CN113693578A - Heart rate estimation method, device, equipment, system and storage medium - Google Patents
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Abstract
The invention discloses a heart rate estimation method, a heart rate estimation device, heart rate estimation equipment, a heart rate estimation system and a storage medium. The method comprises the following steps: respectively controlling each heartbeat collecting device to collect heartbeat physiological signals of the user; performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal; extracting heartbeat interval sequences of the synchronous heartbeat physiological signals, wherein the heartbeat interval sequences are sequences formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals; and carrying out weighted summation on the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence. According to the technical scheme, the heart rate of the user can be estimated by combining the heartbeat physiological signals of the user acquired by the image acquisition equipment, the wearing equipment and the electrode patch, so that the detection error caused by the fact that a single sensor is not tightly attached is reduced, and the heart rate detection accuracy in a vehicle driving scene is improved.
Description
Technical Field
The embodiment of the invention relates to the field of physiological parameter detection, in particular to a heart rate estimation method, a heart rate estimation device, heart rate estimation equipment, a heart rate estimation system and a storage medium.
Background
Modern life is fast in pace, and people use automobiles more and more frequently and more time. Meanwhile, due to neglect of the physiological health problem, the frequency of occurrence of fatigue driving or sudden illness or traffic accidents of the driver is also increasing. Therefore, real-time monitoring of physiological parameters of driving, such as heart rate, is highly desirable.
In the prior art, a single sensor is often used to detect heart rate. However, due to the complex environment in the vehicle, the sensor may not be in complete contact with the user due to the action of the user during the driving process of the vehicle, so that the heart rate detection result is inaccurate, and the actual physiological heart rate change of the user cannot be reflected.
Disclosure of Invention
The embodiment of the invention provides a heart rate estimation method, a heart rate estimation device, heart rate estimation equipment, a heart rate estimation system and a storage medium, which are used for estimating the heart rate of a user by combining heartbeat physiological signals of the user acquired by three sensors, namely image acquisition equipment, wearable equipment and an electrode patch, reducing detection errors caused by untight fit of a single sensor and improving the heart rate detection accuracy in a vehicle driving scene.
In a first aspect, an embodiment of the present invention provides a heart rate estimation method, including:
respectively controlling each heartbeat collecting device to collect heartbeat physiological signals of the user;
performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal;
extracting heartbeat interval sequences of the synchronous heartbeat physiological signals, wherein the heartbeat interval sequences are sequences formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals;
further, the heartbeat interval sequences of the synchronous heartbeat physiological signals are weighted and summed to obtain a final heartbeat interval sequence, and the heart rate of the user is estimated based on the final heartbeat interval sequence.
The heartbeat physiological signal of the user is collected through each heartbeat collecting device respectively, and the method comprises the following steps:
controlling the image acquisition equipment to acquire a facial heartbeat signal representing heartbeat change of the user;
controlling the wearable device to acquire a pulse signal of the user;
and controlling the electrode patch to collect the skin heartbeat signal of the user.
Further, the signal preprocessing is performed on each heartbeat physiological signal to obtain each synchronous heartbeat physiological signal, and the method includes:
filtering each heartbeat physiological signal to obtain a filtered heartbeat physiological signal;
and aligning signal wave crests of the filtered heartbeat physiological signals to obtain synchronous heartbeat physiological signals.
Further, the filtering each heartbeat physiological signal to obtain a filtered heartbeat physiological signal includes:
eliminating the baseline drift noise and the environmental noise of the facial heartbeat signal through wavelet transformation to obtain a filtered facial heartbeat signal;
eliminating baseline drift noise of the pulse signals through adaptive filtering, and eliminating environmental noise of the pulse signals after baseline drift is eliminated through band-pass filtering to obtain filtered pulse signals;
and eliminating the baseline drift noise of the epidermis heartbeat signal through self-adaptive filtering, and eliminating the environmental noise of the epidermis heartbeat signal of the baseline drift noise through band-pass filtering to obtain the filtered epidermis heartbeat signal.
Further, weighting and summing the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, including:
determining the weight of a heartbeat interval sequence corresponding to each synchronous heartbeat physiological signal;
for each heartbeat physiological signal, determining the product of the weight of the heartbeat interval sequence and each heartbeat interval in the heartbeat interval sequence as a weighted heartbeat interval sequence of the synchronous heartbeat physiological signal;
and summing the corresponding weighted heartbeat intervals in each weighted heartbeat interval sequence to obtain a final heartbeat interval sequence.
Further, determining a weight of the heartbeat interval sequence of each of the synchronized heartbeat physiological signals includes:
determining a ratio of a standard deviation to an average value of each heartbeat interval in the heartbeat interval sequence aiming at the heartbeat interval sequence of each synchronous heartbeat physiological signal, and determining a weight coefficient corresponding to the ratio by a table look-up method;
determining the sum of the weight coefficients corresponding to the heartbeat interval sequences of the synchronous heartbeat physiological signals as a total weight coefficient;
determining a ratio of the weight coefficient to the overall weight coefficient as a weight of a sequence of heartbeat intervals of the synchronized heartbeat physiological signal.
In a second aspect, an embodiment of the present invention further provides a heart rate estimation apparatus, including:
the acquisition module is used for respectively controlling each heartbeat acquisition device to acquire heartbeat physiological signals of the user;
the preprocessing module is used for preprocessing the heartbeat physiological signals to obtain synchronous heartbeat physiological signals;
the extraction module is used for extracting a heartbeat interval sequence of each synchronous heartbeat physiological signal, wherein the heartbeat interval sequence is a sequence formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals;
and the estimation module is used for weighting and summing the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
In a third aspect, an embodiment of the present invention further provides a heart rate estimation apparatus, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the heart rate estimation method according to any one of the embodiments of the present invention when executing the program.
In a fourth aspect, an embodiment of the present invention further provides a heart rate estimation system, including a plurality of heartbeat collecting devices and a heart rate estimation device connected to each of the heartbeat collecting devices; the heartbeat collecting device comprises: image acquisition equipment, wearing equipment and electrode patch. The image acquisition device is used for acquiring facial heartbeat signals of the user, which are used for representing heartbeat change, based on the control of the heart rate estimation device; the wearable device is used for collecting the pulse signals of the user based on the control of the heart rate estimation device; the electrode patch is used for collecting the skin heartbeat signal of the user based on the control of the heart rate estimation equipment; the heart rate estimation device is used for executing the method provided by any embodiment of the invention.
In a fifth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the heart rate estimation method according to any one of the embodiments of the present invention.
According to the embodiment of the invention, the heart rate of the user is estimated by collecting the heartbeat physiological signal of the user through combining the image collecting device, the wearing device and the electrode patch, so that the problem of larger heart rate detection caused by untight fitting of a single sensor in the existing vehicle driving scene is solved, the detection error caused by untight fitting of the single sensor is reduced, and the heart rate detection accuracy in the vehicle-mounted scene is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of a method for heart rate estimation according to a first embodiment of the present invention;
FIG. 2A is a flow chart of a heart rate estimation method according to a second embodiment of the present invention;
FIG. 2B is a flow chart of a heart rate signal filtering method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a heart rate estimation device in a third embodiment of the invention;
fig. 4 is a schematic structural diagram of a heart rate estimation device in the fourth embodiment of the invention;
fig. 5 is a schematic structural diagram of a heart rate estimation system in the fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example one
Fig. 1 is a flowchart of a heart rate estimation method according to an embodiment of the present invention, where the present embodiment is applicable to a situation where a heart rate of a user is estimated in real time in a vehicle driving scenario, and the method may be executed by a heart rate estimation apparatus according to an embodiment of the present invention, where the apparatus may be implemented in a software and/or hardware manner, and the apparatus may be integrated in a heart rate estimation device.
In an embodiment of the present invention, a heart rate estimation method is applied to a heart rate estimation system, the heart rate detection system includes a plurality of heartbeat collecting devices, and the heartbeat collecting devices include: image acquisition equipment, wearing equipment and electrode patch. The image acquisition equipment can be a high-precision camera; the wearable device can be any device with a heart rate detection function, such as a bracelet or a heart rate detector; the electrode patch may be provided in a vehicle where there is a prolonged skin contact with the user, for example at the handle of the steering wheel or on a manual gear.
As shown in fig. 1, the method specifically includes the following steps:
and S110, respectively controlling each heartbeat collecting device to collect heartbeat physiological signals of the user.
Wherein, heartbeat collecting device can include: image acquisition equipment, wearing equipment and electrode patch. The heartbeat physiological signal refers to a signal which can represent heartbeat change, such as a heartbeat signal of the epidermis, a pulse signal or a facial heartbeat signal representing heartbeat change on the face.
For example, the heartbeat physiological signal acquired by the image acquisition device may be a facial heartbeat signal representing heartbeat variation of the face of the user, and the heartbeat physiological signal acquired by the wearable device may be a pulse signal of the user and the heartbeat physiological signal acquired by the electrode patch may be an electrocardiosignal conducted by the user through the epidermis.
Specifically, the heart rate estimation device respectively controls each heartbeat collecting device to collect heartbeat physiological signals of the user. For example, the heart rate estimation device may send the acquisition instruction to each heartbeat acquisition device after receiving the start instruction, so that each heartbeat acquisition device acquires the heartbeat physiological signal of the user within the preset time, and transmits the heartbeat physiological signal to the heart rate estimation device to perform heart rate estimation of the user. For example, each heartbeat collecting device collects heartbeat physiological signals of the user within a preset time, where the preset time may be 1S or 10S, and the embodiment of the present invention does not limit this.
And S120, performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal.
Because the heartbeat physiological signals of the heartbeat collecting devices are influenced by the collecting environment, noise exists in the heartbeat physiological signals of the heartbeat collecting devices, and the heartbeat physiological signals of the same user collected by the heartbeat collecting devices at the same time are possibly asynchronous, the heartbeat physiological signals collected by the heartbeat collecting devices need to be preprocessed to eliminate the noise and synchronize.
For example, the signal preprocessing of each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal may include: and carrying out noise filtering, baseline drift elimination, signal alignment and the like on each heartbeat physiological signal.
And S130, extracting the heartbeat interval sequence of each synchronous heartbeat physiological signal.
The heartbeat interval sequence is a sequence formed by time intervals between every two adjacent peaks in the synchronous heartbeat physiological signal.
Specifically, the time interval between every two adjacent peaks in each synchronous heartbeat physiological signal is a heartbeat interval, that is, the time interval of two heartbeats, and a sequence formed by each heartbeat interval is determined as a heartbeat interval sequence to reflect the heartbeat interval of the user. The heartbeat interval can be used for heart rate variability analysis and can also be used as a basis for judging whether fatigue driving exists.
It should be noted that, the facial heartbeat signal and the pulse signal are sine wave-like signals, the heartbeat intervals of which can be obtained by directly obtaining the time interval between every two adjacent peaks, and for the synchronous epidermis heartbeat signal, the heartbeat interval of the synchronous epidermis heartbeat signal is to be obtained by template matching, so as to ensure the accuracy of extracting the heartbeat interval.
S140, carrying out weighted summation on the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
Specifically, for each synchronous heartbeat physiological signal, determining the weight of the heartbeat interval sequence of each synchronous heartbeat physiological signal, performing weighting calculation on each heartbeat interval in the heartbeat interval sequence based on the weight to obtain a weighted heartbeat interval sequence, summing the weighted heartbeat interval sequences corresponding to the three synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
For example, the method of estimating the heart rate of the user based on the final heartbeat interval sequence may be estimating the heartbeat frequency per minute of the user from the final heartbeat interval sequence, or estimating the heartbeat interval variation of the user in time per minute.
According to the technical scheme of the embodiment, the heartbeat physiological signals of the user are acquired by respectively controlling the heartbeat acquisition equipment; preprocessing each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal; extracting heartbeat interval sequences of the synchronous heartbeat physiological signals; the heartbeat interval sequences of the synchronous heartbeat physiological signals are weighted and summed to obtain a final heartbeat interval sequence, the heart rate of the user is estimated based on the final heartbeat interval sequence, detection errors caused by untight fitting of a single sensor can be reduced, and the heart rate detection accuracy under a vehicle driving scene is improved.
Example two
Fig. 2A is a flowchart of a heart rate estimation method according to a second embodiment of the present invention, which is optimized based on the second embodiment.
As shown in fig. 2A, the method of this embodiment specifically includes the following steps:
and S210, respectively controlling each heartbeat collecting device to collect heartbeat physiological signals of the user.
Optionally, the image acquisition device is controlled to acquire a facial heartbeat signal representing heartbeat change of the user; controlling the wearable device to acquire a pulse signal of the user; and controlling the electrode patch to collect the skin heartbeat signal of the user.
When the heart beats, the oxygenated blood is supplied to the head and the neck to drive the face to move, the facial heartbeat signal can be considered as a facial movement signal which is generally difficult to see by naked eyes, but can be obtained by high-precision image acquisition equipment and a computer vision technology. The change rule of the face heartbeat signal is basically consistent with the beating rule of the heart. The pulse signal is a pulse signal conducted by the wearable device, and the heartbeat of a person is consistent with the frequency of the pulse under normal conditions, so that the change of the heartbeat can be reflected by the frequency of the pulse, and the skin heartbeat signal is an electrocardiosignal directly conducted through the electrode patch.
S220, performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal.
The face heartbeat signal is subjected to signal preprocessing to obtain a synchronous face heartbeat signal; and performing signal preprocessing on the pulse signals to obtain synchronous pulse signals, and performing signal preprocessing on the epidermis heartbeat signals to obtain synchronous epidermis heartbeat signals.
Optionally, step S220 may include: step 221 to step 222:
and S221, filtering each heartbeat physiological signal to obtain a filtered heartbeat physiological signal.
Specifically, filtering each heartbeat physiological signal to remove noise to obtain a preprocessed heartbeat physiological signal, where the noise includes: ambient noise and baseline drift noise. The baseline wander noise is noise caused by low-frequency disturbance such as breathing of the user.
For example, the filtering method for filtering each heartbeat physiological signal may be wavelet transformation, adaptive filtering or band-pass filtering.
S222, aligning signal wave crests of the filtered heartbeat physiological signals to obtain synchronous heartbeat physiological signals.
Illustratively, since a certain error exists in the sampling start time of each sensor for acquiring the heartbeat physiological signal, the filtered heartbeat physiological signals are aligned to obtain each synchronous heartbeat physiological signal. For different synchronous heartbeat physiological signals, the heartbeat interval between every two adjacent peaks is kept within a preset error range.
And S230, extracting a heartbeat interval sequence of each synchronous heartbeat physiological signal, wherein the heartbeat interval sequence is a sequence formed by time intervals between every two adjacent wave crests in the synchronous heartbeat physiological signals.
For each synchronous heartbeat physiological signal, obtaining a time interval between every two adjacent wave peaks of the synchronous heartbeat physiological signal, namely a heartbeat interval, wherein a sequence formed by the heartbeat intervals in the synchronous heartbeat physiological signal is called a heartbeat interval sequence.
S240, determining the weight of the heartbeat interval sequence of each synchronous heartbeat physiological signal.
Illustratively, the weight distribution is performed on the heartbeat interval sequence acquired and processed by each sensor to obtain the synchronous heartbeat physiological signal. The weight assignment may be determined according to the stability of the heart rate detection of each sensor, for example, a larger weight is assigned to the synchronous heartbeat physiological signal corresponding to the sensor with the smallest standard deviation, a smaller weight is assigned to the synchronous heartbeat physiological signal corresponding to the sensor with the largest standard deviation, and an intermediate weight is assigned to the synchronous heartbeat physiological signal corresponding to the sensor with the intermediate standard deviation. Or may be determined by a table look-up method based on the ratio of the standard deviation and the mean of the sequence of heartbeat intervals. The ratio of the weight coefficient of the synchronous heartbeat physiological signal to the sum of the weight coefficients of the three synchronous heartbeat physiological signals can also be used.
And S250, aiming at each heartbeat physiological signal, determining the product of the weight of the heartbeat interval sequence and each heartbeat interval in the heartbeat interval sequence as the weighted heartbeat interval sequence of the synchronous heartbeat physiological signal.
Specifically, for the heartbeat interval sequence corresponding to each synchronous heartbeat physiological signal, each heartbeat interval in the heartbeat interval sequence is multiplied by the weight of the heartbeat interval sequence to obtain a weighted heartbeat interval sequence of the synchronous heartbeat physiological signal.
Illustratively, if the heart beat interval sequence of the synchronous facial heart beat signal is R1＝r1,r2,…,ri,…,rnIf the weight of the heartbeat interval sequence corresponding to the synchronous facial heartbeat signal is a, the weighted heartbeat interval sequence of the synchronous facial heartbeat signal is R'1＝R1×a＝ar1,ar2,…,ari,…,arn. If the heart beat interval sequence of the synchronous pulse signal is M1＝m1,m2,…,mi,…,mnIf the weight of the heartbeat interval sequence corresponding to the synchronous pulse signal is b, the weighted heartbeat interval sequence of the synchronous facial heartbeat signal is M'1＝bm1,bm2,…,bmi,…,bmn. If the heart beat interval sequence of the synchronous epidermis heart beat signal is M1＝m1,m2,…,mi,…,mnIf the weighting of the heartbeat interval sequence corresponding to the synchronous epidermis heartbeat signal is c, the weighting heartbeat interval sequence of the synchronous epidermis heartbeat signal is L1＝cl1,cl2,…,cli,…,cln。
And S260, summing the corresponding weighted heartbeat intervals in each weighted heartbeat interval sequence to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
Illustratively, the weighted beat interval sequence of the synchronized facial beat signal is R'1＝AR1＝Ar1,Ar2,…,Ari,…,Arn(ii) a The weighted beat interval sequence of the synchronized pulse signals is M'1＝BM1Bm1,Bm2,…,Bmi,…,Bmn(ii) a The weighted epidermal heartbeat interval sequence of the synchronous pulse signal is L'1＝CL1＝Cl1,Cl2,…,Cli,…,ClnSumming the corresponding weighted heartbeat intervals in each weighted heartbeat interval sequence to obtain a final heartbeat interval sequence
Illustratively, the final heartbeat interval sequence can be stored by a data storage module, and then the stored data is called by the upper computer for playback; the heart rate of the user can be estimated through the final heartbeat interval sequence, and the heartbeat signal and the heart rate can be displayed in real time by connecting the wireless module with a vehicle machine or a mobile phone. The power management module uses the rechargeable battery to supply power to the device, displays the current electric quantity through the indicating lamp, and reminds a user to replace the battery or charge when the electric quantity is insufficient.
According to the technical scheme of the embodiment, the heartbeat physiological signals of the user are acquired by respectively controlling the heartbeat acquisition equipment; performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal; extracting heartbeat interval sequences of the synchronous heartbeat physiological signals, wherein the heartbeat interval sequences are sequences formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals; the heartbeat interval sequences of the synchronous heartbeat physiological signals are weighted and summed to obtain a final heartbeat interval sequence, the heart rate of the user is estimated based on the final heartbeat interval sequence, the heart rate of the user can be determined according to the weight distributed by each sensor, the detection error caused by the fact that a single sensor is not tightly attached is reduced, and the heart rate detection accuracy under the vehicle driving scene is improved.
Optionally, the filtering each heartbeat physiological signal to obtain a filtered heartbeat physiological signal includes:
eliminating the baseline drift noise and the environmental noise of the facial heartbeat signal through wavelet transformation to obtain a filtered facial heartbeat signal;
eliminating baseline drift noise of the pulse signals through adaptive filtering, and eliminating environmental noise of the pulse signals after baseline drift is eliminated through band-pass filtering to obtain filtered pulse signals;
and eliminating the baseline drift noise of the epidermis heartbeat signal through self-adaptive filtering, and eliminating the environmental noise of the epidermis heartbeat signal of the baseline drift noise through band-pass filtering to obtain the filtered epidermis heartbeat signal.
Specifically, as shown in fig. 2B, the process of filtering each heartbeat physiological signal to obtain a filtered heartbeat physiological signal may be as follows: decomposing a face video acquired by an image sensor, extracting an interested region, extracting a face heartbeat signal from the face video, performing wavelet transformation, eliminating baseline drift noise and environmental noise of the face heartbeat signal to obtain a filtered face heartbeat signal, and selecting the number of wavelet decomposition layers within the frequency of 0.5-2Hz considering that the normal heart rate of a human body is 60-100/min.
For the pulse signals collected by the wearable device, baseline drift noise of the pulse signals is eliminated through adaptive filtering, and environmental noise of the pulse signals after baseline drift is eliminated through band-pass filtering, so that the filtered pulse signals are obtained. The bandpass frequency of the bandpass filtering may be 0.5-2 Hz.
For the epidermis heartbeat physiological signals collected by the patch, baseline drift noise of the epidermis heartbeat physiological signals is eliminated through self-adaptive filtering, and the environment noise of the epidermis heartbeat physiological signals of which the baseline drift noise is eliminated through band-pass filtering to obtain the filtered epidermis heartbeat physiological signals. The bandpass frequency of the bandpass filtering may be 0.5-2 Hz.
Optionally, determining a weight of the heartbeat interval sequence of each synchronous heartbeat physiological signal includes:
determining a ratio of a standard deviation to an average value of each heartbeat interval in the heartbeat interval sequence aiming at the heartbeat interval sequence of each synchronous heartbeat physiological signal, and determining a weight coefficient corresponding to the ratio by a table look-up method;
determining the sum of the weight coefficients corresponding to the heartbeat interval sequences of the synchronous heartbeat physiological signals as a total weight coefficient;
determining a ratio of the weight coefficient to the overall weight coefficient as a weight of a sequence of heartbeat intervals of the synchronized heartbeat physiological signal.
Specifically, each heartbeat interval in the heartbeat interval sequence is obtained aiming at the heartbeat interval sequence of each synchronous heartbeat physiological signal, the standard deviation sigma and the average value avg of each heartbeat interval are calculated, and the ratio of the standard deviation to the average value is determined to be W (sigma/avg). And determining the weight coefficient corresponding to the ratio by a table look-up method, for example, the weight coefficient corresponding to the heartbeat interval sequence of the synchronous facial heartbeat signal is a, the weight coefficient corresponding to the heartbeat interval sequence of the synchronous pulse signal is b, and the weight coefficient corresponding to the heartbeat interval sequence of the synchronous epidermal heartbeat signal is c. Determining the sum of the weight coefficients corresponding to the heartbeat interval sequences of the synchronous heartbeat physiological signals as a total weight coefficient, namely the total weight coefficient is a + b + c; determining a ratio of the weight coefficient to the overall weight coefficient as a weight of a heartbeat interval sequence of the synchronized heartbeat physiological signal, namely:
the heart beat interval sequence of the synchronous facial heart beat signal corresponds to the weight of
The heart beat interval sequence of the synchronous pulse signal corresponds to the weight of
The weight corresponding to the heartbeat interval sequence of the synchronous epidermis heartbeat signal is
For example, the way of determining the weight coefficient corresponding to the ratio by a table lookup method may be: the ratio W corresponding to the facial heartbeat signal collected by the image collecting equipment1，W1When the weight coefficient is 0-0.1, the weight coefficient is determined to be a by a table look-up method1；W1When the weight coefficient is 0.1-0.2, the weight coefficient is determined to be a by a table look-up method2；W1When the weight coefficient is more than 0.2, the weight coefficient is determined to be a by a table look-up method3. The specific value of the weight is obtained by calibration through methods such as tests or index simulation.
Ratio W corresponding to pulse signals collected by wearable equipment2，W2When the weight coefficient is 0-0.1, the weight coefficient is determined to be b by a table look-up method1；W2When the weight coefficient is 0.1-0.2, determining the weight coefficient as b by a table look-up method2；W2When the weight coefficient is more than 0.2, the weight coefficient is determined to be b by a table look-up method3。
Corresponding ratio W of skin heartbeat signals collected by wearable equipment3，W3When the weight coefficient is 0-0.1, the weight coefficient is determined to be c by a table look-up method1；W3When the weight coefficient is 0.1-0.2, the weight coefficient is determined to be c by a table look-up method2；W3When the weight coefficient is more than 0.2, the weight coefficient is determined to be c by a table look-up method3。
EXAMPLE III
Fig. 3 is a schematic structural diagram of a heart rate estimation device according to a third embodiment of the present invention. The present embodiment may be applicable to a situation of estimating a heart rate of a user in real time in a vehicle driving scene, where the apparatus may be implemented in a software and/or hardware manner, and the apparatus may be integrated in any device providing a heart rate estimation function, as shown in fig. 3, where the apparatus specifically includes: an acquisition module 310, a pre-processing module 320, an extraction module 330, and an estimation module 340.
The acquisition module 310 is configured to respectively control each heartbeat acquisition device to acquire heartbeat physiological signals of a user;
the preprocessing module 320 is configured to perform signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal;
an extracting module 330, configured to extract a heartbeat interval sequence of each synchronous heartbeat physiological signal, where the heartbeat interval sequence is a sequence formed by time intervals between every two adjacent peaks in the synchronous heartbeat physiological signal;
the estimating module 340 is configured to perform weighted summation on the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimate the heart rate of the user based on the final heartbeat interval sequence.
Optionally, the acquiring module 310 includes:
the first acquisition unit is used for controlling the image acquisition equipment to acquire a facial heartbeat signal representing heartbeat change of the user;
the second acquisition unit is used for controlling the wearable equipment to acquire the pulse signals of the user;
and the third acquisition unit is used for controlling the electrode patch to acquire the skin heartbeat signal of the user.
Optionally, the preprocessing module 320 includes:
the filtering unit is used for filtering each heartbeat physiological signal to obtain a filtered heartbeat physiological signal;
and the synchronization unit is used for performing signal peak alignment on the filtered heartbeat physiological signals to obtain synchronous heartbeat physiological signals.
Optionally, the filtering unit is specifically configured to:
eliminating the baseline drift noise and the environmental noise of the facial heartbeat signal through wavelet transformation to obtain a filtered facial heartbeat signal;
eliminating baseline drift noise of the pulse signals through adaptive filtering, and eliminating environmental noise of the pulse signals after baseline drift is eliminated through band-pass filtering to obtain filtered pulse signals;
and eliminating the baseline drift noise of the epidermis heartbeat signal through self-adaptive filtering, and eliminating the environmental noise of the epidermis heartbeat signal of the baseline drift noise through band-pass filtering to obtain the filtered epidermis heartbeat signal.
Optionally, the estimating module includes:
the weight determining unit is used for determining the weight of the heartbeat interval sequence corresponding to each synchronous heartbeat physiological signal;
the weighting unit is used for determining the product of the weight of the heartbeat interval sequence and each heartbeat interval in the heartbeat interval sequence as the weighted heartbeat interval sequence of the synchronous heartbeat physiological signal aiming at each synchronous heartbeat physiological signal;
and the heart rate determining unit is used for summing the corresponding weighted heart rate intervals in each weighted heart rate interval sequence to obtain a final heart rate interval sequence.
Optionally, the weight determining unit is specifically configured to:
determining a ratio of a standard deviation to an average value of each heartbeat interval in the heartbeat interval sequence aiming at the heartbeat interval sequence of each synchronous heartbeat physiological signal, and determining a weight coefficient corresponding to the ratio by a table look-up method;
determining the sum of the weight coefficients corresponding to the heartbeat interval sequences of the synchronous heartbeat physiological signals as a total weight coefficient;
determining a ratio of the weight coefficient to the overall weight coefficient as a weight of a sequence of heartbeat intervals of the synchronized heartbeat physiological signal.
The product can execute the heart rate estimation method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 4 is a schematic structural diagram of a heart rate estimation device in the fourth embodiment of the present invention. Fig. 4 shows a block diagram of an exemplary heart rate estimation device 12 suitable for implementing an embodiment of the invention. The heart rate estimation device 12 shown in fig. 4 is only an example and should not impose any limitation on the functionality and scope of use of embodiments of the invention.
As shown in fig. 4, the heart rate estimation device 12 is in the form of a general purpose computing device. Components of heart rate estimation device 12 may include, but are not limited to: one or more processors or processors 16, a system memory 28, and a bus 18 that connects the various system components (including the system memory 28 and the processors 16).
The heart rate estimation device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by heart rate estimation device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The heart rate estimation device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, and commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The heart rate estimation device 12 may also be in communication with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the heart rate estimation device 12, and/or any device (e.g., network card, modem, etc.) that enables the heart rate estimation device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. In the heart rate estimating apparatus 12 of the present embodiment, the display 24 is not provided as a separate body but is embedded in the mirror surface, and when the display surface of the display 24 is not displayed, the display surface of the display 24 and the mirror surface are visually integrated. Also, the heart rate estimation device 12 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 20. As shown, the network adapter 20 communicates with the other modules of the heart rate estimation device 12 over the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the heart rate estimation device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processor 16 executes programs stored in the system memory 28 to perform various functional applications and data processing, such as implementing the heart rate estimation method provided by the embodiments of the present invention: respectively controlling each heartbeat collecting device to collect heartbeat physiological signals of the user; performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal; extracting heartbeat interval sequences of the synchronous heartbeat physiological signals, wherein the heartbeat interval sequences are sequences formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals; and carrying out weighted summation on the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
EXAMPLE five
Fig. 5 is a schematic structural diagram of a heart rate estimation system in the fifth embodiment of the present invention. The heart rate detection system includes: a plurality of heartbeat collecting devices and a heart rate estimating device as in the fourth embodiment connected to each of the heartbeat collecting devices; the heartbeat collecting device comprises: the device comprises image acquisition equipment, wearing equipment and an electrode patch;
the image acquisition device is used for acquiring facial heartbeat signals of the user, which are used for representing heartbeat change, based on the control of the heart rate estimation device;
the wearable device is used for collecting the pulse signals of the user based on the control of the heart rate estimation device;
the electrode patch is used for collecting the skin heartbeat signal of the user based on the control of the heart rate estimation equipment;
the heart rate estimation device is used for respectively controlling each heartbeat acquisition device to acquire heartbeat physiological signals of the user; performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal; extracting heartbeat interval sequences of the synchronous heartbeat physiological signals, wherein the heartbeat interval sequences are sequences formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals; and carrying out weighted summation on the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
According to the embodiment of the invention, the heartbeat physiological signals of the user are acquired through the image acquisition equipment, the wearing equipment and the electrode patch, so that the heart rate of the user can be estimated by combining facial heartbeat signals, pulse signals and epidermal heartbeat signals representing electrocardio changes, the detection error caused by the fact that a single sensor is not tightly attached is reduced, and the heart rate detection accuracy under the vehicle driving scene is improved.
EXAMPLE six
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the heart rate estimation method provided in all inventive embodiments of this application: respectively controlling each heartbeat collecting device to collect heartbeat physiological signals of the user; performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal; extracting heartbeat interval sequences of the synchronous heartbeat physiological signals, wherein the heartbeat interval sequences are sequences formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals; and carrying out weighted summation on the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A heart rate estimation method, applied to a heart rate estimation system, the heart rate detection system including a plurality of heartbeat collection devices, the heartbeat collection devices including: image acquisition equipment, wearing equipment and electrode patch, the method includes:
respectively controlling each heartbeat collecting device to collect heartbeat physiological signals of the user;
performing signal preprocessing on each heartbeat physiological signal to obtain a synchronous heartbeat physiological signal;
extracting heartbeat interval sequences of the synchronous heartbeat physiological signals, wherein the heartbeat interval sequences are sequences formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals;
and carrying out weighted summation on the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
2. The method of claim 1, wherein the step of acquiring the heartbeat physiological signals of the user by each heartbeat acquisition device respectively comprises:
controlling the image acquisition equipment to acquire a facial heartbeat signal representing heartbeat change of the user;
controlling the wearable device to acquire a pulse signal of the user;
and controlling the electrode patch to collect the skin heartbeat signal of the user.
3. The method according to claim 2, wherein the signal preprocessing each of the heartbeat physiological signals to obtain each of the synchronized heartbeat physiological signals comprises:
filtering each heartbeat physiological signal to obtain a filtered heartbeat physiological signal;
and aligning signal wave crests of the filtered heartbeat physiological signals to obtain synchronous heartbeat physiological signals.
4. The method according to claim 3, wherein the filtering each heartbeat physiological signal to obtain a filtered heartbeat physiological signal comprises:
eliminating the baseline drift noise and the environmental noise of the facial heartbeat signal through wavelet transformation to obtain a filtered facial heartbeat signal;
eliminating baseline drift noise of the pulse signals through adaptive filtering, and eliminating environmental noise of the pulse signals after baseline drift is eliminated through band-pass filtering to obtain filtered pulse signals;
and eliminating the baseline drift noise of the epidermis heartbeat signal through self-adaptive filtering, and eliminating the environmental noise of the epidermis heartbeat signal of the baseline drift noise through band-pass filtering to obtain the filtered epidermis heartbeat signal.
5. The method of claim 1, wherein weighting and summing the heartbeat interval sequences of each of the synchronized heartbeat physiological signals to obtain a final heartbeat interval sequence comprises:
determining the weight of a heartbeat interval sequence corresponding to each synchronous heartbeat physiological signal;
for each heartbeat physiological signal, determining the product of the weight of the heartbeat interval sequence and each heartbeat interval in the heartbeat interval sequence as a weighted heartbeat interval sequence of the synchronous heartbeat physiological signal;
and summing the corresponding weighted heartbeat intervals in each weighted heartbeat interval sequence to obtain a final heartbeat interval sequence.
6. The method of claim 5, wherein determining a weight for a sequence of heartbeat intervals of each of the synchronized heartbeat physiological signals comprises:
determining a ratio of a standard deviation to an average value of each heartbeat interval in the heartbeat interval sequence aiming at the heartbeat interval sequence of each synchronous heartbeat physiological signal, and determining a weight coefficient corresponding to the ratio by a table look-up method;
determining the sum of the weight coefficients corresponding to the heartbeat interval sequences of the synchronous heartbeat physiological signals as a total weight coefficient;
determining a ratio of the weight coefficient to the overall weight coefficient as a weight of a sequence of heartbeat intervals of the synchronized heartbeat physiological signal.
7. A heart rate estimation device, comprising:
the acquisition module is used for respectively controlling each heartbeat acquisition device to acquire heartbeat physiological signals of the user;
the preprocessing module is used for preprocessing the heartbeat physiological signals to obtain synchronous heartbeat physiological signals;
the extraction module is used for extracting a heartbeat interval sequence of each synchronous heartbeat physiological signal, wherein the heartbeat interval sequence is a sequence formed by time intervals between every two adjacent wave peaks in the synchronous heartbeat physiological signals;
and the estimation module is used for weighting and summing the heartbeat interval sequences of the synchronous heartbeat physiological signals to obtain a final heartbeat interval sequence, and estimating the heart rate of the user based on the final heartbeat interval sequence.
8. Heart rate estimation device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the program, implements a heart rate estimation method according to any of claims 1-6.
9. A heart rate estimation system, wherein the heart rate detection system comprises: a plurality of heartbeat acquisition devices and a heart rate estimation device according to claim 8 connected to each of the heartbeat acquisition devices; the heartbeat collecting device comprises: the device comprises image acquisition equipment, wearing equipment and an electrode patch;
the image acquisition device is used for acquiring facial heartbeat signals of the user, which are used for representing heartbeat change, based on the control of the heart rate estimation device;
the wearable device is used for collecting the pulse signals of the user based on the control of the heart rate estimation device;
the electrode patch is used for collecting the skin heartbeat signal of the user based on the control of the heart rate estimation equipment.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method of heart rate estimation according to any one of claims 1-6.
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