CN113842127B - Pulse rate detection device, pulse rate detection system, and storage medium - Google Patents
Pulse rate detection device, pulse rate detection system, and storage medium Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 49
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- 239000006185 dispersion Substances 0.000 claims description 198
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Abstract
The invention discloses a pulse rate detection device, a pulse rate detection system and a storage medium. The method comprises the steps of preprocessing an acquired physiological signal to obtain a target signal; dividing the target signal according to the initial segment length to obtain a segmented sub-signal; determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence; determining candidate pulse rate according to the peak interval mean value, and updating a candidate pulse rate sequence according to the candidate pulse rate; the final pulse rate is determined from the candidate pulse rate sequence. The invention obtains a segmented sub-signal by segmenting the target signal; determining candidate pulse rates according to the segmented sub-signals, and updating candidate pulse rate sequences according to the candidate pulse rates; the final pulse rate is determined according to the candidate pulse rate sequence, and compared with the existing mode of obtaining the pulse rate through the trained neural network model, the mode disclosed by the invention does not need training the model, can be used for directly detecting the pulse rate, and improves the pulse rate detection efficiency and saves the detection cost.
Description
Technical Field
The present invention relates to the field of pulse rate detection technologies, and in particular, to a pulse rate detection device, a pulse rate detection system, and a storage medium.
Background
Pulse rate refers to the frequency of arterial pulses. There are a number of diseases in the clinic, especially heart diseases, which can cause changes in pulse rate. Therefore, measuring pulse rate is an indispensable examination item for patients. In the prior art, a heart rate value is obtained by using a heart rate detection model, and the heart rate value is output, wherein the heart rate detection model is obtained through training of a PPG signal and an ECG signal corresponding to the PPG signal. In the prior art, when the pulse rate is calculated by adopting a neural network method, the training data is highly dependent, and generalization of a neural network model is difficult to ensure. And the training time cost of the model is high.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide a pulse rate detection device, a pulse rate detection system and a storage medium, and aims to solve the technical problems of low pulse rate detection efficiency and high cost in the prior art.
In order to achieve the above object, the present invention provides a pulse rate detection apparatus comprising: a memory, a processor, and a pulse rate detection program stored on the memory and executable on the processor, the pulse rate detection program configured to implement the steps of:
Collecting physiological signals, and preprocessing the physiological signals to obtain target signals;
dividing the target signal according to the initial segment length to obtain a segment sub-signal;
determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence;
determining candidate pulse rates according to the peak interval average value, and updating a candidate pulse rate sequence according to the candidate pulse rates;
and determining a final pulse rate according to the candidate pulse rate sequence.
Optionally, the pulse rate detection program is configured to implement the steps of:
determining a peak interval time sequence according to the segmented sub-signals;
determining a peak interval time dispersion according to the peak interval time sequence;
judging whether the peak value interval time dispersion is smaller than a preset dispersion threshold value or not;
and when the peak interval time dispersion is smaller than a preset dispersion threshold value, determining a peak interval mean value according to the peak interval time sequence.
Optionally, the pulse rate detection program is configured to implement the steps of:
determining a segmented sub-signal peak value according to the segmented sub-signal;
determining a peak position sequence according to the segmented sub-signal peak value;
Differentiating the peak position sequences to obtain peak position interval sequences;
and determining a peak interval time sequence according to the peak position interval sequence and the sampling rate.
Optionally, the pulse rate detection program is configured to implement the steps of:
determining a target step length according to the peak interval time dispersion and the sampling rate;
determining a target segment length according to the target step length and the historical segment length;
judging whether the target segment length is larger than a preset maximum segment length or not;
and when the target segment length is smaller than or equal to a preset maximum segment length, taking the target segment length as the initial segment length, and executing the step of dividing the target signal according to the initial segment length to obtain a segment sub-signal.
Optionally, the pulse rate detection program is configured to implement the steps of:
judging whether the peak value interval time dispersion is larger than a preset dispersion threshold value or not;
when the peak interval time dispersion is greater than a preset dispersion threshold, determining a target step length according to the following formula:
μ＝fs*VarThreshold
wherein μ is a target step size, fs is a sampling rate, and VarThreshold is a preset dispersion threshold.
Optionally, the pulse rate detection program is configured to implement the steps of:
Judging whether the number of candidate pulse rates in the candidate pulse rate sequence is larger than a preset pulse rate number threshold value or not;
when the number of candidate pulse rates in the candidate pulse rate sequence is smaller than or equal to a preset pulse rate number threshold value, acquiring target dispersion;
determining a target dispersion threshold according to the target dispersion and the preset dispersion threshold;
and taking the target dispersion threshold value as the preset dispersion threshold value, and executing the step of judging whether the peak interval time dispersion is smaller than the preset dispersion threshold value.
Optionally, the pulse rate detection program is configured to implement the steps of:
calculating a target dispersion threshold according to the target dispersion and the preset dispersion threshold by the following formula:
NewVarThreshold＝VarThreshold+MaxVar*0.5
wherein NewVarThreshold is a target dispersion threshold, varThreshold is a preset dispersion threshold, and MaxVar is a target dispersion.
Optionally, the pulse rate detection program is configured to implement the steps of:
the candidate pulse rate sequence determines a reference pulse rate;
selecting a target pulse rate from the candidate pulse rate sequence according to the reference pulse rate according to a preset selection strategy;
and determining a final pulse rate according to the reference pulse rate and the target pulse rate.
In addition, to achieve the above object, the present invention also provides a pulse rate detection system, including: the device comprises an acquisition module, a segmentation module, a peak interval average value determination module, an updating module and a final pulse rate determination module;
the acquisition module is used for acquiring physiological signals and preprocessing the physiological signals to obtain target signals;
the segmentation module is used for segmenting the target signal according to the initial segmentation length to obtain segmented sub-signals;
the peak interval average value determining module is used for determining a peak interval time sequence according to the segmented sub-signals and determining a peak interval average value according to the peak interval time sequence;
the updating module is used for determining candidate pulse rates according to the peak interval average value and updating a candidate pulse rate sequence according to the candidate pulse rates;
the final pulse rate determining module is used for determining a final pulse rate according to the candidate pulse rate sequence.
In addition, in order to achieve the above object, the present invention also proposes a storage medium having stored thereon a pulse rate detection program which, when executed by a processor, implements the steps of:
Collecting physiological signals, and preprocessing the physiological signals to obtain target signals;
dividing the target signal according to the initial segment length to obtain a segment sub-signal;
determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence;
determining candidate pulse rates according to the peak interval average value, and updating a candidate pulse rate sequence according to the candidate pulse rates;
and determining a final pulse rate according to the candidate pulse rate sequence.
The method comprises the steps of collecting physiological signals, and preprocessing the physiological signals to obtain target signals; dividing the target signal according to the initial segment length to obtain a segment sub-signal; determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence; determining candidate pulse rates according to the peak interval average value, and updating a candidate pulse rate sequence according to the candidate pulse rates; and determining a final pulse rate according to the candidate pulse rate sequence. The invention obtains a segmented sub-signal by segmenting the target signal; determining a peak interval mean value according to the segmented sub-signals; determining candidate pulse rate according to the peak interval mean value, and updating a candidate pulse rate sequence according to the candidate pulse rate; the final pulse rate is determined according to the candidate pulse rate sequence, and compared with the existing mode of obtaining the pulse rate through the trained neural network model, the mode disclosed by the invention does not need training the model, can be used for directly detecting the pulse rate, and improves the pulse rate detection efficiency and saves the detection cost.
Drawings
FIG. 1 is a schematic diagram of a pulse rate detection device in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart of a first embodiment of the pulse rate detecting device according to the present invention;
FIG. 3 is a flow chart of a second embodiment of the pulse rate detecting device according to the present invention;
fig. 4 is a block diagram of a first embodiment of the pulse rate detection system according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic diagram of a pulse rate detection device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the pulse rate detection apparatus may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the pulse rate detection apparatus, and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a pulse rate detection program may be included in the memory 1005 as one type of storage medium.
In the pulse rate detection apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the pulse rate detection apparatus invokes a pulse rate detection program stored in the memory 1005 through the processor 1001.
Referring to fig. 2, fig. 2 is a flowchart of a first embodiment of the pulse rate detecting device according to the present invention.
The embodiment of the invention provides a pulse rate detection device, which comprises: a memory, a processor, and a pulse rate detection program stored on the memory and executable on the processor, the pulse rate detection program configured to implement the steps of: in this embodiment, the pulse rate detection device includes the following steps:
step S10: and acquiring a physiological signal, and preprocessing the physiological signal to obtain a target signal.
The physiological signal may be a blood oxygen signal or a respiratory signal. The target signal may be a signal obtained by preprocessing a blood oxygen signal or a respiratory signal. The preprocessing may be a high frequency noise removal processing of the physiological signal using a low pass filter. The pulse rate ranges from 30 to 300 times/min, and the corresponding frequency is 0.5 to 5Hz, so that in order to preserve the detailed information of the signals, the embodiment will preserve the information of the 3 rd harmonic of the fundamental frequency, i.e. the 3 rd harmonic of the fundamental frequency is subjected to low-pass filtering, the cut-off frequency of the physiological signal is set to 15Hz, and similarly, other physiological signals need to be subjected to cut-off frequency setting according to the corresponding pulse rate range, which is not limited herein.
Step S20: and dividing the target signal according to the initial segment length to obtain a segment sub-signal.
The initial segment length may be a segment length for dividing the target signal. The segmented sub-signal may be a plurality of sub-signals having a length equal to the initial segment length obtained by dividing the target information according to the initial segment length.
It should be understood that, in this embodiment, the final pulse rate is determined by the candidate pulse rate sequence, so that different segment lengths are required to segment the target signal, so as to obtain multiple candidate pulse rates, so as to construct the candidate pulse rate sequence according to the multiple candidate pulse rates. When the target signal is segmented for the first time, the minimum segment length is used as the initial segment length, namely the minimum segment length is used for segmenting the target information, and when the target signal is segmented subsequently, the initial segment length calculated each time is used for segmenting the target signal, but the initial segment length for segmentation is not larger than the maximum segment length, and the maximum segment length and the minimum segment length are calculated through the following formulas:
SegmentMin＝fs*60/MaxHr/3
SegmentMax＝fs*60/MinHr/3
Where fs denotes the sampling rate of the physiological signal, segmentMin denotes the minimum segment length, and MaxHr denotes the pulse rate maximum of the physiological signal. In this example, 300 times/min are taken, segmentMax represents the maximum segment length, minHr represents the minimum pulse rate of the physiological signal, and in this example, 30 times/min are taken. The values of MinHr and MaxHr can be adaptively adjusted according to different physiological signals, and the embodiment is not limited herein.
Step S30: and determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence.
The peak interval time sequence may be a peak position interval sequence obtained by differentiating a peak position sequence, and the peak interval time sequence is determined according to the peak position interval sequence and the sampling rate. For example, the sampling points of the target signal are 4096 points, the positions of the detected peak points are at 1500 th, 2100 th and 2500 th, the peak position sequences are [1500, 2100, 2500], the peak position sequences are differentiated to obtain peak position interval sequences, namely [600, 400], and then the peak position interval time sequences are determined according to the peak position interval sequences and the sampling rate by the following formulas:
RrInterval＝DfIndexArray/fs
Wherein, the RrInterval is a peak interval time sequence, the DfIndexArray is a peak position interval sequence, and the fs is a sampling rate.
It should be appreciated that determining a peak interval mean from the peak interval time series may be calculating an average of individual peak interval times in the peak interval time series, with the average being taken as the peak interval mean.
Further, in order to reduce the detection cost of the pulse rate and improve the efficiency of pulse rate detection, the step S30 may include: determining a peak interval time sequence according to the segmented sub-signals; determining a peak interval time dispersion according to the peak interval time sequence; judging whether the peak value interval time dispersion is smaller than a preset dispersion threshold value or not; and when the peak interval time dispersion is smaller than a preset dispersion threshold value, determining a peak interval mean value according to the peak interval time sequence.
It should be noted that the preset dispersion threshold value may be a dispersion threshold value determined in advance according to an empirical value. The determining the peak interval time dispersion from the peak interval time sequence may be calculating the peak interval time dispersion from the peak interval time sequence by the following formula:
Where Var is the peak interval time dispersion and n is the peak interval in the peak interval time sequence
Quantity of time, rrInterval i For the ith peak interval, rrInterval is the peak interval mean.
In a specific implementation, for example, the peak interval time sequence is [10,15,12,14], then the number of peak intervals n is 4, the 1 st peak interval time is 10, the 2 nd peak interval time is 15, and so on, the peak interval average is (10+15+12+14)/4=12.75.
It should be understood that, only when the peak interval time dispersion is smaller than the preset dispersion threshold, determining a peak interval average value according to the peak interval time sequence, further determining a candidate pulse rate according to the peak interval average value, and when the peak interval time dispersion is greater than or equal to the preset dispersion threshold, indicating that an error may occur in the currently obtained peak interval time sequence, determining the candidate pulse rate according to the peak interval average value at this time, returning to the step of determining a target step length according to the peak interval time dispersion and the sampling rate, and re-determining an initial segment length for calculation.
Further, to reduce the detection cost of pulse rate and improve the efficiency of pulse rate detection, the step of determining the peak interval time sequence from the segmented sub-signals may include: determining a segmented sub-signal peak value according to the segmented sub-signal; determining a peak position sequence according to the segmented sub-signal peak value; differentiating the peak position sequences to obtain peak position interval sequences; and determining a peak interval time sequence according to the peak position interval sequence and the sampling rate.
It should be understood that a point with the largest amplitude can be found in each segmented sub-signal, whether the sub-signal is in an ascending trend or a descending trend is judged according to the largest amplitude of the current sub-signal and the largest amplitude of the next sub-signal, and if the largest amplitude of the current sub-signal is smaller than the largest amplitude of the next sub-signal, the current sub-signal is indicated to be in the ascending trend, otherwise, the current sub-signal is in the descending trend. Detecting the trend of the sub-signals, if the current sub-signal is an ascending trend and the next signal is a descending trend, indicating that the maximum amplitude of the current sub-signal is the peak value of the signal, wherein if the sampling points with the same amplitude appear, the previous sampling point is taken as the maximum value, therefore, according to the step of determining the peak value, at least three sub-signals are needed for determining one peak value for the detection of the peak value, and according to the step, the peak point position of all the sub-signals segmented according to the target signal is determined, namely, the peak point position is determined according to the ascending or descending trend and the amplitude of the sub-signal. For example, whether the sub-signal is in an upward trend or a downward trend may be determined according to the maximum amplitude of each of the segmented sub-signals, and the peak value of one segment of the signal may be determined according to the trend of the sub-signal. For example, the segment length is 10, the length of the current sub-signal a is 10 th to 20 th points, the length of the next adjacent sub-signal B is 20 th to 30 th points, the length of the next adjacent sub-signal C adjacent to B is 30 th to 40 th points, and the maximum amplitude values of the points a, B and C are 8,11,9, respectively, and it is known that the sub-signal a is an ascending trend, the sub-signal C is a descending trend, and the peak value determined according to the three sub-signals is the point with the largest amplitude value in the sub-signal B. And sequentially acquiring the positions of all peak points in the target signal according to the rule, namely the peak value of the segmented sub-signal. And forming a sequence of the segmented sub-signal peaks according to the sequence in the target signal, namely a peak position sequence. Differentiating the peak position sequence may be, for example, [150,200,300,450], and the peak position interval sequence obtained by differentiating the peak position sequence may be [50,100,150], and determining the peak interval time sequence from the peak position interval sequence and the sampling rate may be dividing each item of the peak position interval sequence by the sampling rate, respectively. The peak interval time series may be determined by the following formula:
RrInterval＝DfIndexArray/fs
Wherein RrInterval is a peak interval time sequence, dfIndexArray is a peak position interval sequence, and fs is a sampling rate.
Step S40: and determining a candidate pulse rate according to the peak interval average value, and updating a candidate pulse rate sequence according to the candidate pulse rate.
It should be noted that the candidate pulse rate sequence may be a sequence formed by segmenting the target information according to the initial segmentation length that is not used, and further calculating the candidate pulse rate. Determining the candidate pulse rate from the peak interval mean may be calculated by the following equation:
wherein, the liquid crystal display device comprises a liquid crystal display device,and f is the candidate pulse rate, which is the peak interval mean value.
In a specific implementation, after calculating the candidate pulse rate, the candidate pulse rate needs to be rounded for facilitating subsequent calculation, and in a different scenario, the rounding may not be performed for keeping the accuracy of calculation, which is not limited herein.
Further, in order to make the final pulse rate more accurate, after step S40, the method further includes: judging whether the number of candidate pulse rates in the candidate pulse rate sequence is larger than a preset pulse rate number threshold value or not; when the number of candidate pulse rates in the candidate pulse rate sequence is smaller than or equal to a preset pulse rate number threshold value, acquiring target dispersion; determining a target dispersion threshold according to the target dispersion and the preset dispersion threshold; and taking the target dispersion threshold value as the preset dispersion threshold value, and executing the step of judging whether the peak interval time dispersion is smaller than the preset dispersion threshold value.
It should be noted that the preset pulse rate number threshold may be a preset number of candidate pulse rates in the candidate pulse rate sequence. In this embodiment, before determining the candidate pulse rate according to the peak interval average value, it is required to determine whether the peak interval time dispersion is smaller than a preset dispersion threshold, and at this time, if the preset dispersion threshold is set too large, the calculated peak interval time dispersion is larger than the preset dispersion threshold, so that the step of determining the candidate pulse rate according to the peak interval average value may not be performed, and at this time, the number of pulse rates in the candidate pulse rate sequence may be less or inaccurate. Therefore, when the number of candidate pulse rates in the candidate pulse rate sequence is less than or equal to the preset pulse rate number threshold, the preset dispersion threshold may be inaccurately set, and at this time, adaptive adjustment is required for the preset dispersion threshold. The target dispersion may be a dispersion with a maximum dispersion value determined according to the dispersion calculated in each cycle in the dispersion calculation, for example, when the dispersion is calculated according to the minimum segment length for the first time when the pulse rate calculation is performed, the dispersion value is 1.2, after the candidate pulse rate is calculated, the initial segment length is updated, the target signal is segmented, at this time, the calculated dispersion value is 1.4, the calculated dispersion in each cycle is counted in turn, the dispersion with the maximum dispersion value is used as the target dispersion, or the target dispersion value is set to 0 in advance, and when the current calculated dispersion value is greater than the target dispersion value, the current dispersion value is used as the target dispersion value. Determining the target dispersion threshold value from the target dispersion and the preset dispersion threshold value may be calculating the target dispersion threshold value by the following formula:
NewVarThreshold＝VarThreshold+MaxVar*0.5
Wherein NewVarThreshold is a target dispersion threshold, varThreshold is a preset dispersion threshold, and MaxVar is a target dispersion.
In a specific implementation, when the number of candidate pulse rates in the candidate pulse rate sequence is smaller than or equal to a preset pulse rate number threshold value, acquiring a target dispersion; determining a target dispersion threshold according to the target dispersion and the preset dispersion threshold; and taking the target dispersion threshold value as the preset dispersion threshold value, returning to the step of dividing the target signal according to the minimum segment length, calculating the peak interval time dispersion, judging whether the peak interval time dispersion is smaller than the preset dispersion threshold value or not at this time, namely judging whether the peak interval time dispersion is smaller than the target dispersion threshold value, determining a peak interval mean value according to the peak interval time sequence when the peak interval time dispersion is smaller than the target dispersion threshold value, determining a candidate pulse rate according to the peak interval mean value, updating a candidate pulse rate sequence according to the candidate pulse rate, and returning to the step of determining a target step according to the peak interval time dispersion and the sampling rate.
Step S50: and determining a final pulse rate according to the candidate pulse rate sequence.
The final pulse rate may be determined according to the candidate pulse rate sequence by taking the pulse rate having the largest number of occurrences in the candidate pulse rate sequence as a reference pulse rate, and calculating the final pulse rate by taking the partial pulse rate adjacent to the reference pulse rate and the reference pulse rate together. The purpose is to discard partially inaccurate candidate pulse rates.
Further, in order to make the calculated final pulse rate more accurate, the step S50 may include: determining a reference pulse rate according to the candidate pulse rate sequence; selecting a target pulse rate from the candidate pulse rate sequence according to the reference pulse rate according to a preset selection strategy; and determining a final pulse rate according to the reference pulse rate and the target pulse rate.
The reference pulse rate may be the pulse rate with the largest frequency in the candidate pulse rate sequence, and if the pulse rates with the same frequency are found, a smaller pulse rate is selected as the reference pulse rate, for example, if the pulse rate in the candidate pulse rate is 60,70,80,80,70, the pulse rate with the largest frequency is 70 and 80, and if the pulse rate is 70, the smaller pulse rate is used as the reference pulse rate. The selecting of the target pulse rate from the candidate pulse rate sequence according to the reference pulse rate according to a preset selection strategy may be selecting a pulse rate within a preset range from the reference pulse rate. For example, a pulse rate differing from the reference pulse rate by 1% or 2%, or a pulse rate differing from the reference pulse rate by a range of 0 to 4 is selected. Determining the final pulse rate from the reference pulse rate and the target pulse rate may be calculating the final pulse rate from the reference pulse rate and the target pulse rate by the following formula:
HR＝HR 0 *N 0 /N+HR 1 *N 1 /N+...HR n *N n /N
Wherein HR is the final pulse rate value, HR 0 For the reference pulse value, N 0 N is the total number of the reference pulse rate and the target pulse rate, HR 1 For a first target pulse rate, HR n N is the number of different pulse rates among the target pulse rates, N is the nth target pulse rate 1 N is the number of pulse rates corresponding to the first target pulse rate n The number of pulse rates corresponding to the nth target pulse rate.
In implementations, for example, the candidate pulse rate has a pulse rate of 59, 60, 65, 60, 61, 60, 61. The most frequent pulse rate is 60, the reference pulse rate is 60, the selection strategy is to select pulse rates differing from the reference pulse rate by 2%, i.e. the selection range is 58.8-61.2, and the selected target pulse rates are 59 and 61. From the above values, it can be seen that: the reference pulse rate value is 60, the number of reference pulse rates is 3, the total number of the reference pulse rates and the target pulse rates is 6, the target pulse rates are 59 and 61, the target pulse rate 59 is taken as a first target pulse rate, the target pulse rate 61 is taken as a second target pulse rate, the number of pulse rates corresponding to the first target pulse rate 59 is 1, the number of pulse rates corresponding to the second target pulse rate 61 is 2, and the data are brought into the final pulse rate to calculate the final pulse rate HR as follows:
HR＝60*3/6+59*1/6+61*2/6
The embodiment collects physiological signals and preprocesses the physiological signals to obtain target signals; dividing the target signal according to the initial segment length to obtain a segment sub-signal; determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence; determining candidate pulse rates according to the peak interval average value, and updating a candidate pulse rate sequence according to the candidate pulse rates; and determining a final pulse rate according to the candidate pulse rate sequence. In the embodiment, a target signal is segmented to obtain segmented sub-signals; determining a peak interval mean value according to the segmented sub-signals; determining candidate pulse rate according to the peak interval mean value, and updating a candidate pulse rate sequence according to the candidate pulse rate; the final pulse rate is determined according to the candidate pulse rate sequence, and compared with the existing mode of obtaining the pulse rate through the trained neural network model, the mode of the embodiment does not need training of the model, can directly detect the pulse rate, improves pulse rate detection efficiency and saves detection cost.
Referring to fig. 3, fig. 3 is a flowchart of a second embodiment of the pulse rate detecting device according to the present invention.
Based on the first embodiment, in this embodiment, after step S40, the method further includes:
Step S401: and determining a target step length according to the peak interval time dispersion and the sampling rate.
It should be noted that, the target step length may be a step length for updating the initial segment length, for example, the initial segment length is a, the target step length is B, and the updated initial segment length is a+b. The determining the target step length according to the peak interval time dispersion and the sampling rate may be calculating the target step length by the following algorithm:
wherein μ is a target step size, var is a peak interval time dispersion, varThreshold is a preset dispersion threshold, and fs is a sampling rate.
In a specific implementation, when calculating the target step length, the peak interval time dispersion is compared with a preset dispersion threshold value and 0.01, a corresponding formula for calculating the target step length is selected according to the comparison result, and the target step length is calculated according to the corresponding formula for calculating the target step length, wherein the 0.01 and the preset dispersion threshold value are both empirically set thresholds, and can be adjusted according to an actual scene, and the embodiment is not limited herein.
Further, in order to make the detected pulse rate more accurate, the step S401 may include: judging whether the peak value interval time dispersion is larger than a preset dispersion threshold value or not;
When the peak interval time dispersion is greater than a preset dispersion threshold, determining a target step length according to the following formula:
μ＝fs*VarThreshold
wherein μ is a target step size, fs is a sampling rate, and VarThreshold is a preset dispersion threshold.
It should be understood that when the dispersion of the peak interval time is greater than the preset dispersion threshold, it is indicated that a certain error may exist in the obtained peak interval time when the target signal is segmented with the current initial segmentation length, and at this time, the initial segmentation length needs to be redetermined to calculate the candidate pulse rate.
Step S402: and determining the target segment length according to the target step length and the historical segment length.
It should be noted that the historical segment length may be the initial segment length used in the last calculation of the candidate pulse rate. The determining the target segment length according to the target step length and the historical segment length may be determining the target segment length by the following formula:
NewSegment＝Segment+μ
wherein NewSegment is the target Segment length, segment is the history Segment length, and μ is the target step size.
In a specific implementation, since the target step length corresponds to the length of the sampling point of the sub-signal, when determining the target segment length according to the target step length and the historical segment length, the target step length needs to be rounded firstly, specifically, rounding may be performed by rounding, or decimal places may be directly discarded, where the embodiment is not limited, for example, the historical segment length is 4, the calculated target step length is 1.6, rounding is performed on the target step length by rounding, and the obtained processed target step length is 2, and the target segment length is 4+2=6. The target segment length is the initial segment length used for dividing the target signal when calculating the candidate pulse rate.
Step S403: and judging whether the target segment length is larger than a preset maximum segment length.
It should be noted that, the preset maximum segment length may be a segment length calculated by the following formula:
SegmentMax＝fs*60/MinHr/3
where fs represents the sampling rate of the physiological signal, segmentMax represents the preset maximum segment length, minHr represents the minimum pulse rate of the physiological signal, and in this embodiment 30 times/min may be taken. The value of MinHr can be adaptively adjusted according to different physiological signals, and the embodiment is not limited herein.
In a specific implementation, it is determined whether the target segment length is greater than a preset maximum segment length, and when the target segment length is greater than the preset maximum segment length, the target signal is already not suitable for being segmented by using the target segment length, and at this time, the step of determining the final pulse rate according to the candidate pulse rate sequence may be returned.
Step S404: and when the target segment length is smaller than or equal to a preset maximum segment length, taking the target segment length as the initial segment length, and executing the step of dividing the target signal according to the initial segment length to obtain a segment sub-signal.
It should be understood that when the target segment length is less than or equal to the preset maximum segment length, at this time, the target signal may be segmented according to the target segment length, so as to obtain a candidate pulse rate, and a more comprehensive candidate pulse rate sequence may be obtained, so that the final pulse rate calculated according to the candidate pulse rate sequence is more accurate. Therefore, when the target segment length is smaller than or equal to the preset maximum segment length, the target segment length is used as the initial segment length, and the step of dividing the target signal according to the initial segment length to obtain segmented sub-signals is returned to, so that the candidate pulse rate is obtained and the candidate pulse rate sequence is updated.
The embodiment determines a target step length according to the peak interval time dispersion and the sampling rate; determining a target segment length according to the target step length and the historical segment length; judging whether the target segment length is larger than a preset maximum segment length or not; and when the target segment length is smaller than or equal to a preset maximum segment length, taking the target segment length as the initial segment length, and executing the step of dividing the target signal according to the initial segment length to obtain a segment sub-signal. In the embodiment, a target step length is determined through the peak interval time dispersion and the sampling rate; and determining the target segment length according to the target step length and the historical segment length, further segmenting the target signal by adopting the target segment length, determining the candidate pulse rate again, and updating the candidate pulse rate sequence, so that the pulse rate in the obtained candidate pulse rate sequence is more comprehensive and accurate. And further, the calculated final pulse rate is more accurate.
Referring to fig. 4, fig. 4 is a block diagram of a first embodiment of the pulse rate detection system according to the present invention.
As shown in fig. 4, the pulse rate detection system according to the embodiment of the present invention includes: the device comprises an acquisition module 10, a segmentation module 20, a peak interval average value determination module 30, an updating module 40 and a final pulse rate determination module 50;
the acquisition module 10 is used for acquiring physiological signals and preprocessing the physiological signals to obtain target signals;
the dividing module 20 is configured to divide the target signal according to an initial segmentation length to obtain segmented sub-signals;
the peak interval average determining module 30 is configured to determine a peak interval time sequence according to the segmented sub-signals, and determine a peak interval average according to the peak interval time sequence;
the updating module 40 is configured to determine a candidate pulse rate according to the peak interval average value, and update a candidate pulse rate sequence according to the candidate pulse rate;
the final pulse rate determination module 50 is configured to determine a final pulse rate according to the candidate pulse rate sequence.
The embodiment collects physiological signals and preprocesses the physiological signals to obtain target signals; dividing the target signal according to the initial segment length to obtain a segment sub-signal; determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence; determining candidate pulse rates according to the peak interval average value, and updating a candidate pulse rate sequence according to the candidate pulse rates; and determining a final pulse rate according to the candidate pulse rate sequence. In the embodiment, a target signal is segmented to obtain segmented sub-signals; determining a peak interval mean value according to the segmented sub-signals; determining candidate pulse rate according to the peak interval mean value, and updating a candidate pulse rate sequence according to the candidate pulse rate; the final pulse rate is determined according to the candidate pulse rate sequence, and compared with the existing mode of obtaining the pulse rate through the trained neural network model, the mode of the embodiment does not need training of the model, can directly detect the pulse rate, improves pulse rate detection efficiency and saves detection cost.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details that are not described in detail in this embodiment may refer to the parameter operation method provided in any embodiment of the present invention, and are not described herein again.
Based on the first embodiment of the pulse rate detection system of the present invention, a second embodiment of the pulse rate detection system of the present invention is provided.
In this embodiment, the peak interval average determining module 30 is further configured to determine a peak interval time sequence according to the segmented sub-signals; determining a peak interval time dispersion according to the peak interval time sequence; judging whether the peak value interval time dispersion is smaller than a preset dispersion threshold value or not; and when the peak interval time dispersion is smaller than a preset dispersion threshold value, determining a peak interval mean value according to the peak interval time sequence.
Further, the peak interval average determining module 30 is further configured to determine a segmented sub-signal peak value according to the segmented sub-signal; determining a peak position sequence according to the segmented sub-signal peak value; differentiating the peak position sequences to obtain peak position interval sequences; and determining a peak interval time sequence according to the peak position interval sequence and the sampling rate.
Further, the updating module 40 is further configured to determine a target step according to the peak interval time dispersion and the sampling rate; determining a target segment length according to the target step length and the historical segment length; judging whether the target segment length is larger than a preset maximum segment length or not; and when the target segment length is smaller than or equal to a preset maximum segment length, taking the target segment length as the initial segment length, and executing the step of dividing the target signal according to the initial segment length to obtain a segment sub-signal.
Further, the updating module 40 is further configured to determine whether the peak interval time dispersion is greater than a preset dispersion threshold; when the peak interval time dispersion is greater than a preset dispersion threshold, determining a target step length according to the following formula:
μ＝fs*VarThreshold
wherein μ is a target step size, fs is a sampling rate, and VarThreshold is a preset dispersion threshold.
Further, the updating module 40 is further configured to determine whether the number of candidate pulse rates in the candidate pulse rate sequence is greater than a preset pulse rate number threshold; when the number of candidate pulse rates in the candidate pulse rate sequence is smaller than or equal to a preset pulse rate number threshold value, acquiring target dispersion; determining a target dispersion threshold according to the target dispersion and the preset dispersion threshold; and taking the target dispersion threshold value as the preset dispersion threshold value, and executing the step of judging whether the peak interval time dispersion is smaller than the preset dispersion threshold value.
Further, the updating module 40 is further configured to calculate a target dispersion threshold according to the target dispersion and the preset dispersion threshold by the following formula:
NewVarThreshold＝VarThreshold+MaxVar*0.5
wherein NewVarThreshold is a target dispersion threshold, varThreshold is a preset dispersion threshold, and MaxVar is a target dispersion.
Further, the final pulse rate determining module 50 is further configured to determine a reference pulse rate according to the candidate pulse rate sequence; selecting a target pulse rate from the candidate pulse rate sequence according to the reference pulse rate according to a preset selection strategy; and determining a final pulse rate according to the reference pulse rate and the target pulse rate.
Other embodiments or specific implementations of the pulse rate detection system of the present invention may refer to the above method embodiments, and are not described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. read-only memory/random-access memory, magnetic disk, optical disk), comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (5)
1. A pulse rate detection apparatus, characterized in that the pulse rate detection apparatus comprises: a memory, a processor, and a pulse rate detection program stored on the memory and executable on the processor, the pulse rate detection program configured to implement the steps of:
collecting physiological signals, and preprocessing the physiological signals to obtain pulse signals;
dividing the pulse signal according to the initial segmentation length to obtain segmented sub-signals;
determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence;
determining candidate pulse rates according to the peak interval average value, and updating a candidate pulse rate sequence according to the candidate pulse rates;
determining a final pulse rate according to the candidate pulse rate sequence;
the determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence includes:
determining a peak interval time sequence according to the segmented sub-signals;
determining a peak interval time dispersion according to the peak interval time sequence;
judging whether the peak value interval time dispersion is smaller than a preset dispersion threshold value or not;
When the peak interval time dispersion is smaller than a preset dispersion threshold value, determining a peak interval mean value according to the peak interval time sequence;
after the peak interval time dispersion is determined according to the peak interval time sequence, the method further comprises the following steps:
determining a target step length according to the peak interval time dispersion and the sampling rate;
determining a target segment length according to the target step length and the historical segment length;
judging whether the target segment length is larger than a preset maximum segment length or not;
when the target segment length is smaller than or equal to a preset maximum segment length, taking the target segment length as the initial segment length, and executing the step of segmenting the pulse signal according to the initial segment length to obtain segmented sub-signals;
the determining a target step length according to the peak interval time dispersion and the sampling rate comprises the following steps:
judging whether the peak value interval time dispersion is larger than a preset dispersion threshold value or not;
when the time dispersion of the peak value interval is larger than a preset dispersion threshold value, acquiring a sampling rate and the preset dispersion threshold value, wherein a target step length is the product of the sampling rate and the preset dispersion threshold value;
After determining the candidate pulse rate according to the peak interval average value and updating the candidate pulse rate sequence according to the candidate pulse rate, the method further comprises the following steps:
judging whether the number of candidate pulse rates in the candidate pulse rate sequence is larger than a preset pulse rate number threshold value or not;
when the number of candidate pulse rates in the candidate pulse rate sequence is smaller than or equal to a preset pulse rate number threshold value, acquiring target dispersion;
the target dispersion threshold value is a preset dispersion threshold value plus 0.5 times of target dispersion;
and taking the target dispersion threshold value as the preset dispersion threshold value, and executing the step of judging whether the peak interval time dispersion is smaller than the preset dispersion threshold value.
2. The pulse rate detection apparatus according to claim 1, wherein the pulse rate detection program is configured to implement the steps of:
determining a segmented sub-signal peak value according to the segmented sub-signal;
determining a peak position sequence according to the segmented sub-signal peak value;
differentiating the peak position sequences to obtain peak position interval sequences;
and determining a peak interval time sequence according to the peak position interval sequence and the sampling rate.
3. The pulse rate detection apparatus according to claim 1, wherein the pulse rate detection program is configured to implement the steps of:
Determining a reference pulse rate according to the candidate pulse rate sequence;
selecting a target pulse rate from the candidate pulse rate sequence according to the reference pulse rate according to a preset selection strategy;
and determining a final pulse rate according to the reference pulse rate and the target pulse rate.
4. A pulse rate detection system, the pulse rate detection system comprising: the device comprises an acquisition module, a segmentation module, a peak interval average value determination module, an updating module and a final pulse rate determination module;
the acquisition module is used for acquiring physiological signals and preprocessing the physiological signals to obtain pulse signals;
the segmentation module is used for segmenting the pulse signal according to the initial segmentation length to obtain segmented sub-signals;
the peak interval average value determining module is used for determining a peak interval time sequence according to the segmented sub-signals and determining a peak interval average value according to the peak interval time sequence;
the updating module is used for determining candidate pulse rates according to the peak interval average value and updating a candidate pulse rate sequence according to the candidate pulse rates;
the final pulse rate determining module is used for determining a final pulse rate according to the candidate pulse rate sequence;
The peak interval mean value determining module is used for determining a peak interval time sequence according to the segmented sub-signals;
determining a peak interval time dispersion according to the peak interval time sequence;
judging whether the peak value interval time dispersion is smaller than a preset dispersion threshold value or not;
when the peak interval time dispersion is smaller than a preset dispersion threshold value, determining a peak interval mean value according to the peak interval time sequence;
the peak interval mean value determining module is used for determining a target step length according to the peak interval time dispersion and the sampling rate;
determining a target segment length according to the target step length and the historical segment length;
judging whether the target segment length is larger than a preset maximum segment length or not;
when the target segment length is smaller than or equal to a preset maximum segment length, taking the target segment length as the initial segment length, and executing the step of segmenting the pulse signal according to the initial segment length to obtain segmented sub-signals;
the peak interval mean value determining module is used for judging whether the peak interval time dispersion is larger than a preset dispersion threshold value or not;
when the time dispersion of the peak value interval is larger than a preset dispersion threshold value, acquiring a sampling rate and the preset dispersion threshold value, wherein a target step length is the product of the sampling rate and the preset dispersion threshold value;
After determining the candidate pulse rate according to the peak interval average value and updating the candidate pulse rate sequence according to the candidate pulse rate, the method further comprises the following steps:
judging whether the number of candidate pulse rates in the candidate pulse rate sequence is larger than a preset pulse rate number threshold value or not;
when the number of candidate pulse rates in the candidate pulse rate sequence is smaller than or equal to a preset pulse rate number threshold value, acquiring target dispersion;
the target dispersion threshold value is a preset dispersion threshold value plus 0.5 times of target dispersion;
and taking the target dispersion threshold value as the preset dispersion threshold value, and executing the step of judging whether the peak interval time dispersion is smaller than the preset dispersion threshold value.
5. A storage medium having a pulse rate detection program stored thereon, the pulse rate detection program when executed by a processor performing the steps of:
collecting physiological signals, and preprocessing the physiological signals to obtain pulse signals;
dividing the pulse signal according to the initial segmentation length to obtain segmented sub-signals;
determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence;
Determining candidate pulse rates according to the peak interval average value, and updating a candidate pulse rate sequence according to the candidate pulse rates;
determining a final pulse rate according to the candidate pulse rate sequence;
the determining a peak interval time sequence according to the segmented sub-signals, and determining a peak interval mean value according to the peak interval time sequence includes:
determining a peak interval time sequence according to the segmented sub-signals;
determining a peak interval time dispersion according to the peak interval time sequence;
judging whether the peak value interval time dispersion is smaller than a preset dispersion threshold value or not;
when the peak interval time dispersion is smaller than a preset dispersion threshold value, determining a peak interval mean value according to the peak interval time sequence;
after the peak interval time dispersion is determined according to the peak interval time sequence, the method further comprises the following steps:
determining a target step length according to the peak interval time dispersion and the sampling rate;
determining a target segment length according to the target step length and the historical segment length;
judging whether the target segment length is larger than a preset maximum segment length or not;
when the target segment length is smaller than or equal to a preset maximum segment length, taking the target segment length as the initial segment length, and executing the step of segmenting the pulse signal according to the initial segment length to obtain segmented sub-signals;
The determining a target step length according to the peak interval time dispersion and the sampling rate comprises the following steps:
judging whether the peak value interval time dispersion is larger than a preset dispersion threshold value or not;
when the time dispersion of the peak value interval is larger than a preset dispersion threshold value, acquiring a sampling rate and the preset dispersion threshold value, wherein a target step length is the product of the sampling rate and the preset dispersion threshold value;
after determining the candidate pulse rate according to the peak interval average value and updating the candidate pulse rate sequence according to the candidate pulse rate, the method further comprises the following steps:
judging whether the number of candidate pulse rates in the candidate pulse rate sequence is larger than a preset pulse rate number threshold value or not;
when the number of candidate pulse rates in the candidate pulse rate sequence is smaller than or equal to a preset pulse rate number threshold value, acquiring target dispersion;
the target dispersion threshold value is a preset dispersion threshold value plus 0.5 times of target dispersion;
and taking the target dispersion threshold value as the preset dispersion threshold value, and executing the step of judging whether the peak interval time dispersion is smaller than the preset dispersion threshold value.
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