A heart rate and cardiac cycle detection method based on ballistocardiogram signal

Abstract

The present invention relates to a method for detecting heart rate and cardiac cycle based on ballistocardiogram signals, and belongs to the field of heartbeat signal processing. The method comprises: using a fiber Bragg grating (FBG) sensor to acquire a subject's ballistocardiogram (BCG) signal; preprocessing the acquired signal, including extracting valid BCG signals and reconstructing signal segments with abnormal amplitudes; using a designed adaptive template matching method to detect J waves in the BCG signal and adjust J waves with abnormal positions; and calculating the heart rate and cardiac cycle based on the detected J wave position. The present invention provides a more comfortable and convenient detection method for non-contact heart rate health detection at home, which can accurately acquire heart rate and cardiac cycle.

Description

Technical Field

[0001] The invention belongs to the field of heartbeat signal processing and relates to a heart rate and cardiac cycle detection method based on ballistocardiogram signals. Background Art

[0002] With the continuous development of smart homes, home health monitoring provides people with a more convenient way to monitor their health status in real time during their daily lives. Heart rate, as an important physiological indicator of the human body, usually reflects whether the human body has certain cardiovascular diseases, sleep quality and other problems. At present, the main methods of collecting heart rate are contact and non-contact. Contact detection requires electrodes to be in contact with human skin to obtain information, so it is highly restrictive and less comfortable. Non-contact detection embeds sensors in beds, chairs, etc. to detect body vibration signals caused by heartbeats. This method avoids direct contact between sensors and human skin and has gradually become a research hotspot for home health monitoring.

[0003] The human body vibration signal caused by the ejection and contraction of the heart is called the ballistocardiogram (BCG) signal. BCG is similar to the electrocardiogram signal and has more obvious peak information, such as Figure 1 As shown, the J wave in the BCG signal can be detected to calculate the heart rate and cardiac cycle. Currently, the heart rate detection methods based on BCG signals include: spectrum method, waveform method, template matching method, etc. The spectrum method can perform Fourier transform on a segment of BCG signal to obtain the heart rate, but this method cannot reflect the changes in heartbeat activity in real time. The waveform method calculates the distance between two peaks based on the waveform characteristics. The calculation method is simple, but the BCG waveform is relatively complex, making it difficult to accurately detect the position of the heartbeat J wave. The template matching method usually divides the BCG signal into sub-segments for training to extract heartbeat sub-templates, and uses the sub-templates to obtain the subject's heart rate, but this method may not be able to accurately detect the J wave position, resulting in inaccurate calculated heart rate and cardiac cycle. Summary of the Invention

[0004] In view of this, an object of the present invention is to provide a method for detecting heart rate and cardiac cycle based on a ballistocardiogram signal.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A method for detecting heart rate and cardiac cycle based on a ballistocardiogram signal, the method comprising the following steps:

[0007] S1: Collect BCG signals of subjects using FBG sensors;

[0008] S2: pre-process the collected signals;

[0009] S3: Use adaptive template matching to detect J waves in BCG signals and adjust J waves with abnormal positions;

[0010] S4: Calculate the heart rate and cardiac cycle based on the detected J wave.

[0011] Optionally, S1 includes the following steps:

[0012] S11: multiple FBG sensors with different central wavelengths are connected in series to form a detection channel, and multiple detection channels are connected in series in the same form;

[0013] S12: Use a fiber Bragg grating demodulator for demodulation, and adjust the sampling frequency to 250 Hz.

[0014] Optionally, S2 specifically includes the following steps:

[0015] S21: Based on the heart rate frequency range of 1.0-3.5 Hz, the BCG signal in this frequency band is extracted using an FIR filter;

[0016] S22: Detect whether there is a signal segment with abnormal amplitude in the BCG signal. If so, proceed to step S23; otherwise, proceed to step S3;

[0017] S23: Reconstruct signal segments with abnormal amplitude using an autoregressive model.

[0018] Optionally, S3 specifically includes the following steps:

[0019] S31: Calculate the division length of the heartbeat signal using the autocorrelation function;

[0020] S32: Divide the BCG signal into sub-signal segments of equal length, and select some of the signal segments as the input set of the K-means algorithm;

[0021] S33: Use K-means algorithm to train and extract heartbeat sub-templates;

[0022] S34: Calculate the correlation coefficient function between the heartbeat sub-template and the BCG signal, consider the peak point greater than the set threshold as a valid heartbeat, record its corresponding position and mark it in the BCG signal;

[0023] S35: With each marked point as the center, search for the position of the maximum peak point in the local range, and record the position as the heartbeat J wave;

[0024] S36: Adjust the abnormal position of J wave according to the heartbeat interval range of 0.4-1.5s.

[0025] Optionally, the S4 specifically includes the following steps:

[0026] S41: Calculate the number of J waves detected per unit time, and the calculation result is regarded as the current heart rate of the subject;

[0027] S42: Calculate the distance between two J waves, which is one beat of the subject's cardiac cycle. By calculating the distance between two consecutive adjacent J waves, the change of the cardiac cycle is obtained.

[0028] The beneficial effects of the present invention include: It fully considers user comfort and adopts a non-contact detection method. The use of optical FBG sensors avoids electromagnetic noise interference, while the simultaneous use of multiple sensors increases the detection range and enables the acquisition of high-quality signals for analysis. The use of adaptive template matching and correction of J waves with abnormal positions improves J wave detection accuracy, thereby enabling better calculation of heart rate and cardiac cycle.

[0029] Other advantages, objects, and features of the present invention will be described in part in the following description and, in part, will be apparent to those skilled in the art upon examination of the following description or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings, in which:

[0031] Figure 1 This is a schematic diagram of BCG signal;

[0032] Figure 2 Schematic diagram of the signal acquisition device;

[0033] Figure 3 This is the J wave detection flow chart;

[0034] Figure 4 Adjusted rules for J-wave search;

[0035] Figure 5 Adjust the rules for abnormally located J waves. DETAILED DESCRIPTION

[0036] The following describes the embodiments of the present invention by means of specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0037] Among them, the accompanying drawings are only for illustrative purposes and represent only schematic diagrams rather than actual pictures, and should not be understood as limiting the present invention. In order to better illustrate the embodiments of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the dimensions of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions may be omitted in the accompanying drawings.

[0038] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "back", etc. indicating directions or positional relationships, they are based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operate in a specific direction. Therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0039] See also Figures 1 to 5 It is a heart rate and cardiac cycle detection method based on the ballistocardiogram signal. The use of FBG sensors for detection avoids most electromagnetic noise interference and has a long service life. At the same time, the non-invasive detection method also increases the comfort and convenience of use. By using the adaptive template matching method and correcting the abnormal position of the J wave, the accuracy of the detection is effectively improved.

[0040] The present invention provides a method for detecting heart rate and cardiac cycle based on ballistocardiogram signals. The method consists of four main parts: the first part collects the original signal of human body vibration caused by heartbeat activity by forming a sensor array of FBG sensors and placing them on a bed for signal acquisition; the second part preprocesses the collected original signal; the third part uses an adaptive template matching method to detect J waves and adjust J waves with abnormal positions; and the fourth part calculates the heart rate and cardiac cycle based on the detected J waves.

[0041] The present invention provides a method for detecting heart rate and cardiac cycle based on ballistocardiogram signal. Figure 2 As shown, the specific steps include:

[0042] 1. Original signal acquisition

[0043] (1) Multiple FBG sensors with different central wavelengths are connected in series to a grating, and multiple detection channels are designed to form a sensor array;

[0044] (2) The designed detection platform is placed on the mattress, and the subject lies flat on the detection platform to collect the original BCG signal;

[0045] (3) Use a fiber Bragg grating demodulator to demodulate the signal collected by the sensor array, and save the demodulation results to the computer connected to it. The sampling frequency is adjusted to 250 Hz.

[0046] 2. Signal preprocessing

[0047] (1) Based on the heart rate frequency range of 1.0-3.5 Hz, the BCG signal in this frequency band is extracted using an FIR filter;

[0048] (2) Detect whether there is a signal segment with abnormal amplitude in the BCG signal. If so, proceed to step (3); otherwise, proceed to the J wave detection step;

[0049] (3) Use the autoregressive model to reconstruct the signal segments with abnormal amplitude.

[0050] 3. Heartbeat J wave position detection

[0051] (1) Select a segment of BCG signal and calculate its autocorrelation coefficient function and perform normalization processing. The peak points with coefficients greater than the set threshold of 0.3 are regarded as valid peak points. The difference between adjacent valid peak points is calculated and the average value L of the difference set is taken as the segment length of the heartbeat signal segment. If the number of valid peak points is less than 2, the set threshold is adjusted to 0.25.

[0052] (2) The BCG signal is divided into equal lengths of length L, and a part of the signal segments is selected as the input set Y = {x1, x2, ..., x m}, and execute the K-means algorithm to obtain the cluster with the most signal segments for extracting the heartbeat sub-template. The specific steps are as follows:

[0053] The number of iterations of the K-means algorithm was set to 100, and the first six BCG signal sub-segments were selected as the initial cluster centers. The Euclidean distance was used as the similarity metric to divide the selected signal segment set into the cluster closest to it.

[0054]

[0055] Update the cluster center until the cluster center does not change, then stop the iteration and output the divided results;

[0056] Select the cluster with the most signal segments and take the average of each point to obtain the heartbeat sub-template;

[0057] (3) Calculate the correlation coefficient function between the sub-template and the heartbeat signal, record the peak point where the coefficient is greater than the set threshold, and mark it in the BCG signal;

[0058]

[0059] Where x(t) represents the BCG signal and I(t) represents the heartbeat sub-template;

[0060] (4) With each marked point as the center, search for the maximum peak point in the local range, i.e., the J wave. The search rules are as follows: Figure 4 As shown, the J wave positions at the two end points need to be specially judged. After the J wave position detection is completed, the interval between the two J waves is used to determine whether there is an abnormal J wave. If the interval between the two J waves exceeds the range of 0.4-1.5s, then the J wave position is abnormal. Figure 5 Adjust the adjustment rules.

[0061] 4. Heart rate and cardiac cycle calculation

[0062] (1) Calculate the number of J waves per unit time and regard it as the subject's current heart rate;

[0063] (2) Continuously calculate the interval between two adjacent J waves, and the size of the interval is the change state of the subject's cardiac cycle.

[0064] The present invention designs a heart rate and cardiac cycle detection method based on ballistocardiogram signals, which mainly includes two stages: signal acquisition and signal processing.

[0065] (1) Signal acquisition stage

[0066] The signal acquisition phase primarily involves designing detection equipment and collecting human physiological signals. Vibration signals caused by heartbeats are collected and demodulated using a sensor array. The sampling frequency is set to 250Hz.

[0067] (2) Signal processing stage

[0068] The signal processing stage primarily consists of preprocessing and heart rate calculation. First, a FIR filter is used to extract valid BCG signals from the acquired raw signal. Next, the signal is checked for segments with abnormal amplitudes. If so, an autoregressive model is used to reconstruct the signal. Finally, an adaptive template matching method is used to detect J waves in the BCG signal and adjust any abnormally positioned J waves.

[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for detecting heart rate and cardiac cycle based on ballistocardiogram signals, characterized in that: The method comprises the following steps: S1: Collect BCG signals of subjects using FBG sensors; S2: pre-process the collected signals; S3: Use adaptive template matching to detect J waves in BCG signals and adjust J waves with abnormal positions; The S3 specifically includes the following steps: S31: Calculate the division length of the heartbeat signal using the autocorrelation function; S32: Divide the BCG signal into sub-signal segments of equal length, and select some of the signal segments as the input set of the K-means algorithm; S33: Use K-means algorithm to train and extract heartbeat sub-templates; S34: Calculate the correlation coefficient function between the heartbeat sub-template and the BCG signal, consider the peak point greater than the set threshold as a valid heartbeat, record its corresponding position and mark it in the BCG signal; S35: Searching for the maximum peak point in the local range with each marked point as the center, and recording the position as the heartbeat J wave; S36: Adjust the abnormally positioned J wave based on the heartbeat interval range of 0.4-1.5s. After the J wave position detection is completed, determine whether there is an abnormally positioned J wave based on the interval between the two J waves. If the interval between the two J waves exceeds the range of 0.4-1.5s, the following adjustment rules are used: S361: Determine whether the distance between two points is within 0.4-1.5s; If so, keep the J wave position unchanged and go to S364; If not, proceed to S362; S362: Determine whether the distance between the two points is less than 0.4s; If yes, search the next 200 sampling points for the position of the maximum peak point and proceed to S364; If not, proceed to S363; S363: Determine whether the distance between the two points is greater than 1.5s; If yes, search the first 200 sampling points for the position of the maximum peak point and proceed to S364; If not, proceed to S364; S364: Determine whether it is the last J wave. If so, end; if not, return to S361; S4: Calculate the heart rate and cardiac cycle based on the detected J wave; The S1 comprises the following steps: S11: multiple FBG sensors with different central wavelengths are connected in series to form a detection channel, and multiple detection channels are connected in series in the same form; S12: Use a fiber Bragg grating demodulator for demodulation, and adjust the sampling frequency to 250 Hz.

2. The method for detecting heart rate and cardiac cycle based on ballistocardiogram signals according to claim 1, wherein: The S2 specifically includes the following steps: S21: Based on the heart rate frequency range of 1.0-3.5 Hz, the BCG signal in this frequency band is extracted using an FIR filter; S22: Detect whether there is a signal segment with abnormal amplitude in the BCG signal. If so, proceed to step S23; otherwise, proceed to step S3; S23: Reconstruct signal segments with abnormal amplitude using an autoregressive model.

3. The method for detecting heart rate and cardiac cycle based on ballistocardiogram signals according to claim 1, wherein: The S4 specifically comprises the following steps: S41: Calculate the number of J waves detected per unit time, and the calculation result is regarded as the current heart rate of the subject; S42: Calculate the distance between two J waves, which is one beat of the subject's cardiac cycle. By calculating the distance between two consecutive adjacent J waves, the change of the cardiac cycle is obtained.

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