above described treatment of the second sound recordings of the second plurality, first sound recordings that are affected by general background noise that extends over a longer portion or part of a heartbeat, such as an alarm or person speaking, are removed. This, way, the steps (e) and (f) features contribute to a more robust determining of the indication of the risk for CAD.

The method according to the first aspect may further comprise prior to the step (c) of performing the filtering: (g) determining a second heart sound level of each first sound recording of the first plurality, and (h) discarding the first sound recordings having a second heart sound level that is below a first determined heart sound level. The processor in the second aspect may be further be configured to perform the above steps (g) and (h) prior to the step (c). Similarly, the computer program product of the third aspect may comprise program code instructions configured to cause the processor to perform the above steps (g) and (h) prior to the step (c).

In step (g), the second heart sound level may be based on a mean or variance of the sound level of the complete first sound recording, or at least of a period corresponding to or covering a complete heartbeat in the first sound recording. In step (g), a second band-pass filtering of the complete first sound recording, or at least of a period corresponding to or covering a complete heartbeat in the first sound recording, may be performed prior to determining the second heart sound level. The second band-pass filtering may allow passage within <NUM>-<NUM>. In step (h), the first determined heart sound level may be approximately <NUM> dB.

The above described treatment of the first sound recordings of the first plurality may ensure that they have been obtained properly before being used to determine the indication of the risk for CAD. For example, if the first acoustic sensor is not placed in a correct manner on the patient, the heart sound level may be below <NUM> dB, and the affected first sound recordings are discarded. This contributes to a more robust determining of the indication of the risk for CAD.

The method according to the first aspect may further comprise subsequent to step (c) of performing the filtering and prior to the step (d) of determining an indication: (i) determining a second noise level for a second period of each second sound recording of the second plurality, and (j) discarding each first sound recordings having a simultaneously recorded second recording with a second noise level in the second period above a second determined noise level. The processor in the second aspect may further be configured to perform the above steps (i) and (j) subsequent to step (c) and prior to the step (c). Similarly, the computer program product of the third aspect may comprise program code instructions configured to cause the processor to perform the above steps (i) and (j) subsequent to step (c) and prior to the step (c).

The second period may correspond to the diastolic period, or a period within the diastolic period, or the second portion of the second sound recording. In step (i), the second noise level may be based on a variance of the sound level of the second period. In step (i), a third band-pass filtering may be performed prior to determining the second noise level. The third band-pass filtering may allow passage within <NUM>-<NUM>. The third band-pass filtering may be performed on the second period. In step (j), the second determined noise level may be approximately <NUM> dB.

Despite the use of the adaptive filter, and the optional discarding by steps (e) and (f) as described above, some heartbeats may still be contaminated by very intense and brief ambient noise in the diastolic period, like a door closing or an item being dropped. Such ambient noise may be avoided by steps (i) and (j), thus contributing to a more robust and accurate determining of the indication of the risk for CAD.

The method according to the first aspect may further comprise subsequent to step (c) of performing the filtering and prior to the step (d) of determining an indication: (k) determining a third heart sound level for a third period of each first sound recording of the first plurality, and (l) discarding the first sound recording if the third heart sound level exceeds a second determined heart sound level. The processor in the second aspect may further be configured to perform the above steps (k) and (l) subsequent to step (c) and prior to the step (d). Similarly, the computer program product of the third aspect may comprise program code instructions configured to cause the processor to perform the above steps (k) and (l) subsequent to step (c) and prior to the step (d).

The third period may correspond to the diastolic period, or a period within the diastolic period, or the first portion of the first sound recording, or correspond to the second period. In step (k), the third heart sound level may be based on a mean or variance of the sound levels of the third period. In step (k), the third heart sound level may be based on the median of the variance of the sound levels of the third periods. In step (k), a fourth band-pass filtering may be performed prior to determining the third heart sound level. The fourth band-pass filtering may allow passage within <NUM>-<NUM>. The fourth band-pass filtering may be performed on the third period. In step (l), the determined third heart sound level may be between <NUM> and <NUM> dB, or approximately <NUM> dB, greater than the median of the mean or variance of the sound levels of the third periods. The steps (k) and (l) may be performed repeatedly in an iterative process.

In addition to ambient noise, a first sound recording may be contaminated by internal physiological noise, such as bowel or peristaltic sound. Such internal noise may be removed by the steps (k) and (l), which contributes a more robust and accurate determining of the indication of the risk for CAD.

The system of the second aspect or the electronic stethoscope of the fifth aspect may comprise a support for supporting the first acoustic sensor and the second acoustic sensor, and for positioning the second acoustic sensor at the first acoustic sensor. The system may comprise a housing for accommodating the first acoustic sensor and the second acoustic senor. The housing may be configured to acoustically shield the first acoustic sensor from the ambient background.

The program code instructions of the third aspect may be stored on a non-transitory memory.

The aspects described above in the summary and detailed description are to be read together with the claims and may further encompass any of the features described in the claims.

The following detailed description refers to the accompanying drawings. The same reference numbers in different drawings identify the same or similar elements, steps, or features. Further, the following detailed description is provided for the purpose of illustration and explanation of some example embodiments.

<FIG> is a plot of several overlaid recorded heartbeats. The S1, S2, S3, and S4 sounds are indicated, as well as the diastasis or diastolic period <NUM>. The heartbeats have been aligned with respect to their respective S2 sound. The horizontal axis indicates the time in milliseconds with respect to the onset of the S2 sound. The vertical axis indicates the sound pressure in Pascal.

<FIG> schematically illustrates a configuration of a system <NUM> for indicating a risk for CAD for a person. The system <NUM> has a first acoustic sensor <NUM> that can be placed on the chest of a person <NUM> and record heartbeats. The system <NUM> also has a second acoustic sensor <NUM> that can be placed at the person <NUM> and record ambient background sounds. A processor <NUM> is connected with the first acoustic sensor <NUM> and the second acoustic sensor <NUM>. The processor <NUM> has a transient memory <NUM> which can store recordings from the first acoustic sensor <NUM> and the second acoustic senor, and by which it can execute program code instructions.

The system <NUM> comprises a support <NUM> that supports the first acoustic sensor <NUM> and the second acoustic sensor <NUM> and positions the second acoustic sensor <NUM> at the first acoustic sensor <NUM>. The system <NUM> further has a housing <NUM> that accommodates the first acoustic sensor <NUM> and the second acoustic senor <NUM>. The system <NUM> also has a non-transient memory <NUM> storing program code instructions for the processor.

One application of the above system is as an electronic stethoscope. In a variant of the embodiment, the program code instructions cause the processor to perform a method for indicating the risk for CAD. Several embodiments of such methods, or related methods, are described below.

In one embodiment of the system, it additionally has an indicator <NUM> operatively connected with the processor <NUM>. The indicator <NUM> can, for example, have a set of differently colored lamps or a display that shows the determined indication. The indication as such may be color coded or represented by a number that can be associated with the risk for CAD.

<FIG> is a flow chart schematically illustrating a configuration of a general method <NUM> for indicating a risk for CAD for a person. A first plurality of first sound recordings is obtained <NUM>, where each of the first recordings is of a heartbeat of the person. A second plurality of second sound recording is also obtained <NUM>, where each second sound recording is of the ambient background surrounding the person and is recorded simultaneously to a first sound recording of the first plurality. This means that each second sound recording forms a pair with a first sound recording.

Subsequently, a filtering of each first sound recording of the first plurality is performed <NUM>. The filtering is adaptive and uses a simultaneously recorded second sound recording. According to the invention, in the filtering <NUM> of each first sound recording, a diastolic period of the heartbeat of the first sound recording is first determined <NUM>. An adaptive filtering of the first sound recording is then performed <NUM>. The adaptive filtering is configured to reduce noise originating from the ambient background that is present in both the first sound recording and in the simultaneously recorded second sound recording.

According to the invention, the adaptive filtering <NUM> is based on, or generated from, a first portion of the first sound recording and on a second portion of the simultaneously recorded second sound recording, where the first portion and the second portion are covered by and located within the diastolic period.

Subsequent to the filtering <NUM>, an indication of the risk CAD is determined <NUM> based on the filtered first sound recordings of the first plurality.

A flow chart illustrating a detailed configuration of the adaptive filtering <NUM> is shown in <FIG>. First, a first portion of the first sound recording is determined <NUM> and a second portion of the simultaneously recorded second sound recording is determined <NUM>. The adaptive filter is then determined <NUM> based on the first portion and the second portion so that it can reduce noise originating from the ambient background that is present in both the first and second sound recordings. Subsequently, a portion of the first sound recording, e.g. the first portion, is filtered <NUM> by the adaptive filter.

<FIG> is a flow chart illustrating a detailed configuration of a method <NUM> for indicating a risk for CAD of a person. The steps described in relation to <FIG> are included and indicated with the same indexing.

For each first portion of the first sound recording and the second portion of the simultaneously recorded second sound recording, the first portion and the second portion are of equal length, and the first portion and the second portion are concurrent. The first portion of the first sound recording and the second portion of the simultaneously recorded second sound recording start <NUM> after to the start of the diastolic period. Further, the length of the first portion of the first sound recording and the second portion of the simultaneously recorded second sound have a length that is no longer than <NUM>.

When determining <NUM> the diastolic period the onset of the S2 sound is determined <NUM>. For example, this can be done as described by <NPL>). The first portion of the first sound recording and the second portion of the simultaneously recorded second sound recording start at <NUM> subsequent to the onset of the S2 sound.

Additionally, the onset of the S4 sound is also determined <NUM>. For example, this can be done by aligning heartbeats according to their respective S1 sounds. The S4 sound is linked to the S1 sound, which means that the S4 sound is typically aligned with the S1 sound. The activity before the S4 sound is regarded as related to the previous heartbeat. The onset of the S4 sound is regarded as the time at which the heartbeats start to be synchronized according to an alignment of the subsequent S1 sounds. Further, the first portion of the first sound recording and the second portion of the simultaneously recorded second sound recording end before the onset of the S4 sound. However, the abovementioned length of <NUM> may cause the first and second periods to end earlier than the onset of the S4 sound.

The adaptive filtering is based on a Wiener filter and the filtering is performed on the first portion of each first sound recording. In an alternative configuration, the adaptive filtering is based on a least square filter.

Prior to the filtering <NUM>, a first noise level of each second sound recording of the second plurality is determined <NUM>, and each first sound recording having a simultaneously recorded second recording with a first noise level above a first determined noise level is discarded <NUM>. The first noise level is based on the variance of the sound level of the complete second sound recording. A first band-pass filtering allowing passage within <NUM>-<NUM> of the complete second sound recording is performed prior to determining the first noise level. Further, first determined noise level is set to <NUM> dB.

Prior to the filtering <NUM>, a second heart sound level of each first sound recording of the first plurality is also determined <NUM>, and the first sound recordings having a second heart sound level that is below a first determined heart sound level are discarded <NUM>. The second heart sound level is based on the variance of the sound level of the corresponding complete first sound recording. A second band-pass filtering allowing passage within <NUM>-<NUM> of the complete first sound recording is performed prior to determining the first noise level. Further, the first determined heart sound level is set to <NUM> dB.

Subsequent to the filtering <NUM> and prior to the determining <NUM> of an indication for CAD, a second noise level for a second period of each second sound recording is determined <NUM>. Additionally, each first sound recordings having a simultaneously recorded second recording with a second noise level above a second determined noise level is discarded <NUM>. Each second period corresponds in extent to the second portion of the same second sound recording. The second noise level is based on the variance of the sound level of the second period. A third band-pass filtering allowing passage within <NUM>-<NUM> is performed prior to determining the second noise level. Further, he second determined noise level is set to <NUM> dB.

Subsequent to the filtering <NUM> and prior to the determining <NUM> of an indication for CAD, a third heart sound level for a third period of each first sound recording is determined <NUM>. Further, the first sound recording is discarded <NUM> if the third heart sound level exceeds a second determined heart sound level. The third period corresponds to first portion of the first sound recording of the corresponding first sound recording. A fourth band-pass filtering allowing passage within <NUM>-<NUM> is performed prior to determining the third heart sound level. The third heart sound level is based on the variance of the sound levels of the third periods. The determined third heart sound level is set to approximately <NUM> dB greater than the median of the variance of the sound levels of the third periods.

<FIG> is a flow chart illustrating a detailed configuration of the determining <NUM> of the indication of the risk for CAD. This step can be implemented in the above described methods. One or more first heart sound levels from the filtered first sound recordings are determined <NUM>. Each first heart sound level is determined from a first period within a filtered first sound recording. The risk for CAD is then determined <NUM> based on the one or more first heart sound levels. Each first period correspond in extent to the diastolic period of the corresponding first sound recording.

One example of determining the risk for CAD is to calculate the mean of the one or more first heart sound levels. If the means is greater than a predetermined value, a high risk is indicated, and if the mean is lower than a predetermined value, a low risk is indicated.

<FIG> schematically illustrates another configuration of a system <NUM>. The system <NUM> has a first acoustic sensor <NUM> configured to be placed on the chest of a person <NUM> and for recording heartbeats, and a second acoustic sensor <NUM> configured to be placed at the person <NUM> and for recording ambient background sounds. The system <NUM> further has a control unit <NUM> that is operatively connected with the first acoustic sensor <NUM> and the second acoustic sensor <NUM>.

The control unit <NUM> can obtain a first plurality of first sound recordings with the first acoustic sensor <NUM>, and each first recording is of a heartbeat of the person <NUM>. Further, the control unit <NUM> can obtain a second plurality of second sound recording with the second acoustic sensor <NUM>, and each second sound recording is of the ambient background surrounding the person <NUM> and being recorded simultaneously to a first sound recording of the first plurality.

The control unit <NUM> has a filtering unit <NUM> that can perform a filtering of each first sound recording of the first plurality by using a simultaneously recorded second sound recording of the second plurality. The filtering unit <NUM> has a first determining unit <NUM> that can determine a diastolic period of the heartbeat of the first sound recording, and an adaptive filter unit <NUM> that can perform an adaptive filtering of the first sound recording for reducing noise originating from the ambient background that is present in the first sound recording and in the simultaneously recorded second sound recording. The adaptive filtering is based on a first portion of the first sound recording and on a second portion of the simultaneously recorded second sound recording. According to the invention, the first portion and the second portion are covered by the diastolic period.

The system <NUM> further has a second determining unit <NUM> operatively connected with the control unit <NUM> unit that can determine an indication of the risk for CAD-based on the filtered first sound recordings of the first plurality. In another embodiment of the system <NUM>, the control unit <NUM> additionally has an indication unit <NUM> operatively connected with the second determining unit <NUM> that can indicate the determined indication. An indication unit <NUM> can for example have a set of differently colored lamps or a display that shows the determined indication. The indication as such may be color coded or represented by a number that can be associated with the risk for CAD.

<FIG> is a flow chart illustrating a configuration of a method <NUM> that filters a first sound recording of a heartbeat of a person. The filtering is performed by using a second sound recording of the ambient background surrounding the person, where the second sound recording is recorded simultaneously to the first sound recording. A diastolic period of the heartbeat of the first sound recording is first determined <NUM>. Subsequently, an adaptive filtering of the first sound recording is performed <NUM> for reducing noise originating from the ambient background that is present in the first sound recording and in the second sound recording.

According to the invention, the adaptive filtering is based on a first portion of the first sound recording and on a second portion of the second sound recording, and wherein the first portion and the second portion are covered by the diastolic period.

An example of program code instruction, in this case MATLAB code, for implementing the Wiener filter in the abovementioned configurations is described below. A filtering function is defined as: <MAT>.

In another configuration, the filter function is defined as: <MAT>.

In the above functions, x is the signal to be denoised, or the first portion of the first sound recording; noise is a vector representing the noise signal, or the second portion of a second sound recording; M is the filter order, z is the filtered signal, or filtered first portion; and Hd are digital filter coefficients. For example, the filter order can be <NUM> samples corresponding to <NUM>. An autocorrelation matrix of the noise signal is then generated: <MAT> <MAT> <MAT>.

The cross correlation between signal and noise is determined: <MAT>.

The digital filter coefficients are then generated: <MAT>.

The noise signal is then generated: <MAT>.

The noise signal is subtracted from the signal: <MAT>.

Claim 1:
A system (<NUM>, <NUM>) comprising:
(A) a first acoustic sensor (<NUM>, <NUM>) configured to be placed on the chest of the person and for recording heartbeats,
(B) a second acoustic sensor (<NUM>, <NUM>) configured to be placed at the person and for recording ambient background sounds,
(C) a processor (<NUM>) operatively connected with the first acoustic sensor and the second acoustic sensor and configured to:
(a) obtain a first plurality of first sound recordings with the first acoustic sensor, wherein each first sound recording is of a heartbeat of the person,
(b) obtain a second plurality of second sound recording with the second acoustic sensor, wherein each second sound recording is of the ambient background surrounding the person and being recorded simultaneously to a first sound recording of the first plurality,
(c) perform a filtering of each first sound recording of the first plurality by using a simultaneously recorded second sound recording of the second plurality, the filtering of each first sound recording comprises:
(i) determining a diastolic period of the heartbeat of the first sound recording, and
(ii) determining a first portion of the first sound recording and a second portion of the simultaneously recorded second sound recording, wherein the first portion and the second portion are covered by the diastolic period,
(iii) determining an adaptive filter for the first sound recording, wherein the adaptive filter is based on the first portion and the second portion and configured for reducing noise originating from the ambient background that is present in both the first sound recording and in the simultaneously recorded second sound recording, and
(iv) employing the adaptive filter to the first sound recording,
wherein the processor is further configured to:
(d) determining an indication of the risk for coronary artery disease based on the filtered first sound recordings of the first plurality.