Wearable electrocardiogram detection system and R-wave detection method thereof

Abstract

The invention relates to the technical field of electrocardiosignal detection, and discloses a wearable electrocardiosignal detection system, which mainly comprises the following components: an elastic waistband which is used as a substrate layer, has uniform elasticity, softness and air permeability, can be tightly attached to the waist curve of a human body, has good biocompatibility, and can adjust the waistline to adapt to users with different body types; the conductive cloth serves as a conductive layer main body; the insulating cloth covers the outer side of the conductive layer, has wear resistance, water resistance and flexibility, and can shield external electromagnetic interference and prevent sweat from corroding the conductive layer; and the conductive sponge is embedded in the contact area of the conductive layer and the skin, so that the fitness of the device and the human skin is enhanced, and stable signal acquisition is guaranteed. According to the method, the R wave in the electrocardiogram can be accurately detected through operations such as filtering and expansion corrosion in the preprocessing stage and a self-adaptive threshold updating mechanism, the non-linear and non-stationary characteristics of the electrocardiosignal are effectively handled, the accuracy and reliability of R wave detection are improved, and the method is suitable for long-term and continuous electrocardiogram monitoring in daily life.

Description

Technical Field

[0001] The present invention relates to the technical field of electrocardiogram (ECG) signal detection, and in particular to a wearable ECG detection system and an R-wave detection method thereof. Background Art

[0002] In today's era of rapid technological advancement, people's demand for health management is growing, and ECG monitoring technology is also ushering in a trend of convenience and daily use. However, while traditional hospital ECG monitoring equipment performs well in terms of detection accuracy, it has many inconveniences in actual use. On the one hand, its monitoring time is strictly limited, and patients often need to lie still in bed for a long time. This not only brings great inconvenience to patients, but may also result in the monitoring data not fully reflecting the patient's ECG changes during daily activities. On the other hand, traditional equipment is usually bulky and lacks portability, which greatly limits the patient's free range of movement. These limitations make it difficult for traditional ECG monitoring equipment to meet patients' needs for long-term, continuous ECG monitoring in daily life.

[0003] Against this backdrop, wearable ECG monitoring systems are gradually emerging. Their core advantage lies in enabling users to easily monitor their ECG in daily life, greatly improving their convenience. However, current wearable ECG monitoring systems on the market still face several pressing challenges. Some products lack comfort. For example, some devices lack a good fit, leading to shifting or loosening during user activity. This can not only cause discomfort but also compromise the stability and accuracy of the monitoring signal. Furthermore, some existing systems lack robustness during signal acquisition, making them susceptible to external interference, resulting in signal degradation and impacting subsequent ECG analysis results. Furthermore, the algorithm complexity within ECG monitoring systems has a crucial impact on system performance and application scope. Currently, many ECG monitoring systems utilize complex algorithms to improve detection accuracy, but these algorithms often require significant computing resources, placing significant pressure on hardware costs and power consumption. Especially for resource-constrained wearable devices, complex algorithms can lead to slow operation, reduced battery life, and even compromise the real-time and accuracy of detection. Therefore, in order to enable the wearable ECG detection system to be better applied in daily life, it is particularly important to develop a system that can not only ensure detection accuracy but also have a simple and efficient algorithm. Summary of the Invention

[0004] (1) Technical problems solved

[0005] In response to the shortcomings of the existing technology, the present invention provides a wearable electrocardiogram detection system and its R-wave detection method, which solves the problem of the above-mentioned background technology that "some devices have poor fit, which leads to displacement or loosening during user activities, which may not only cause wearing discomfort, but also affect the stability and accuracy of the monitoring signal."

[0006] (2) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A wearable electrocardiogram detection system mainly consists of the following components:

[0008] Elastic waistband: As the base layer, it has uniform elasticity and soft breathability, can closely fit the waist curve of the human body, and has good biocompatibility. The waist circumference can be adjusted to suit users of different body shapes;

[0009] Conductive cloth: serves as the main body of the conductive layer;

[0010] Insulating cloth: Covering the outside of the conductive layer, it is wear-resistant, waterproof and flexible, can shield external electromagnetic interference, and prevent sweat from corroding the conductive layer;

[0011] Conductive sponge: embedded in the contact area between the conductive layer and the skin, it enhances the fit between the device and the human skin and ensures stable signal acquisition;

[0012] Electrode assembly: This includes a male buckle and a bottom buckle, which are used to connect to hardware devices to further process and transmit ECG signals. The electrode assembly also includes electrode buckle 1, electrode buckle 2, and electrode buckle 3. The electrode assembly is connected to the conductive cloth and conductive sponge to ensure accurate transmission of ECG signals.

[0013] Hardware device: It consists of a front-end acquisition module, a main control processing module, a data storage module, a Bluetooth module and a power management module, and is responsible for the acquisition, processing, storage and transmission of ECG signals.

[0014] In terms of the production steps, the present invention describes in detail the cutting, punching and fixing methods of the elastic belt, conductive cloth, insulating cloth and conductive sponge to ensure the stability of the device and the quality of signal acquisition.

[0015] During the signal processing, the R-wave detection method of the present invention mainly includes the following steps:

[0016] Preprocessing stage: The ECG signal is filtered through a sliding filter to remove high-frequency noise. The filtered signal is divided into two branches, and expansion-after-erosion and corrosion-after-expansion operations are performed respectively. The two branches are then subtracted to remove low-frequency interference components in the ECG signal, enhance the R wave, and convert negative features into positive ones. A sliding maximum filter is used to merge the features of the R wave and the P wave to reduce the difficulty of subsequent R wave recognition.

[0017] Threshold decision stage: When entering the process for the first time, a 10-second segment is selected from the signal and divided into 10 sub-segments. The difference between the maximum and minimum values ​​of each sub-segment is calculated. After eliminating the maximum difference and the minimum difference, the sum is divided by 8 to obtain the initial threshold. The final threshold is then calculated using the formula to determine whether the signal amplitude of the current sampling point is greater than the amplitude of the previous sampling point, and whether it continues to be the maximum value in the sliding window and the duration reaches the width of the sliding window. If the conditions are met, it is determined to be a peak and recorded. Based on the relationship between the peak value and the current threshold, it is determined whether it is an R wave, and the threshold is updated accordingly to adapt to the dynamic changes of the signal. When determining the R wave in the electrocardiogram, the current RR interval is calculated and compared with one-third of the previous RR interval average to avoid tall T waves or noise interference.

[0018] (3) Beneficial effects

[0019] The present invention provides a wearable electrocardiogram (ECG) detection system and an R-wave detection method thereof. The system has the following beneficial effects:

[0020] (1) When the wearable ECG detection system and its R-wave detection method are in use, the nonlinear and non-stationary characteristics of the ECG signal are effectively dealt with through operations such as filtering, expansion and corrosion in the preprocessing stage and the adaptive threshold update mechanism in the threshold decision stage, thereby improving the accuracy and reliability of R-wave detection. In terms of signal processing, the R-wave in the ECG can be accurately detected through operations such as filtering, expansion and corrosion in the preprocessing stage and the adaptive threshold update mechanism, effectively dealing with the nonlinear and non-stationary characteristics of the ECG signal, improving the accuracy and reliability of R-wave detection, and being suitable for long-term and continuous ECG monitoring in daily life.

[0021] (2) When the wearable ECG detection system and its R-wave detection method are in use, the design of components such as the elastic waistband and the conductive sponge ensures that the device is soft, breathable, fits comfortably, and has good biocompatibility, thus avoiding irritation or allergies to the skin. In addition, the use of insulating cloth can effectively shield external electromagnetic interference, prevent sweat from corroding the conductive layer, and extend the service life of the device. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a schematic diagram of wearing the central electrical signal monitoring belt of the present invention;

[0023] Figure 2 This is a schematic diagram of the stacked structure of the central electrical signal monitoring belt of the present invention;

[0024] Figure 3 This is a front view of the central electrical signal monitoring belt of the present invention;

[0025] Figure 4This is a schematic diagram of the reverse side of the central electrical signal monitoring belt of the present invention;

[0026] Figure 5 Schematic diagram of the pretreatment effect in the present invention;

[0027] Figure 6 This is a schematic diagram of the baseline drift R-wave recognition effect in the present invention;

[0028] Figure 7 This is a schematic diagram of the effect of identifying changes in the heart rhythm in the present invention;

[0029] Figure 8 This is a schematic diagram of the negative R wave identification effect of the present invention;

[0030] Figure 9 This is a schematic diagram of the myoelectric interference R-wave recognition effect in the present invention;

[0031] Figure 10 Schematic diagram of the algorithm flow in the present invention.

[0032] In the figure: 1. Elastic belt; 2. Conductive cloth; 3. Insulating cloth; 4. Conductive sponge; 5. Electrode assembly; 51. Electrode buckle 1; 52. Electrode buckle 2; 53. Electrode buckle 3; 6. Hardware device. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0034] See also Figures 1-10 The present invention provides a wearable electrocardiogram detection system, comprising:

[0035] Elastic waistband 1: Serving as the base layer of the device, it possesses uniform elasticity, closely conforming to the waist curve of the human body. It is soft and breathable, ensuring wearer comfort. Its excellent biocompatibility prevents skin irritation or allergies. The elastic waistband is also adjustable to accommodate users of different body types, enhancing the device's versatility.

[0036] Conductive cloth 2: As the main body of the conductive layer, it is responsible for signal transmission.

[0037] Insulating cloth 3: Covering the outside of the conductive layer, it is wear-resistant, waterproof and flexible. It can effectively shield external electromagnetic interference, prevent sweat from corroding the conductive layer, extend the service life of the device, and provide protection for the normal operation of the device.

[0038] Conductive sponge 4: Embedded in the contact area between the conductive layer and the skin, its soft texture enhances the fit between the device and human skin. Even if the device deforms during human movement, it can maintain good contact, ensuring stable signal acquisition and improving signal acquisition quality.

[0039] Electrode assembly 5: includes a male buckle and a bottom buckle, which can be fastened and fixed on the conductive cloth 2, and is used to connect the hardware device 6 to realize further processing and transmission of the ECG signal. It is a key link in the signal transmission chain. Specifically, the electrode assembly 5 also includes electrode buckle 1 51, electrode buckle 2 52, and electrode buckle 3 53. The electrode assembly 5 is connected to the conductive cloth 2 and the conductive sponge 4 to ensure the accurate transmission of the ECG signal.

[0040] Hardware device 6: It is mainly composed of a front-end acquisition module, a main control processing module, a data storage module, a Bluetooth module and a power management module. The front-end acquisition module accurately collects high-quality ECG signals through differential amplification and right leg drive common-mode suppression technology; the main control processing module integrates signal digitization, real-time filtering and task scheduling, and efficiently processes the collected signals; the data storage module supports data recording and playback functions; the Bluetooth module realizes wireless data transmission, supports real-time interaction with smart terminal devices, and ensures that data can be transmitted to the terminal device in a timely manner. The power management module provides a stable and reliable power supply for the entire hardware platform to ensure that the system can work continuously.

[0041] Further, the production steps are as follows:

[0042] Punch three holes, each 2-3 mm in diameter, into an elastic waistband (1) with a width of 5-10 cm and adjustable length. These holes are used to place electrode buckle 1 51, electrode buckle 2 52, and electrode buckle 3 53, respectively. Electrode buckle 1 51 and electrode buckle 53 are located on the same horizontal line, 4-5 cm apart, and electrode buckle 2 52 is located on the perpendicular bisector of the line connecting electrode buckle 1 51 and electrode buckle 3 53. Cut a piece of conductive fabric (2) with a width of 2-3 cm. Punch holes, each 2-3 mm in diameter, at points corresponding to the holes punched in the elastic waistband (1). Then, insert the male buckle of the electrode assembly (5) through the holes and snap it into place with the bottom buckle, firmly securing it to the conductive fabric (2) and ensuring a stable connection between the electrode assembly (5) and the conductive fabric. Use a needle-punching technique to tightly fit the conductive fabric (2) to the elastic waistband (1), ensuring a secure, wrinkle-free, and flat surface. Cut a piece of insulating fabric (3) with a width of 5-10 cm to completely cover the elastic waistband (1) and the conductive fabric (2). Also use a needle-punching technique to secure it to form a complete protective layer. Finally, cut a 2-3 cm wide piece of conductive sponge 4. Fold the excess conductive fabric 2 back onto the insulating fabric 3, leaving a 2-4 cm length. The conductive sponge 4 is then placed over the top, making it softer and more comfortable against the skin while stabilizing signal acquisition, improving both wearing comfort and signal acquisition quality. The thickness of the conductive sponge is 2-6 mm, ensuring good elasticity without affecting signal transmission.

[0043] The present invention also provides an R-wave detection method for a wearable electrocardiogram detection system. Specifically, with respect to signal processing, the present invention provides the following steps:

[0044] 1. Preprocessing stage

[0045] For the ECG signal x(n) (such as Figure 5 (a) shows that the QRS wave is the part with the most concentrated energy in a single heartbeat. In order to highlight the key features of the ECG signal, the signal is first preprocessed. The first step of preprocessing is to filter the ECG signal through a traditional sliding filter to remove high-frequency noise and obtain the filtered ECG signal y0(n), as shown in Figure 5 (b) shown.

[0046] Next, the filtered signal is divided into two branches: one branch is first dilated and then eroded; the other branch is first eroded and then dilated. Finally, the two results are subtracted. The relevant formula is as follows:

[0047]

[0048] Among them, ⊕ represents the expansion operation, represents the corrosion operation, f(n) is the signal sequence, k(m) is the structure element, n = 0, 1, ..., N-1, m = 0, 1, ..., M-1, and N>M.

[0049] The formula for the expansion operation is:

[0050]

[0051] The formula for the corrosion operation is:

[0052]

[0053] In order to extract the low-frequency interference components in the ECG signal, a linear structural element is specially selected for filtering. When the duration of the characteristic wave in the signal is shorter than the set scale of the structural element, the characteristic wave will be filtered out; on the contrary, if the duration of the characteristic wave exceeds the scale parameter of the structural element, it can be retained. The width of the R wave in the ECG signal is generally between 0.06 and 0.1s. Therefore, setting the width of the structural element to 0.1s can effectively remove the low-frequency noise in the ECG signal, enhance the R wave, and convert the negative features into positive ones. Figure 5 (c) shown.

[0054] Since the enhancement of R waves will also lead to the enhancement of P waves, a sliding maximum filter is designed to merge the features of R waves and P waves, thereby reducing the difficulty of subsequent R wave identification. The formula of the sliding maximum filter is as follows:

[0055]

[0056] In order to better adapt to abnormal situations, the window width W of the sliding maximum filter is set to the PR interval of the reference ECG signal (0.12~0.2s). To ensure the coverage of the normal PR interval and adapt to abnormal situations, the window width is set to 0.25s. The processed signal is as follows Figure 5 (d) shown.

[0057] 2. Threshold Decision Stage

[0058] First, we need to calculate the threshold. When calculating the initial threshold th_r, we first need to determine whether it is the first time to enter the process. If it is the first time to enter, select a 10s segment from the signal y(n) and divide it into 10 sub-segments. The time window corresponding to each sub-segment can be determined by the formula:

[0059] W i =[(i-1)F s +1,iF s ]

[0060] Where Fs is the sampling frequency and i is the sub-segment number, ranging from 1 to 10.

[0061] For each sub-segment W i , calculate the difference between its maximum and minimum values ​​according to the formula, namely:

[0062]

[0063] Get the difference Δy of all 10 sub-segments i After that, remove the largest difference and the smallest difference. Then, sum the remaining differences and divide by 8 to get the initial threshold value according to the formula:

[0064]

[0065] The formula defines how the threshold th_n is calculated, namely:

[0066] th_n=0.2×th_r

[0067] The formula defines how the final threshold th is calculated:

[0068] th=0.5×(th_r-th_n)+th_n

[0069] Next, we determine the peak. During peak detection of ECG signals, two conditions must be met: first, the signal amplitude at the current sampling point must be greater than the amplitude at the previous sampling point; second, the amplitude must remain at the maximum value within the sliding window for a duration equal to the width of the sliding window. When both conditions are met, the point is considered a peak, and the peak amplitude is recorded as the variable peak.

[0070] The threshold needs to be updated later. During the R wave detection process of the ECG signal, when the peak value is identified, the threshold needs to be updated to adapt to the dynamic changes of the signal. The specific rules are as follows:

[0071] If the peak value peak is greater than th, the peak is determined to be an R wave. At this time, th_r is updated according to the following formula:

[0072] th_r=0.875×th_r+0.125×peak

[0073] If the peak value is less than th, the peak is determined not to be an R wave. At this time, th_n is updated according to the following formula:

[0074] th_n=0.875×th_n+0.125×peak

[0075] Then, th is updated using the formula th = 0.5 × (th_r - th_n) + th_n. This adaptive threshold update mechanism can effectively cope with the nonlinear and non-stationary characteristics of the ECG signal and improve the accuracy and reliability of R-wave detection.

[0076] Finally, when determining the R wave in the electrocardiogram, in order to avoid interference from tall T waves or noise, the following method can be used: calculate the current RR interval and compare it with one-third of the previous RR interval mean. If the current RR interval is less than this value, and the current peak is greater than the previous peak that has been identified as the R wave, it indicates that there is a possibility of misjudgment of the previous R wave determination. In this case, the current peak is used to overwrite the previous R wave determination result. If the current RR interval is greater than or equal to one-third of the mean, the current peak is directly used as the new R wave. The formula for calculating the mean RR interval is:

[0077]

[0078] Where RR1, RR2, ..., RR7 represent the previous 1 to 7 RR intervals.

[0079] IV. Experimental Verification

[0080] We used matlab2023 simulation software to perform R wave detection on the MIT-BIH standard ECG database and counted 47 ECG data (excluding ECG data No. 207) and calculated the final accuracy to be 99.67%. Figure 6 This is a typical baseline drift ECG signal. Figure 7 It is an electrocardiogram signal of heart rhythm changes. Figure 8 It is an electrocardiogram signal containing a negative R wave. Figure 9 It is an electrocardiogram signal interfered with by myoelectricity.

[0081] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. Wearable ECG detection system, characterized in that: include: The elastic waistband (1), as a base layer, has uniform elasticity and soft breathability, can closely fit the waist curve of the human body, has good biocompatibility, and can adjust the waist circumference to suit users of different body shapes; Conductive cloth (2), serving as the main body of the conductive layer; Insulating cloth (3), covering the outside of the conductive layer, is wear-resistant, waterproof and flexible, can shield external electromagnetic interference, and prevent sweat from corroding the conductive layer; Conductive sponge (4), embedded in the area where the conductive layer contacts the skin, enhances the fit between the device and the human skin and ensures stable signal acquisition; The electrode assembly (5) comprises a male buckle and a bottom buckle, and is used to connect to a hardware device (6) to achieve further processing and transmission of the electrocardiogram signal. The electrode assembly (5) further comprises an electrode buckle 1 (51), an electrode buckle 2 (52), and an electrode buckle 3 (53). The electrode assembly (5) is connected to the conductive cloth (2) and the conductive sponge (4) to ensure accurate transmission of the electrocardiogram signal. The hardware device (6) is composed of a front-end acquisition module, a main control processing module, a data storage module, a Bluetooth module and a power management module, and is responsible for the acquisition, processing, storage and transmission of electrocardiogram signals.

2. The wearable electrocardiogram detection system according to claim 1, characterized in that: The front-end acquisition module of the hardware device (6) collects electrocardiogram signals through differential amplification and right leg drive common mode suppression technology, the main control processing module digitizes the collected signals, performs real-time filtering and task scheduling, the data storage module supports data recording and playback functions, the Bluetooth module realizes wireless transmission of data, and the power management module provides stable and reliable power supply for the entire hardware platform.

3. The wearable electrocardiogram detection system according to claim 1, wherein: The manufacturing process steps are as follows: Step 1: Drilling holes at designated locations on the elastic waistband (1) for mounting the electrode assembly (5); Step 2: Cut the conductive cloth (2) to a suitable size and drill holes at corresponding positions, insert the male buckle of the electrode assembly (5) through the holes and buckle it with the bottom buckle to fix it on the conductive cloth (2); Step 3: Use needle punching technology to fit the conductive fabric (2) tightly onto the elastic waistband (1), ensuring that it is firm and flat without wrinkles; Step 4: Cut the insulating cloth (3) to a suitable size, cover the elastic waistband (1) and the conductive cloth (2) surface, and fix it by acupuncture technology to form a complete protective layer; Step 5: Cut the conductive sponge (4) to a suitable size, fold the excess conductive cloth (2) back over the insulating cloth (3), and then use acupuncture technology to cover the conductive sponge (4) on the conductive cloth (2), making it softer and more comfortable to contact with the skin, while stabilizing signal acquisition, improving wearing comfort and signal acquisition quality.

4. The wearable electrocardiogram detection system according to claim 1, wherein: The specific dimensions of the components are as follows: the elastic waistband (1) has a width of 5-10 cm and an adjustable length, and is provided with three holes with a diameter of 2-3 mm for placing electrode buckle 1 (51), electrode buckle 2 (52), and electrode buckle 3 (53), wherein electrode buckle 1 (51) and electrode buckle 3 (53) are on the same horizontal line and are 4-5 cm apart, and electrode buckle 2 (52) is located on the perpendicular bisector of the line connecting electrode buckle 1 (51) and electrode buckle 3 (53), the width of the conductive cloth (2) is 2-3 cm, the width of the insulating cloth (3) is 5-10 cm, and the width of the conductive sponge (4) is 2-3 cm and the thickness is 2-6 mm.

5. The R-wave detection method of the wearable electrocardiogram detection system according to any one of claims 1 to 4, characterized in that: The following steps are involved: S1: Preprocessing stage: S101: Filtering the ECG signal through a sliding filter to remove high-frequency noise and obtain a filtered ECG signal; S102: Split the filtered signal into two branches, perform dilation followed by corrosion, and corrosion followed by dilation on each branch, and finally subtract the two results to extract the key features of the ECG signal; S103: Merging R-wave and P-wave features through a sliding maximum filter to reduce the difficulty of subsequent R-wave identification; S2: Threshold decision stage: S201: Calculate the difference between the maximum and minimum values ​​of the signal segments by segmentation, and calculate the initial threshold after removing abnormal values; S202: Determine the peak and record its amplitude; S203: dynamically adjusting the threshold value based on the comparison between the peak value and the current threshold value to adapt to the nonlinear and non-stationary characteristics of the ECG signal; S204: By calculating and comparing the current RR interval with the average of the previous RR intervals, interference from tall T waves or noise is avoided, thereby further improving the accuracy of R wave detection.

6. The R-wave detection method of a wearable electrocardiogram detection system according to claim 5, characterized in that: The formula for the expansion operation is: The formula for the corrosion operation is: Wherein, f(n) is a signal sequence, k(m) is a structural element, n=0, 1,…, N-1, m=0, 1,…, M-1, and N>M.

7. The R-wave detection method of a wearable electrocardiogram detection system according to claim 5, wherein: The window width of the sliding maximum filter is set to 0.25s, and its formula is:

8. The R-wave detection method of a wearable electrocardiogram detection system according to claim 5, wherein: The first 10 seconds of the pre-processed signal are selected, and the difference between the maximum and minimum values ​​of the signal in each second is calculated and recorded as Δy i , i ranges from 1 to 10, and the threshold is calculated using the following three formulas: th_n=0.2×th_r, th=0.5×(th_r-th_n)+th_n.

9. The R-wave detection method of a wearable electrocardiogram detection system according to claim 5, characterized in that: After the peak value peak is identified, the threshold needs to be updated to adapt to the dynamic changes of the signal. If the peak value peak is greater than th, the peak is determined to be an R wave, and th_r is updated using the formula th_r = 0.875×th_r + 0.125×peak. If the peak value peak is less than th, the peak is determined to be not an R wave, and th_n is updated according to the formula th_n = 0.875×th_n + 0.125×peak. Then, th is updated using the formula th = 0.5×(th_r-th_n) + th_n.

10. The R-wave detection method of a wearable electrocardiogram detection system according to claim 5, characterized in that: When determining the R wave in the electrocardiogram, to avoid interference from tall T waves or noise, the following methods can be used: Calculate the current RR interval and compare it with one-third of the previous RR interval mean. If the current RR interval is less than this value and the current peak is greater than the previous peak identified as an R wave, the previous R wave determination result is overwritten with the current peak. If the current RR interval is greater than or equal to one-third of the mean, the current peak is directly used as the new R wave.

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