TWM530126U - Apparatus for examining and processing heartbeat signal based on fitting curve - Google Patents

Abstract

An apparatus for examining a heartbeat signal based on a fitting curve is provided. The apparatus includes an input/output unit and a processing unit. A heartbeat signal which has passed an average process is obtained by the input/output unit, and a characteristic wave is acquired from the heartbeat signal by the processing unit. A plurality of characteristic points of the characteristic wave are recognized by the processing unit. Based on the characteristic points, the characteristic wave is divided to a plurality of characteristic wave segments by the processing unit. Fitting is performed to the characteristic wave segments by the processing unit, so as to obtain a fitting curve. Based on the fitting curve, an evaluation parameter of the characteristic wave is calculated by the processing unit. Whether the heartbeat signal is an abnormal heartbeat signal is determined according to the evaluation parameter by the processing unit.

Description

Detection device for heartbeat signal based on fitting curve

The present invention relates to a detecting device, and more particularly to a detecting device based on a heartbeat signal of a fitting curve.

With the improvement of living standards, the prevention and detection of major diseases have gradually received the attention of modern people. Thanks to advances in technology, by measuring relevant physiological signals and analyzing them, early signs of many major diseases can be detected, and patients can receive treatment early to avoid deterioration.

Heart disease is one of the major diseases in modern society and is a common cause of sudden death. Most doctors use an electrocardiogram to determine whether a subject has heart disease. In the electrocardiogram, a complete heartbeat waveform represents the change in the potential of cardiomyocytes during a myocardial action cycle. In general, the physician can observe the subject's heartbeat waveform to determine if the subject is likely to have a heart disease or to determine if the subject is at high risk of developing a heart disease.

In recent years, many studies have shown that abnormal potentials in heartbeat signals are an important indicator for assessing the risk of arrhythmia and can assist in the diagnosis of Acute Myocardial Ischemia, Myocardial Infraction, Patients with heart disease such as Left Ventricular Hypertrophy, Ventricular Arrhythmia, Ventricular Tachycardia, or high-risk groups.

However, the abnormal potential in the aforementioned heartbeat signal usually has a small amplitude and is therefore difficult to perceive through the naked eye. Corresponding to this, how to correctly detect the aforementioned abnormal potential from the heartbeat signal is still one of the goals of those skilled in the art.

The present invention provides a heartbeat signal detecting device, which can effectively detect an abnormal potential in a heartbeat signal, and thereby determine whether the heartbeat signal is abnormal.

The embodiment of the present invention provides a detecting device for a heartbeat signal. The detecting device includes an input and output unit and a processing unit. The input and output unit is used to obtain an averaged heartbeat signal. The processing unit is coupled to the input and output unit. The processing unit extracts the characteristic wave from the heartbeat signal, and identifies a plurality of feature points of the characteristic wave, thereby distinguishing the characteristic wave into the plurality of characteristic wave segments based on the foregoing feature points. The processing unit fits the characteristic wave segment to obtain a fitting curve of the corresponding characteristic wave, and calculates an evaluation parameter based on the fitting curve. The aforementioned evaluation parameters are reflected in the special potential of the characteristic wave. The processing unit determines whether the heartbeat signal is an abnormal heartbeat signal by the evaluation parameter.

Based on the above, the detecting device for the heartbeat signal provided by the embodiment of the present application identifies the characteristic wave and the plurality of feature points from the heartbeat signal provided by the averaged heartbeat signal or the average signal electrocardiograph to distinguish the characteristic wave into multiple The characteristic wave segments are then fitted to the characteristic wave segments to finally obtain a fitting curve of the corresponding characteristic waves. The evaluation parameters are further calculated based on the aforementioned fitting curve. The aforementioned evaluation parameters may reflect an abnormal potential among the characteristic waves. Finally, the evaluation parameter determines whether the heartbeat signal is an abnormal heartbeat signal. Therefore, the detection device of the heartbeat signal provided by the embodiment of the present invention can effectively detect and utilize the abnormal potential in the heartbeat signal, thereby accurately determining whether the heartbeat signal is abnormal.

The above described features and advantages of the present invention will be more apparent from the following description.

Reference will now be made in detail to the exemplary embodiments embodiments In addition, wherever possible, elements and components in the drawings and the embodiments may have the same or similar parts.

In the detection device of the heartbeat signal provided by the new embodiment, the main detection object is a special potential in the heartbeat signal, especially a special potential in the QRS complex in the heartbeat signal. Figure 1 is a schematic diagram showing an ideal complete heartbeat waveform. Referring to FIG. 1, in general, in a heartbeat signal, a complete heartbeat waveform includes a P wave, a QRS complex, and a T wave. The QRS complex is a group of waves formed by Q waves, R waves, and S waves. The P wave, the QRS complex, and the T wave correspond to the atrial depolarization period, the ventricular depolarization phase, and the ventricular repolarization phase, respectively, during the heartbeat cycle. The aforementioned special potential is the Abnormal Intra-QRS Potential (AIQP) inside the QRS complex. In general, the abnormal potential inside the QRS complex has a smaller vibration and a higher frequency than the QRS complex, and thus is not easily detected by the naked eye.

2 is a schematic diagram of a device for detecting a heartbeat signal according to an embodiment of the present invention. Referring to FIG. 2, the detecting apparatus 100 includes at least an input and output unit 120 and a processing unit 140. The input/output unit 120 serves as a signal transmission interface between the detecting device 100 and an external device, and is, for example, supporting an Ethernet standard, a Bluetooth communication standard, a ZIGBEE communication standard, and a Wi-Fi communication standard. The communication interface of the communication standard and the wireless communication standard, or the connection interface compatible with the Serial Advanced Technology Attachment (SATA) standard, the Universal Serial Bus (USB) standard or other suitable standards.

The processing unit 140 can be any type of control circuit, such as a system-on-chip (SOC), an application processor, a media processor, a microprocessor, a central processing unit. (central processing unit, CPU), digital signal processor or the like.

It should be noted that in another embodiment of the present invention, the detecting device 100 may further include components such as a display, a speaker, a storage unit, and the like, but is not limited thereto. The detecting device 100 is realized by, for example, an electronic device such as a common desktop computer, a notebook computer, a smart mobile device, a tablet, or a personal digital assistant (PDA), but the present invention is not limited thereto. .

3 is a flow chart of a method for detecting a heartbeat signal according to the description of the present application. The detecting method shown in FIG. 3 can be performed by the detecting device 100 shown in FIG. 2, but the present invention is not limited thereto. Referring to FIG. 2 and FIG. 3, in the present embodiment, the detecting device 100 obtains the averaged heartbeat signal by its input/output unit 120 (step S310). The heartbeat signal includes a plurality of data points, the unit of which is, for example, microvolts (μV). Here, the detecting device 100 receives the heartbeat signal directly from the average signal electrocardiograph, for example, by the input/output unit 120, but the present invention is not limited thereto.

In another embodiment, the detecting device 100 performs an averaging process to obtain a heartbeat signal. In detail, the detecting device 100 receives a plurality of heartbeat signals (previous heartbeat signals) from a high-resolution electrocardiograph or other type of electrocardiograph, for example, by the input-output unit 120, and then the heartbeat signal (previous heartbeat) is processed by the processing unit 140. Signal) Align and average to get the sample heartbeat signal. Then, the processing unit 140 selects a similar person from the subsequently received heartbeat signal (current heartbeat signal) according to the template heartbeat signal as an implementation object of the detection method. Specifically, when the correlation coefficient of the subsequently received heartbeat signal (current heartbeat signal) and the sample heartbeat signal is greater than a threshold, the heartbeat signal (current heartbeat signal) is regarded as a heartbeat signal that can be detected. The aforementioned threshold is, for example, 0.98. It is worth noting that the sample heartbeat signal can also be updated based on the heartbeat signal that can be detected.

Specifically, the heartbeat signal received by the average signal electrocardiograph and the heartbeat signal obtained by performing the averaging process have lower random noise to avoid the random noise affecting detection method and whether the detecting device 100 is detecting whether the heartbeat signal is detected. The accuracy on the abnormal heartbeat signal.

Referring back to FIG. 2 and FIG. 3, in the embodiment, after the heartbeat signal is obtained (step S310), the processing unit 140 further extracts the feature wave from the heartbeat signal (step S320). Here, the characteristic wave is the aforementioned QRS complex and includes a plurality of data points. Briefly, the processing unit 140 can identify the QRS complex by the signal strength of the heartbeat signal on the time axis, and search for the start and end points (Offset) of the QRS complex forward and backward from the strongest signal of the heartbeat signal. . In an embodiment of the present invention, the processing unit 140 may perform a band-pass filtering process on the heartbeat signal before extracting the feature wavefront. The cutoff frequency of the band pass filtering process is set, for example, between 150 Hz (Hertz, Hz) and 250 Hz.

Referring to FIG. 2 and FIG. 3, after extracting the feature wave (step S320), in the embodiment, the processing unit 140 identifies a plurality of feature points of the feature wave (step S330), and distinguishes the feature wave based on the feature point. Feature wave segments (step S340). Referring to Figure 1, the QRS complex is composed of Q waves, R waves, and S waves. The Q wave is the first reverse wave after the QRS start point (Onset), and the S wave is the first reverse wave after the R wave. The peaks of the Q wave, the R wave, and the S wave are q point, r point, and s point, respectively. In general, r is the peak of the largest positive amplitude in the QRS complex, and q and s are the peaks with negative amplitude in the QRS complex, respectively.

The processing unit 140 is, for example, a data point in a characteristic wave such as an onset of a QRS complex, an end point of an QRS complex, an offset, a q point, an r point, and an s point, and then distinguishes the feature wave into a QRS. The characteristic wave segment such as the start point (Onset) of the wave group to q point, q point to r point, r point to s point, and s point to the end point (Offset) of the QRS complex. Specifically, the purpose of distinguishing a characteristic wave into a plurality of characteristic wave segments is that the characteristic waves can be curve-fitted in stages to avoid large amplitude and steep Q waves, R waves, and S waves affecting the QRS complex. Detection of internal abnormal potential (AIQP).

Referring to FIG. 2 and FIG. 3, in the embodiment, the processing unit 140 performs fitting on the feature wave segment to obtain a fitting curve of the corresponding feature wave (step S350). The processing unit 140 performs curve fitting on each of the characteristic wave segments with a polynomial function and a minimum error square, and integrates the fitting curve segments corresponding to the respective characteristic wave segments, thereby obtaining a fitting curve corresponding to the entire characteristic wave. Specifically, assuming that any of the characteristic wave segments is u(n) and n is a discrete time variable, the m- th order polynomial function û(n) designed to approximate u(n) is as follows. û(n)=a ₀ + a ₁ n + a ₂ n ² +...+a _m n ^m ...... (1)

It is worth noting that n and m are positive integers, and a ₀ , a ₁ , a ₂ , ..., a _m are coefficients of the m- th order polynomial function û(n) . The m- th order polynomial function û(n) is taken as the fitting curve segment corresponding to the characteristic wave segment u(n) , and the fitting error e(n) is as follows. e(n)= u(n) - û(n) ...... (2)

By making the sum of the squares of the fitting error e(n) the objective function X and making the objective function X reach the minimum value, a coefficient combination a ₀ , a of a set of optimal m- order polynomial functions û(n) can be obtained. ₁ , a ₂ , ..., a _m .

Referring to FIG. 2 and FIG. 3, in the present embodiment, after obtaining the fitting curve and the associated fitting error, the processing unit 140 calculates the evaluation parameter based on the fitting curve (step S360). In detail, after the processing unit 140 calculates the fitting error between the fitting curve and the characteristic wave, the ratio between the root mean square value of the fitting error and the root mean square value of the characteristic wave is calculated to obtain the evaluation parameter.

In more detail, the portion of the characteristic wave that cannot be fitted by the fitting curve may include an abnormal potential (AIQP) inside the QRS complex. Therefore, the potential parameter AIQP_L related to the abnormal potential (AIQP) can be obtained based on the fitting error e(n) as shown below.

It is worth noting that n ₁ and n ₂ are positive integers, the fitting error e(n) is the error between the fitted curve and the characteristic wave, and QRSD is the interval length of the QRS complex. On the other hand, considering the influence of the total energy of the QRS complex on the abnormal potential (AIQP), the processing unit 140 further defines that the ratio between the potential parameter AIQP_L corresponding to the root mean square value of the QRS complex is the evaluation parameter AQR , which As follows.

It is worth noting that s(n) is a characteristic wave (QRS complex). In other words, the evaluation parameter AQR is the ratio between the root mean square value of the fitting error and the root mean square value of the characteristic wave. After the evaluation parameter AQR is obtained, the processing unit 140 further determines whether the heartbeat signal is an abnormal heartbeat signal by the evaluation parameter AQR (step S370). The evaluation parameter AQR can reflect whether the QRS complex contains an abnormal potential (AIQP, a special potential).

In an embodiment of the present invention, the processing unit 140 compares the evaluation parameter AQR with a threshold value, and when the evaluation parameter AQR is greater than the threshold value, determines that the heartbeat signal is an abnormal heartbeat signal. Otherwise, the processing unit 140 determines that the heartbeat signal is a non-abnormal heartbeat signal. In general, the evaluation parameter AQR obtained from the abnormal heartbeat signal is larger than the evaluation parameter AQR obtained by the non-abnormal heartbeat signal. Thus, by evaluating the plurality of statistical parameters AQR abnormal beat signal and the acquired evaluation parameters of a non-AQR plurality of signals acquired abnormal heartbeats, pre-processing unit 140 may obtain the appropriate threshold.

4A-4C are schematic diagrams showing the process of detecting a non-abnormal heartbeat signal. 4A-4C, FIG. 4A is a non-abnormal heartbeat signal, and FIG. 4B is a fitting curve obtained by fitting the QRS complex of the heartbeat signal of FIG. 4A. It should be noted that the curve segment L ₁ , the curve segment L ₂ , the curve segment L _{3 ,} and the curve segment L ₄ are respectively fitting curve segments obtained after fitting the respective characteristic wave segments. It should be noted that in order to show the difference between the heartbeat signal and the fitting curve, FIG. 4B shows the heartbeat signal in a thicker line segment. Finally, FIG. 4C illustrates the fitting error between each characteristic wave segment and each of the fitted curve segments L ₁ , L ₂ , L _{3 ,} and L ₄ .

5A-5C are schematic diagrams showing the process of detecting an abnormal heartbeat signal. Referring to Figures 5A-5C, Figure 5A is an abnormal heartbeat signal containing an abnormal potential (AIQP) within the QRS complex. 5B is a fitting curve obtained by fitting the QRS complex of the heartbeat signal of FIG. 5A, and FIG. 5C is a diagram showing the relationship between each characteristic wave segment and each of the fitting curve segments L ₂ , L _{3 ,} and L ₄ . Fit error. It should be noted that in order to show the difference between the heartbeat signal and the fitted curve, FIG. 5B shows the heartbeat signal in a thicker line segment.

In one embodiment of the present invention, the potential parameter AIQP_L obtained from the heartbeat signal of FIG. 4A is 8.8 microvolts (μV), and the evaluation parameter AQR is 1.9%. On the other hand, the potential parameter AIQP_L obtained from the heartbeat signal of FIG. 5A is 12.0 microvolts (μV), and the evaluation parameter AQR is 4.6%. In other words, the evaluation parameter AQR can clearly reflect whether any heartbeat signal contains an abnormal potential (AIQP) inside the QRS complex and is an abnormal heartbeat signal.

In an embodiment of the present invention, in addition to the potential parameter AIQP_L and the evaluation parameter AQR , the processing unit 140 of the detecting device 100 can also determine by detecting the Ventricular Delay Potentials (VLP) in the QRS group. Whether the heartbeat signal is an abnormal heartbeat signal. In general, when a ventricular delay potential occurs in a QRS complex, the heartbeat signal can be considered an abnormal heartbeat signal. Specifically, the processing unit 140 can determine whether the heartbeat signal is an abnormal heartbeat signal by using a Linear Discriminant Method in combination with the ventricular delay potential, the potential parameter AIQP_L, and the correlation data of the evaluation parameter AQR .

It should be noted that the detection method mentioned in the foregoing embodiment is mainly applicable to detecting the heartbeat signal received by the average signal electrocardiograph and the heartbeat signal obtained after performing the averaging process. However, when the heartbeat signal (current heartbeat signal) received by the input/output unit 120 of the detecting device 100 is an unprocessed heartbeat signal, the heartbeat signal may have a large random error, which is less suitable for adoption. The evaluation parameters obtained based on the combined fitting error are used to determine whether the heartbeat signal is an abnormal heartbeat signal.

Relatively speaking, fitting the unprocessed heartbeat signal can achieve the effect of reducing random errors. Therefore, in an embodiment of the present invention, the processing unit 140 extracts the QRS complex (feature wave) from the heartbeat signal, and after segmentation fitting the QRS complex, the finally obtained fitting curve is filtering the random error. QRS complex. At this time, the fitting error is more difficult to accurately reflect the abnormal potential (AIQP, that is, the special potential) in the QRS complex, but the fitting curve can be regarded as the heartbeat signal after the noise is removed.

FIG. 6 is a flowchart of a method for processing a heartbeat signal according to an illustrative example of the present application. The foregoing processing method is applied to the detecting device 100 shown in FIG. 2, but the present invention is not limited thereto. In general, an electronic device having computing power and capable of receiving a heartbeat signal can perform the processing method of the heartbeat signal. Referring to Fig. 6, in the present embodiment, the heartbeat signal that has not been averaged is first acquired (step S610). Then, the feature wave is extracted from the unprocessed heartbeat signal (step S620), and then a plurality of feature points of the feature wave are identified (step S630), and based on the feature point, the feature wave is distinguished into a plurality of feature wave segments ( Step S640).

The aforementioned characteristic wave is a QRS complex, and the aforementioned feature points are an onset of the QRS complex, an end point of the QRS complex (Offset), a Q wave crest (q point), an R wave crest (r point), and S. Wave peak (s point). Thereafter, each of the characteristic wave segments is fitted to obtain a fitting curve of the corresponding characteristic wave (step S650). In this embodiment, the fitting curve is a heartbeat signal that reduces the random error and smoothed, and other analysis methods or detection methods can be used to analyze or detect the fitting curve.

In summary, the detecting device for the heartbeat signal provided by the novel embodiment identifies the characteristic wave and the plurality of feature points from the heartbeat signal provided by the averaged heartbeat signal or the average signal electrocardiograph to distinguish the characteristic wave as A plurality of characteristic wave segments are then fitted to the characteristic wave segments to finally obtain a fitting curve of the corresponding characteristic waves. The evaluation parameters are further calculated based on the aforementioned fitting curve. The aforementioned evaluation parameters may reflect an abnormal potential among the characteristic waves. Finally, the evaluation parameter determines whether the heartbeat signal is an abnormal heartbeat signal. Therefore, the detection device of the heartbeat signal provided by the embodiment of the present invention can effectively detect and utilize the abnormal potential in the heartbeat signal, thereby accurately determining whether the heartbeat signal is abnormal.

Although the present invention has been disclosed in the above embodiments, it is not intended to limit the present invention, and any person skilled in the art can make some changes and refinements without departing from the spirit and scope of the present invention. The scope of the present invention is defined by the scope of the appended claims.

100‧‧‧Detection device
120‧‧‧Input and output unit
140‧‧‧Processing unit
P‧‧‧P wave
Q‧‧‧Q wave
R‧‧‧R wave
S‧‧‧S wave
T‧‧‧T wave
The peak of the q‧‧‧Q wave
r‧‧‧R wave crest
The peak of the s‧‧‧S wave
The starting point of the Onset‧‧‧QRS wave group
The end point of the Offset‧‧‧QRS complex
L ₁ , L ₂ , L ₃ , L ₄ ‧‧‧Fitting curve section
Steps for detecting the heartbeat signal of S310, S320, S330, S340, S350, S360, S370‧‧
Steps for processing S610, S620, S630, S640, S650‧‧ ‧ heartbeat signals

Figure 1 is a schematic diagram showing an ideal complete heartbeat waveform. 2 is a schematic diagram of a device for detecting a heartbeat signal according to an embodiment of the present invention. 3 is a flow chart of a method for detecting a heartbeat signal according to the description of the present application. 4A-4C are schematic diagrams showing the process of detecting a non-abnormal heartbeat signal. 5A-5C are schematic diagrams showing the process of detecting an abnormal heartbeat signal. FIG. 6 is a flow chart of a method for processing a heartbeat signal according to the description of the present application.

100‧‧‧Detection device

120‧‧‧Input and output unit

140‧‧‧Processing unit

Claims (4)

A heartbeat signal detecting device, comprising: an input and output unit, configured to obtain an averaged heartbeat signal; and a processing unit coupled to the input and output unit, wherein the processing unit extracts a characteristic wave from the heartbeat signal, and identifies the The plurality of feature points of the characteristic wave are used to distinguish the feature wave into a plurality of feature wave segments based on the feature points, and the processing unit fits the feature wave segments to obtain a fitting curve corresponding to the characteristic wave And calculating an evaluation parameter based on the fitting curve, wherein the evaluation parameter is responsive to a special potential of the characteristic wave, and the processing unit determines, by the evaluation parameter, whether the heartbeat signal is an abnormal heartbeat signal. The detecting device of claim 1, wherein the input/output unit obtains a plurality of previous heartbeat signals, and the processing unit averages the previous heartbeat signals to obtain a template heartbeat signal, and according to the template heartbeat The signal is selected by the current heartbeat signal received. The detecting device of claim 1, wherein the processing unit calculates a plurality of fitting errors between the fitting curve and the characteristic wave, and calculates a root mean square value of the fitting errors and the characteristic wave The ratio between the root mean square values to obtain the evaluation parameters. The detecting device of claim 1, wherein the processing unit compares the evaluation parameter with a threshold value, and when the evaluation parameter is greater than the threshold value, determining that the heartbeat signal is the abnormal heartbeat signal.