The invention relates to a method, an analysis device, a computer program and a computer program product analysing phonocardiogram and electrocardiogram data from a portable sensor device.
ECG is an established technology where electric signals generated by the body of a patient are measured and analysed. Traditionally, a number of electrodes are placed on the body at various places. A conductive gel is used to provide better conductive contact between the electrode and the skin. The patient typically lies down for minutes when the ECG is taken. The data detected using the electrodes is recorded and can be analysed by a professional, such as a physician or trained nurse. Once the measurement procedure is done, the conductive gel is wiped off.
While having proved useful, the traditional way of obtaining an ECG is not optimal in all cases. For instance, such an ECG needs to be measured in a clinic and the procedure is messy for the patient.
Lately, portable sensor devices with integral electrodes for obtaining ECG data have been developed. These portable sensor devices allow users to capture ECG data at will and also without the use of conductive gel. This gives the user greater control over when to capture ECG data and also in a much more convenient and less messy way.
Such portable sensor devices can also be configured to measure phonocardiogram (PCG) data, i.e. sound data of the heart. However, PCG data captured by a portable device is susceptible to a noisier environment than e.g. in a clinic. Additionally, more noise can occur when an inexperienced user is using the portable sensor device to capture the PCG data, compared to when an experienced medical professional captures the PCG data.
The analysis of electrocardiogram data and the phonocardiogram data is complicated and any incorrect analysis should be avoided to the greatest extent possible, as this can affect the health of the user.
It is an object to improve the analysis of the combination of electrocardiogram data and phonocardiogram data.
According to a first aspect, it is presented a method for analysing heart data of a user. The method is performed in an analysis device and comprises the steps of: obtaining phonocardiogram data, representing audio data of activities of the heart, from a portable sensor device; obtaining electrocardiogram data, based on electrical signals measured by electrodes placed on the body of the user, from the portable sensor device, wherein the electrocardiogram data corresponds to the phonocardiogram data in time; dividing the phonocardiogram data in time segments based on cardiac cycles identified using at least one of the phonocardiogram data and the electrocardiogram data; dividing the electrocardiogram data in time segments corresponding to the time segments of the phonocardiogram data; and determining whether the heart is considered to need further examination or not based on only time segments of the phonocardiogram data and the electrocardiogram data where the quality of the phonocardiogram data is greater than a threshold level and the quality of the electrocardiogram data is greater than a threshold level.
The step of dividing may comprise dividing the phonocardiogram data in time segments based on cardiac cycles identified using the electrocardiogram data.
Each cardiac cycle may be made up of a plurality of time segments.
The step of determining whether the heart is considered to need further examination or not may comprise the step of: calculating a composite of data in for corresponding time segments in the cardiac cycles.
The step of determining whether the heart is considered to need further examination or not may comprise: determining a time between a peak in the electrocardiogram data and a peak in the phonocardiogram data.
The method may further comprise the step of: adjusting a gain applied for the phonocardiogram data based on the electrocardiogram data.
The step of determining whether the heart is considered to need further examination or not may comprise the step of: deriving a plurality of frequency components of the phonocardiogram data.
The step of determining whether the heart is considered to need further examination or not may comprise the steps of: determining whether there is a signal greater than a threshold level in a particular frequency component of the phonocardiogram data; determining that the heart is considered to need further examination when there is no signal greater than the threshold level in the particular frequency component; and analysing signal levels in other frequency components when there a signal greater than the threshold level in the particular frequency component.
The method may further comprise the step of: transmitting a signal to a device of the user containing information of whether the heart is considered to need further examination or not.
According to a second aspect, it is presented an analysis device for analysing heart data of a user. The analysis device comprises: a processor; and a memory storing instructions that, when executed by the processor, cause the analysis device to: obtain phonocardiogram data, representing audio data of activities of the heart, from a portable sensor device; obtain electrocardiogram data, based on electrical signals measured by electrodes placed on the body of the user, from the portable sensor device, wherein the electrocardiogram data corresponds to the phonocardiogram data in time; divide the phonocardiogram data in time segments based on cardiac cycles identified using at least one of the phonocardiogram data and the electrocardiogram data; divide the electrocardiogram data in time segments corresponding to the time segments of the phonocardiogram data; and determine whether the heart is considered to need further examination or not based on only time segments of the phonocardiogram data and the electrocardiogram data where the quality of the phonocardiogram data is greater than a threshold level and the quality of the electrocardiogram data is to greater than a threshold level.
According to a third aspect, it is presented a computer program for analysing heart data of a user. The computer program comprises computer program code which, when run on an analysis device causes the analysis device to: obtain phonocardiogram data, representing audio data of activities of the heart, from a portable sensor device; obtain electrocardiogram data, based on electrical signals measured by electrodes placed on the body of the user, from the portable sensor device, wherein the electrocardiogram data corresponds to the phonocardiogram data in time; divide the phonocardiogram data in time segments based on cardiac cycles identified using at least one of the phonocardiogram data and the electrocardiogram data; divide the electrocardiogram data in time segments corresponding to the time segments of the phonocardiogram data; and determine whether the heart is considered to need further examination or not based on only time segments of the phonocardiogram data and the electrocardiogram data where the quality of the phonocardiogram data is greater than a threshold level and the quality of the electrocardiogram data is greater than a threshold level.
According to a fourth aspect, it is presented a computer program product comprising a computer program according to the third aspect and a computer readable means on which the computer program is stored.
Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to “a/an/the element, apparatus, component, means, step, etc.” are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.
The invention is now described, by way of example, with reference to the accompanying drawings, in which:
The invention will now be described more fully hereinafter with reference to the accompanying drawings, in which certain embodiments of the invention are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided by way of example so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Like numbers refer to like elements throughout the description.
Looking first to
The smartphone 7 is also connected to a wide area network 6, such as the Internet, e.g. via WiFi or a cellular network, to allow communication with an analysis device 1, here in the form of a server. The portable sensor device 2 captures ECG data and PCG data and sends this data, via the smartphone 7, to the analysis device 1. This allows the analysis device 1 to determine whether the heart of the user 5 can be considered to be in a normal state or whether the heart needs further examination based on the PCG data and the ECG data captured by the portable sensor device 2. Further investigation can be determined to be needed e.g. if any abnormal heart condition cannot be ruled out. It is to be noted that even if further investigation is to be performed, the heart can in fact be normal, i.e. non-pathological.
In
Alternatively, the analysis device can form part of the portable sensor device 2 (not shown). In such a case, the portable sensor 2 can also perform the functions of the smartphone 7.
In
Additionally, a transducer 8, e.g. in the form of a microphone, is provided to convert sound captured by the body into electric analogue PCG signals. The analogue PCG signals are converted to digital PCG signals using an A/D converter. The digital PCG signal is then sent to the analysis device for analysis together with the ECG signal
In
One measurement which can be used in the analysis of the ECG data and the PCG data is a time measurement 15 between a peak 12 in the ECG data and a peak 13 in the PCG data. The peak 12 in the ECG data is the peak in the QRS complex, representing the rapid depolarization of the right and left ventricles. The peak 13 in the PCG data is the sound of when valves are closed, which is the peak of the PCG data with the greatest amplitude.
The time measurement 15 can be expressed as a percentage of the average cardiac cycle. When this measurement 15 is excessive, this indicates an abnormal condition which should be investigated further.
Looking now to
It is to be noted that there can be any number of segments in a cardiac cycle and the segments can be provided at different sections than what is shown in
The memory 64 can be any combination of read and write memory (RAM) and read only memory (ROM). The memory 64 also comprises persistent storage, which, for example, can be any single one or combination of magnetic memory, optical memory, solid state memory or even remotely mounted memory.
A data memory 66 is also provided for reading and/or storing data during execution of software instructions in the processor 60. The data memory 66 can be any combination of read and write memory (RAM) and read only memory (ROM).
The analysis device 1 further comprises an I/O interface 62 for communicating with other external entities, such as the smartphone 7 of the user using Internet Protocol (IP) over the wide area network 6.
Other components of the analysis device are omitted in order not to obscure the concepts presented herein
In an obtain phonocardiogram data step 40, PCG data is obtained from a portable sensor device. As explained above, the PCG data represents audio data of activities of the heart. The PCG data can be the digital PCG signals described above. The phonocardiogram data can be received from the portable measurement device.
In an obtain electrocardiogram data step 42, ECG data is obtained from the portable sensor device. As explained above, the ECG data is based on electrical signals measured by electrodes placed on the body of the user. The ECG data corresponds to the PCG data in time. The ECG data can be the digital ECG data described above. The electrocardiogram data can be received from the portable measurement device.
In a segment phonocardiogram data step 44, the PCG data is divided in time segments based on cardiac cycles identified using at least one of the PCG data and the ECG data. Optionally, each cardiac cycle is made up of a plurality of time segments, as shown in
In a segment electrocardiogram data step 46, the ECG data is divided in time segments corresponding to the time segments of the PCG data. In other words, within a single cardiac cycle there are corresponding time segments in the ECG data and the PCG data.
In an optional adjust gain step 48, a gain applied for the PCG data is adjusted based on the ECG data. This allows the gain for the PCG data to be increased in sections when the PCG signal is expected to be low to capture details in the PCG signal. Also, the gain of the PCG data is then decreased in sections when the PCG signal is expected to be high to be able to capture the entire dynamic range of the signal. In other words, using the ECG data for the gain of the PCG data, both dynamic range and low level detail.
In a determine further examination need step 50, the analysis device determines whether the heart is considered to need further examination or not, based on only time segments of the PCG data and the ECG data where the quality of the PCG data is greater than a threshold level and the quality of the ECG data is greater than a threshold level. In other words, time segments where there is excessive interference or noise are discarded in the analysis. Particularly when combined with the optional composite calculation described below, the discarding of low quality segments increases overall signal quality, which can be applied for both PCG data and ECG data. Since interference can be short in duration, by discarding only time segments where there is low quality, other segments of the same cardiac cycle can be used and contribute to the analysis. The quality can e.g. be measured as a signal to noise ratio (SNR) or signal to noise and interference ratio (SINR), and the threshold level can be a specific numerical value of SNR or SINR. In one embodiment, the quality of ECG is quantified using a quality index. The quality index is based on identification of heart events, such as contractions, from the ECG data. Based on the identification, an ideal ECG signal is synthesised. The ECG data is then compared with the ideal ECG signal and its deviation is quantified, e.g. using RMS (Root Mean Square). The quantified deviation can thus function as a quality index. The quality of the PCH data can be quantified in an according way. In one embodiment, the quality is determined based on a set of quality criteria. Such quality criteria can include similarity between beats, likelihood of missed/extra detections, average rate and rhythm variability.
In an optional transmit result step 52, a signal is transmitted to a device of the user containing information of whether the heart is considered to need further examination or not. For instance, the signal can be transmitted to the smartphone of the user using IP over the wide area network. This allows the smartphone to display the result of the analysis to the user, indicating to the user whether the heart is considered to need further examination or whether the user should be investigated further to determine the user's heart condition.
Since the phonocardiogram data is more susceptible to noise than the electrocardiogram data, a better analysis is achieved by correlating the two types of data. This is particularly true when the data is captured using a portable sensor device, which might be used in a noisy environment. Moreover, the end user handling the portable sensor device may not be a trained medical professional, which may result in even more noise in the phonocardiogram data.
Looking now to
In an optional calculate average step 50a, a composite of data in corresponding time segments in the cardiac cycles is calculated. The composite can e.g. be calculated by averaging, by obtaining a median value or calculating a weighted average (where e.g. extremes are omitted). When this is performed over many samples, noise or interference in individual cardiac cycles are reduced in intensity. Moreover, corresponding time segments can be of different duration in different cardiac cycles as long as the correspondence of the time segments in the cardiac cycle is ensured. In this way, signals for several cardiac cycles can form base for the analysis even when there is an irregular heart rhythm. Corresponding time segments can be determined by matching signals of similar patterns (see e.g. segments 16a-c of
In an optional determine offset step 50b, a time between a peak in the ECG data and a peak in the PCG data is determined, as explained above for the time 15 with reference to
In an optional derive frequency components of phonocardiogram step 50c, a plurality of frequency components of the PCG data are derived. This can e.g. be done using fast Fourier transform (FFT) or wavelet analysis.
In an optional conditional signal in 1st frequency component step 50d, the analysis device determines whether there is a signal greater than a threshold level in a particular frequency component of the PCG data. For instance, a heart murmur are sounds of relatively high frequency. Optionally, the duration of the signal in the particular frequency must also be longer than a specified duration.
If a signal greater than the threshold level in a particular frequency component is determined, the method proceeds to an optional determine no further examination step 50f. Otherwise, the method proceeds to an optional analyse other frequency components step 50e. Optionally, if the signal in the particular frequency component is constant throughout the heart cycle, this is typically not of physiological origin and is interpreted as background noise, and the method proceeds to the determine no further examination step 50f. Alternatively, the constant frequency component can indicate a low quality of the time segment and whereby the time segment could be disregarded.
In the optional analyse other frequency components step 50e, signal levels in other frequency components are analysed when there a signal greater than the threshold level in the particular frequency component.
In the optional determine no further examination step 50f, the analysis device determines that the heart is considered to need further examination when there is no signal greater than the threshold level in the particular frequency component.
In an optional further examination or not step 50g, the analysis device determines whether the heart is considered to need further examination or not based on the previous steps.
The invention has mainly been described above with reference to a few embodiments. However, as is readily appreciated by a person skilled in the art, other embodiments than the ones disclosed above are equally possible within the scope of the invention, as defined by the appended patent claims.
Number | Date | Country | Kind |
---|---|---|---|
1750858-1 | Jun 2017 | SE | national |
Filing Document | Filing Date | Country | Kind |
---|---|---|---|
PCT/SE2018/050708 | 6/28/2018 | WO | 00 |