WO2019000337A1 - 生理信息测量方法、存储介质及生理信息监测装置、设备 - Google Patents
生理信息测量方法、存储介质及生理信息监测装置、设备 Download PDFInfo
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- WO2019000337A1 WO2019000337A1 PCT/CN2017/090910 CN2017090910W WO2019000337A1 WO 2019000337 A1 WO2019000337 A1 WO 2019000337A1 CN 2017090910 W CN2017090910 W CN 2017090910W WO 2019000337 A1 WO2019000337 A1 WO 2019000337A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
Definitions
- the embodiments of the present application relate to physiological information monitoring technologies, and in particular, to a physiological information measuring method, a storage medium, and a physiological information monitoring device and device.
- the separation of the respiratory signal and the heartbeat signal can be realized by the wavelet filter and the adaptive filter, but whether it is a wavelet filter or an adaptive filter, the calculation amount is large.
- the processing time is long and the algorithm has poor real-time performance.
- the purpose of the present application is to provide a physiological information measuring method, a storage medium, and a physiological information monitoring device and device, which can effectively separate a heartbeat signal and a respiratory signal, and has a small amount of calculation and good real-time performance.
- an embodiment of the present application provides a physiological information monitoring apparatus, where the apparatus includes:
- Piezoelectric sensor for receiving a mechanical vibration pressure signal generated by human breathing and heart beat, and converting the mechanical vibration pressure signal into a heartbeat respiratory electric signal;
- control processing unit configured to process the heartbeat respiratory electrical signal
- control processing unit include:
- At least one processor At least one processor
- the processor is in communication with a control internal or external memory of the control processing unit;
- the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:
- the heartbeat breathing sampling signal comprising a mutual interference breathing signal and a heartbeat signal, the breathing signal being a periodic signal, the heartbeat signal being a periodic signal, the breathing The period of the signal is greater than the period of the heartbeat signal;
- the processor of the control processing unit is further capable of:
- the heartbeat separation signal is obtained by subtracting the respiratory separation signal from the heartbeat breath sampling signal.
- the processor of the control processing unit is further capable of:
- Respiratory frequency information is obtained based on the respiratory separation signal.
- the processor of the control processing unit is further capable of:
- Heart rate information is obtained based on the heartbeat separation signal.
- the performing the open operation processing and the closing operation processing on the heartbeat respiratory sampling signal based on the preset structural element including:
- the first signal and the second signal are averaged.
- the embodiment of the present application further provides a physiological information measuring method for monitoring a device, where the method includes:
- the heartbeat breathing sampling signal comprising a mutual interference breathing signal and a heartbeat signal, the breathing signal being a periodic signal, the heartbeat signal being a periodic signal, the breathing The period of the signal is greater than the period of the heartbeat signal;
- the method further includes:
- the heartbeat separation signal is obtained by subtracting the respiratory separation signal from the heartbeat breath sampling signal.
- the method further includes:
- Respiratory frequency information is obtained based on the respiratory separation signal.
- the method further includes:
- Heart rate information is obtained based on the heartbeat separation signal.
- the performing the open operation processing and the closing operation processing on the heartbeat respiratory sampling signal based on the preset structural element including:
- the first signal and the second signal are averaged.
- the embodiment of the present application further provides a storage medium, where the storage medium stores executable instructions, and when the executable instructions are executed by the physiological information monitoring apparatus, the physiological information monitoring apparatus performs the foregoing method. .
- the embodiment of the present application further provides a program product, where the program product includes a program stored on a storage medium, where the program includes program instructions, when the program instruction is executed by the physiological information monitoring device,
- the physiological information monitoring device performs the method of the above claims.
- the embodiment of the present application further provides a physiological information monitoring device, where the physiological information monitoring device includes:
- the monitoring body is configured to carry a part of a human body or a human body; and the physiological information monitoring device described above, wherein the piezoelectric sensor in the physiological information monitoring device is disposed in the monitoring body.
- the monitoring device and the device perform the opening processing and the closing operation processing on the heartbeat breathing sampling signals that interfere with each other, and the opening and closing operations can remove the noise in the signal whose pulse width does not exceed the width of the selected structural element, thereby If the width is greater than or equal to the preset heartbeat period and less than the preset breathing period, the heartbeat signal in the mutually disturbing heartbeat breathing sampling signal can be removed to effectively separate the breathing signal. Since the data processing process only involves addition and subtraction operations, and does not involve multiplication and division operations, the calculation amount is small and the real-time performance is good.
- FIG. 1 is a schematic structural view of a circuit portion of an embodiment of a physiological information monitoring apparatus of the present application
- FIG. 2 is a waveform diagram of a heartbeat signal and a respiratory signal that are not interfered with each other;
- FIG. 3 is a waveform diagram of a heartbeat respiratory signal that interferes with each other;
- FIG. 4 is a schematic flow chart of a physiological information measuring method provided by an embodiment of the present application.
- FIG. 5 is a schematic flowchart of a physiological information measuring method provided by an embodiment of the present application.
- FIG. 6 is a schematic flowchart of a physiological information measuring method provided by an embodiment of the present application.
- FIG. 7 is a schematic structural diagram of a physiological information measuring apparatus according to an embodiment of the present application.
- FIG. 8 is a schematic structural diagram of a physiological information measuring apparatus according to an embodiment of the present application.
- FIG. 9 is a schematic structural diagram of a physiological information monitoring apparatus according to an embodiment of the present application.
- the embodiment of the present application proposes a physiological information monitoring scheme based on a morphological filtering algorithm, which is applicable to the physiological information monitoring device shown in FIG. 1 , and the device uses the same piezoelectric thin film sensor to measure mechanical vibration generated by human respiratory motion and heart beat.
- a pressure signal and converting the mechanical vibration pressure signal into The heartbeat respiratory electric signal is an analog signal;
- the hardware circuit signal processing unit is configured to perform amplification and filtering on the heartbeat respiratory electric signal, and the micro control unit (MCU) algorithm processing unit processes the
- the heartbeat respiratory electric signal processed by the amplification filtering is separated by a morphological filtering algorithm to separate the heartbeat signal and the respiratory signal, thereby obtaining accurate heart rate information and respiratory frequency information.
- the program can be applied to sleep detection equipment such as mattresses, pillows, heart rate monitoring equipment, respiratory frequency monitoring equipment or other equipment that needs to measure heart rate or respiratory rate.
- Mathematical morphology is a mathematical method based on set algebra and quantitative description of geometric structure by set theory. Corrosion and expansion are the two most basic morphological operations in mathematical morphology. Since the heartbeat respiration signal is a one-dimensional gray signal, the gray-scale morphology operation in the one-dimensional discrete case is introduced below.
- the open and close operations smooth the signal in different ways, where the open operation suppresses the peak of the signal (positive pulse) and the closed operation suppresses the valley of the signal (negative pulse).
- the widths of the positive and negative pulses that can be filtered out of the signal f by the open and close operations depend on the width M of the structural element g used for the operation. If the width of the noise pulse in the signal does not exceed the width of the selected structural element, it can be removed by the open and close operations.
- the embodiment of the present application utilizes this feature of the opening and closing operations to separate the heartbeat signal and the respiratory signal. Since normal non-interfering heartbeat signals and respiratory signals are periodic signals, normal adults The heart rate ranges from 50 beats/minute to 100 beats/minute, that is, the heartbeat cycle T1 ranges from 0.6 seconds to 1.2 seconds; the respiratory rate ranges from 12 beats/minute to 25 beats/minute, that is, the respiratory cycle T2 ranges from 2.4 seconds to 5 seconds. second. That is, the breathing cycle is greater than the heartbeat cycle. Therefore, it is possible to set the width of the structural element to be greater than or equal to the heartbeat period and less than the breathing period, so that the heartbeat signal in the heartbeat breathing sampling signal can be filtered out.
- the actual value of the structural element is generally greater than the heartbeat period and not equal to the heartbeat period.
- the signal after the opening and closing operation is the breathing signal, and then the original respiratory heartbeat signal and the respiratory signal before the opening and closing operations are subtracted, and the heartbeat signal can be obtained.
- FIG. 2 the heartbeat signal waveform and the respiratory signal waveform of the human body which do not interfere with each other are shown, wherein the heartbeat signal waveform is shown in the upper part and the respiratory signal waveform in the lower part.
- Figure 3 shows the heartbeat breathing signals that interfere with each other.
- the amplitude of the respiratory signal is relatively large, the frequency is relatively low, and the amplitude of the heartbeat signal is relatively small and the frequency is relatively high, so the influence of the respiratory signal on the heartbeat signal is far greater than the influence of the heartbeat signal on the respiratory signal, thereby The accuracy of heart rate information will also be greatly affected.
- the embodiment of the present application provides a physiological information measuring method, which is used in a physiological information monitoring apparatus, and the method includes:
- Step 101 Acquire a heartbeat breathing sampling signal.
- the heartbeat breathing sampling signal includes a respiratory signal and a heartbeat signal that interfere with each other, the breathing signal is a periodic signal, and the heartbeat signal is a periodic signal, and the period of the respiratory signal is greater than a period of the heartbeat signal.
- a heartbeat breath sampling signal may be acquired by sampling in mutually disturbing respiratory heartbeat signals, and the length of the heartbeat breathing sampling signal may be a plurality of breathing cycles.
- Step 102 Perform an open operation process and a closed operation process on the heartbeat respiratory sampling signal based on a preset structural element to obtain a respiratory separation signal, where a width of the preset structural element is greater than or equal to a preset heartbeat cycle and less than a preset respiratory cycle. ;
- the respiratory separation signal refers to the respiratory signal separated from the heartbeat breathing acquisition signal.
- the heartbeat breathing sampling signal may be first subjected to an open operation process and then subjected to a closed operation process, or the heartbeat breath sampling signal may be first subjected to a closed operation process and then subjected to an open operation process.
- the heartbeat breath sampling signal function is denoted as f
- the structural element function is denoted g
- the morphological filtering operation of signal f with respect to g can be expressed as MF g (f). Then the corresponding two methods are expressed as:
- the signal can be filtered by combining open-closed and closed-on cascaded operations. That is, the heartbeat breathing sampling signal is first subjected to an opening operation process and then subjected to a closing operation process, and the heartbeat breathing sampling signal is first subjected to a closed operation process and then subjected to an open operation process, and then the two operation results are averaged.
- the function is expressed as:
- the opening and closing operations can remove the noise in the signal whose pulse width does not exceed the width of the selected structural element, thereby If the width is greater than or equal to the preset heartbeat period less than the preset breathing period, the heartbeat signal in the heartbeat breathing sampling signal of the respiratory interference can be removed, thereby separating the breathing signal. Since the data processing process only involves addition and subtraction operations, and does not involve multiplication and division operations, the calculation amount is small and the real-time performance is good. Because the method can obtain accurate respiratory frequency information according to the mutually disturbing heartbeat breathing sampling signal, the heartbeat respiratory electrical signal can be collected using only one piezoelectric sensor, which saves hardware cost.
- the method includes: in addition to the step of acquiring the respiratory separation signal, that is, in addition to the step 201 and the step 202 (steps 201 and 202 are specifically referred to step 101 and step 102), the method further includes:
- Step 203 Subtract the heartbeat breathing sampling signal from the respiratory separation signal to obtain a heartbeat separation signal.
- the result of the morphological filtering operation is subtracted from the original heartbeat breathing sampling signal, and the peak-to-valley signal removed from the original heartbeat breathing sampling signal, that is, the heartbeat separation signal, wherein the heartbeat separation signal refers to The heartbeat signal separated from the heartbeat breathing acquisition signal.
- the original heartbeat breathing sampling signal includes a breathing signal and a heartbeat signal
- the breathing separation signal is subtracted from the original heartbeat breathing sampling signal as a heartbeat separation signal.
- the method further includes the steps of acquiring respiratory frequency information and heart rate information, as follows:
- Step 301 Acquire a heartbeat breathing sampling signal
- Step 302 Perform an open operation process and a closed operation process on the heartbeat respiratory sampling signal based on a preset structural element to obtain a respiratory separation signal, where a width of the preset structural element is greater than or equal to a preset heartbeat cycle and less than a preset respiratory cycle. ;
- Step 303 Obtain respiratory frequency information according to the respiratory separation signal.
- Step 304 Subtract the heartbeat breathing sampling signal from the respiratory separation signal to obtain a heartbeat separation signal.
- Step 305 Obtain heart rate information according to the heartbeat separation signal.
- step 303 may also be performed after step 304 or step 305, which is not limited in this application.
- the monitoring device to which the above method is applicable may be a sleep monitoring product, a heart rate monitoring product, a respiratory frequency monitoring product, or other products that need to obtain heart rate information or respiratory frequency information.
- the embodiment of the present application further provides a physiological information measuring device.
- the device includes:
- a sampling module 401 configured to acquire a heartbeat breathing sampling signal
- the signal processing module 402 is configured to perform an open operation process and a closed operation process on the heartbeat respiratory sampling signal based on a preset structural element to obtain a respiratory separation signal, where a width of the preset structural element is greater than or equal to a preset heartbeat period and is less than Preset breathing cycle;
- the performing the open operation processing and the closed operation processing on the heartbeat respiratory sampling signal according to the preset structural element including:
- the first signal and the second signal are averaged.
- the opening and closing operations can remove the noise in the signal whose pulse width does not exceed the width of the selected structural element, thereby If the width is greater than or equal to the preset heartbeat period and less than the preset breathing period, the heartbeat signal in the mutually disturbing heartbeat breathing sampling signal can be removed, thereby separating the breathing signal. Since the data processing process only involves addition and subtraction operations, and does not involve multiplication and division operations, the calculation amount is small and the real-time performance is good.
- the physiological information measuring device includes: in addition to the sampling module 501 and the signal processing module 502,
- the respiratory frequency information obtaining module 503 is configured to obtain respiratory frequency information according to the respiratory separation signal
- a heartbeat signal separation module 504 configured to subtract the heartbeat separation signal from the heartbeat breath sampling signal to obtain a heartbeat separation signal
- the heart rate information obtaining module 505 is configured to obtain heart rate information according to the heartbeat separation signal.
- the foregoing apparatus can perform the method provided by the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
- the foregoing apparatus can perform the method provided by the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
- an embodiment of the present application further provides a physiological information monitoring device 20 .
- the physiological information monitoring device 20 includes a piezoelectric sensor 21 and a control processing unit 23 . among them,
- the piezoelectric sensor 21 is configured to receive a mechanical vibration pressure signal generated by human breathing and heart beat, and convert the mechanical vibration pressure signal into a heartbeat respiratory electric signal.
- the piezoelectric sensor may select a piezoelectric film sensor or other piezoelectric sensor, and the piezoelectric film sensor is sensitive to pressure change of mechanical vibration, and is commonly used in medical fields for human organisms. Measurement of parameters.
- the physiological information monitoring apparatus further includes an analog signal processing unit 22, and the analog signal processing unit 22 is configured to receive a heartbeat respiratory electrical signal sent by the piezoelectric sensor, and to The signal is preprocessed with analog signals.
- the analog signal preprocessing includes analog signal processing such as analog amplification processing and filtering processing.
- the analog signal processing unit 22 may include an analog amplifying subunit 221 for performing analog amplification processing on the heartbeat respiratory electrical signal, and an analog filtering subunit 222 for The heartbeat respiratory electrical signal is subjected to filtering processing.
- the control processing unit 23 is configured to receive a heartbeat respiratory electrical signal, and perform data processing on the cardiac electrical respiratory signal to separate the respiratory separation signal and/or the heartbeat separation signal, and further output heart rate information and/or respiratory frequency information.
- control processing unit 23 can adopt an MCU controller or a digital signal processing (DSP) controller.
- DSP digital signal processing
- the control processing unit 23 includes at least one processor 232 (illustrated by one processor in FIG. 9) and a memory 231, wherein the memory 231 may be built in the control processing unit 23 or externally external to the control processing unit.
- the 231 may also be a remotely located memory, and the control processing unit 23 is connected via a network (the memory is built in the control processing unit in FIG. 9 as an example).
- the processor 232 and the memory 231 may be connected by a bus or other means, as exemplified by a bus connection in FIG.
- the memory 231 is configured to store a non-volatile software program, a non-volatile computer-executable program, and a module, such as a program instruction/module corresponding to the physiological information measurement method in the embodiment of the present application (for example, the sampling shown in FIG. 7) Module 401).
- the processor 232 executes various functional applications and data processing by executing non-volatile software programs, instructions, and modules stored in the memory 231, that is, implementing the physiological information measuring method of the above method embodiments.
- the memory 231 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application required for at least one function; the storage data area may store data created in a process of using the physiological information monitoring device, and the like. Further, the memory 231 may include a high speed random access memory, and may also include a nonvolatile memory such as at least one magnetic disk storage device, a flash memory device, or other nonvolatile solid state storage device. In some embodiments, the memory 231 can optionally include a memory remotely located relative to the processor 232 that can be connected to the physiological information monitoring device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
- the one or more modules are stored in the memory 231, and when executed by the one or more processors 232, perform a physiological information monitoring method in any of the above method embodiments, for example, performing the above described FIG.
- the opening and closing operations can remove the noise in the signal whose pulse width does not exceed the width of the selected structural element, thereby If the width is greater than or equal to the preset heartbeat period and less than the preset breathing period, the heartbeat signal in the heartbeat breathing sampling signal of the respiratory interference can be removed, thereby separating the call Aspirate the signal. Since the data processing process only involves addition and subtraction operations, and does not involve multiplication and division operations, the calculation amount is small and the real-time performance is good.
- the above-mentioned physiological information monitoring apparatus can perform the method provided by the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
- the method provided by the embodiments of the present application can perform the method provided by the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
- the embodiment of the present application provides a storage medium storing computer executable instructions executed by one or more processors, for example, one processor 232 in FIG. 9 may make the above one or
- the plurality of processors may perform the physiological information measuring method in any of the above method embodiments, for example, performing the method steps 101-102 in FIG. 4 described above, the method steps 201 to 203 in FIG. 5, and the method in FIG. Step 301 to step 305; implement the functions of the modules 401-402 in FIG. 7, and the modules 501-505 in FIG.
- the embodiment of the present application provides a physiological information monitoring device, which includes: a monitoring body 10 and the above-described physiological information monitoring device 20, the physiological information monitoring device 20 includes a piezoelectric sensor 21 and control processing. Unit 23.
- the monitoring body 10 is used to carry a part of a human body or a human body, such as a mattress or a pillow.
- the piezoelectric sensor 21 may be placed in the detecting body 10 for receiving a mechanical vibration pressure signal generated by the human respiratory motion and the heart beat, and converting the mechanical vibration pressure signal into a heartbeat respiratory electrical signal.
- the physiological information monitoring device 20 may further include an analog signal processing unit 22 for receiving a heartbeat respiratory electrical signal transmitted by the piezoelectric sensor and performing analog signal preprocessing on the cardiac electrical respiratory signal.
- the control processing unit 23 is configured to receive a heartbeat respiratory electrical signal and perform data processing on the cardiac electrical respiratory signal to separate the respiratory separation signal and/or the heartbeat separation signal to output heart rate information and/or respiratory frequency information.
- the opening and closing operations can remove the noise in the signal whose pulse width does not exceed the width of the selected structural element, thereby If the width is greater than or equal to the preset heartbeat period less than the preset breathing period, the heartbeat signal in the heartbeat breathing sampling signal of the respiratory interference can be removed, thereby separating the breathing signal. Since the data processing process only involves addition and subtraction operations, and does not involve multiplication and division operations, the calculation amount is small and the real-time performance is good.
- the embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, ie may be located in one Places, or they can be distributed to multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
- the embodiments can be implemented by means of software plus a general hardware platform, and of course, by hardware.
- a person skilled in the art can understand that all or part of the process of implementing the above embodiments can be completed by a computer program to instruct related hardware, and the program can be stored in a computer readable storage medium. When executed, the flow of an embodiment of the methods as described above may be included.
- the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).
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Abstract
一种生理信息监测技术、测量方法、存储介质及生理信息监测装置(20)、设备。生理信息监测装置(20)，包括：压电传感器(21)和控制处理单元(23)，控制处理单元(23)用于基于心跳呼吸电信号获取数字化的心跳呼吸采样信号；基于预设结构元素对心跳呼吸采样信号进行开运算处理以及闭运算处理，得到呼吸分离信号，预设结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期。可以去除互相干扰的心跳呼吸采样信号中的心跳信号，以有效分离出呼吸信号。由于数据处理过程只涉及加减运算，不涉及乘除运算，因此计算量小，实时性好。
Description
本申请实施例涉及生理信息监测技术，尤其涉及一种生理信息测量方法、存储介质及生理信息监测装置、设备。
睡眠监测技术已成为现代医学诊断中不可缺少的内容。目前临床睡眠分析的主要手段是分析多导睡眠图,但是生成多导睡眠图至少要在身上粘贴十枚以上的电极，给被测者带来一定的生理心理负荷，反而更加影响睡眠质量，从而基于压电薄膜(Polyvinylidene Fluoride,PVDF)传感器的睡眠监测产品应运而生，该类产品无需在体表粘贴电极即可记录被测者的躯体活动、呼吸活动、心率等情况。
然而，由于压电薄膜传感器自身的特性决定，只要有压力变化，均会转化成相应的电信号。在利用压电薄膜传感器采集人体生理特征信号时，心跳和呼吸均会对其产生压力。因此，采集到的呼吸和心率信号会相互干扰。
目前，为了得到纯净的呼吸信号和心跳信号，可以通过小波滤波器和自适应滤波器来实现对呼吸信号和心跳信号的分离，但无论是小波滤波器还是自适应滤波器，均计算量较大、处理时间长，算法实时性差。
发明内容
本申请的目的在于提供一种生理信息测量方法、存储介质及生理信息监测装置、设备，能够有效的分离心跳信号和呼吸信号，同时计算量小，实时性好。
为实现上述目的，第一方面，本申请实施例提供了一种生理信息监测装置，所述装置包括：
压电传感器：用于接收人体呼吸和心脏跳动产生的机械振动压力信号，并将所述机械振动压力信号转化为心跳呼吸电信号；
控制处理单元，用于对所述心跳呼吸电信号进行处理，所述控制处理单元
包括：
至少一个处理器；
所述处理器与控制处理单元内置或者外置的存储器通信连接；其中，
所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行：
基于所述心跳呼吸电信号获取数字化的心跳呼吸采样信号,所述心跳呼吸采样信号包括相互干扰的呼吸信号与心跳信号，所述呼吸信号为周期信号，所述心跳信号为周期信号，所述呼吸信号的周期大于所述心跳信号的周期；
基于预设结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，得到呼吸分离信号，所述预设结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期。
可选的，所述控制处理单元的处理器还能够执行：
将所述心跳呼吸采样信号减去所述呼吸分离信号得到心跳分离信号。
可选的，所述控制处理单元的处理器还能够执行：
根据所述呼吸分离信号获得呼吸频率信息。
可选的，所述控制处理单元的处理器还能够执行：
根据所述心跳分离信号获得心率信息。
可选的，所述基于预设的结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，包括：
对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理；或者，
对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理；或者，
对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理，获得第一信号；
对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理，获得第二信号；
对所述第一信号和第二信号进行平均处理。
第二方面，本申请实施例还提供了一种生理信息测量方法，用于监测装置，所述方法包括：
获取心跳呼吸采样信号,所述心跳呼吸采样信号包括相互干扰的呼吸信号与心跳信号，所述呼吸信号为周期信号，所述心跳信号为周期信号，所述呼吸
信号的周期大于所述心跳信号的周期；
基于预设结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，得到呼吸分离信号，所述预设结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期。
可选的，所述方法还包括：
将所述心跳呼吸采样信号减去所述呼吸分离信号得到心跳分离信号。
可选的，所述方法还包括：
根据所述呼吸分离信号获得呼吸频率信息。
可选的，所述方法还包括：
根据所述心跳分离信号获得心率信息。
可选的，所述基于预设的结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，包括：
对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理；或者，
对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理；或者，
对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理，获得第一信号；
对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理，获得第二信号；
对所述第一信号和第二信号进行平均处理。
第三方面，本申请实施例还提供了一种存储介质，所述存储介质存储有可执行指令，所述可执行指令被生理信息监测装置执行时，使所述生理信息监测装置执行上述的方法。
第四方面，本申请实施例还提供了一种程序产品，所述程序产品包括存储在存储介质上的程序，所述程序包括程序指令，当所述程序指令被生理信息监测装置执行时，使所述生理信息监测装置执行权利要求上述的方法。
第五方面，本申请实施例还提供了一种生理信息监测设备，所述生理信息监测设备包括：
监测本体，用于承载人体或人体的部位；以及上述的生理信息监测装置，所述生理信息监测装置中的压电传感器设置于所述监测本体中。
本申请实施例提供的生理信息测量方法、存储介质、程序产品及生理信息
监测装置、设备，通过对互相干扰的心跳呼吸采样信号进行开运算处理和闭运算处理，由于开、闭运算可以去除信号中脉冲宽度不超过所选择结构元素的宽度的噪声，因此通过使结构元素的宽度大于或等于预设心跳周期小于预设呼吸周期，就可去除互相干扰的心跳呼吸采样信号中的心跳信号，以有效分离出呼吸信号。由于该数据处理过程只涉及加减运算，不涉及乘除运算，因此计算量小，实时性好。
一个或多个实施例通过与之对应的附图中的图片进行示例性说明，这些示例性说明并不构成对实施例的限定，附图中具有相同参考数字标号的元件表示为类似的元件，除非有特别申明，附图中的图不构成比例限制。
图1是本申请生理信息监测装置的一个实施例的电路部分结构示意图；
图2是互相不受干扰的心跳信号和呼吸信号的波形示意图；
图3是互相干扰的心跳呼吸信号的波形示意图；
图4是本申请实施例提供的生理信息测量方法的流程示意图；
图5是本申请实施例提供的生理信息测量方法的流程示意图；
图6是本申请实施例提供的生理信息测量方法的流程示意图；
图7是本申请实施例提供的生理信息测量装置的结构示意图；
图8是本申请实施例提供的生理信息测量装置的结构示意图；
图9是本申请实施例提供的生理信息监测设备的结构示意图。
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请实施例提出一种基于形态学滤波算法的生理信息监测方案，适用于图1所示的生理信息监测装置，所述装置用同一压电薄膜传感器测量人体呼吸运动和心脏跳动产生的机械振动压力信号，并将所述机械振动压力信号转化为
心跳呼吸电信号，该心跳呼吸电信号为一模拟信号；硬件电路信号处理单元用于对所述心跳呼吸电信号进行放大滤波等处理，微控制单元(Microcontroller Unit，MCU)算法处理单元对该经过放大滤波处理后的心跳呼吸电信号利用形态学滤波算法进行分离处理，以分离出心跳信号和呼吸信号，从而获得准确的心率信息和呼吸频率信息。通过该方案可以减少硬件成本，并且大大的提高压电薄膜(PVDF)传感器类产品测量人体呼吸频率和心率的准确度，同时计算量小、实时性好。该方案可应用于床垫、枕头等睡眠检测设备、心率监测设备、呼吸频率监测设备或者其他需要测量心率或者呼吸频率的设备。
下面首先对数学形态学进行相关说明。
数学形态学是建立在集合代数基础上，用集合论方法定量描述几何结构的一种数学方法。腐蚀和膨胀是数学形态学中最基本的两种形态学运算，由于心跳呼吸信号是一维灰度信号，下面介绍一维离散情况下的灰度形态学运算。
将待处理的心跳呼吸信号f定义为在F＝{0，l，…，N一l}上的离散函数，结构元素g定义为G＝{0，1，…，M一1}上的离散函数,且有N>M。
f关于g的腐蚀
与膨胀⊕运算分别定义为：
基于式(1)和式(2)，f关于g的开运算
和闭运算·相应定义为：
开、闭运算能以不同的方式平滑信号，其中，开运算可抑制信号的波峰(正脉冲)，闭运算可抑制信号的波谷(负脉冲)。开、闭运算从信号f中所能滤除的正、负脉冲的宽度，取决于运算所使用的结构元素g的宽度M。如果信号中噪声脉冲的宽度不超过所选择结构元素的宽度，就可被开、闭运算所去除。
本申请实施例正是利用开、闭运算的这一特性，来分离心跳信号和呼吸信号。由于正常的互不干扰的心跳信号和呼吸信号都是周期性信号，正常的成人
的心率范围为50次/分钟—100次/分钟，即心跳周期T1范围为0.6秒—1.2秒；呼吸率范围为12次/分钟—25次/分钟，即呼吸周期T2范围为2.4秒-5秒。即呼吸周期大于心跳周期。因此，可以设定结构元素的宽度大于或等于心跳周期而小于呼吸周期，这样就可以滤除心跳呼吸采样信号中的心跳信号。在实际应用中，为了更好的滤除心跳呼吸采样信号中的心跳信号，结构元素的实际取值一般大于心跳周期而不等于心跳周期。经过开、闭运算处理之后的信号即为呼吸信号，再将开、闭运算处理前的原始呼吸心跳信号与呼吸信号做减法处理，就能获得心跳信号。
如图2所示，示出了人体正常的互不干扰的心跳信号波形和呼吸信号波形，其中，图2上方为心跳信号波形，下方为呼吸信号波形。图3示出了相互干扰的心跳呼吸信号。从图2可知，由于呼吸信号的振幅比较大，频率比较低，而心跳信号的振幅比较小，频率比较高，因此呼吸信号对心跳信号的影响要远远大于心跳信号对呼吸信号的影响，从而，心率信息的准确性也将受到较大影响。
如图4所示，本申请实施例提供了一种生理信息测量方法，用于生理信息监测装置，所述方法包括：
步骤101：获取心跳呼吸采样信号。
其中，所述心跳呼吸采样信号包括相互干扰的呼吸信号与心跳信号，所述呼吸信号为周期信号，所述心跳信号为周期信号，所述呼吸信号的周期大于所述心跳信号的周期。
在本申请的一个实施例中，可以通过在相互干扰的呼吸心跳电信号中，采样获取一段心跳呼吸采样信号，该段心跳呼吸采样信号的长度可以为包括多个呼吸周期。
步骤102：基于预设结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，得到呼吸分离信号，所述预设结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期；
其中，呼吸分离信号指的是从心跳呼吸采集信号中分离出来的呼吸信号。
具体的，可以对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理，也可以对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理。如果心跳呼吸采样信号函数表示为f，结构元素函数表示为g，信号f关于g的形态学滤波运算可以表示为MFg(f)。则上述两种方式分别对应函数表示为：
和
其中，开运算和闭运算请参照公式(3)和公式(4)。
为有效抑制噪声，降低输出统计偏倚，可采用开-闭、闭-开级联运算组合的方式对信号进行滤波。即对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理，以及对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理，然后对上述两个运算结果进行平均处理。这种方式函数表示为：
本申请实施例，通过对互相干扰的心跳呼吸采样信号进行开运算处理和闭运算处理，由于开、闭运算可以去除信号中脉冲宽度不超过所选择结构元素的宽度的噪声，因此通过使结构元素的宽度大于或等于预设心跳周期小于预设呼吸周期，就可去除呼吸干扰的心跳呼吸采样信号中的心跳信号，从而分离出呼吸信号。由于该数据处理过程只涉及加减运算，不涉及乘除运算，因此计算量小，实时性好。因为该方法可以根据互相干扰的心跳呼吸采样信号获取准确的呼吸频率信息，因此可以仅使用一个压电传感器采集心跳呼吸电信号，节约了硬件成本。
更进一步地，如图5所示，所述方法除了获取呼吸分离信号的步骤，也即除了包含步骤201、步骤202(步骤201与步骤202具体参照步骤101与步骤102)之外，还包括：
步骤203：将所述心跳呼吸采样信号减去所述呼吸分离信号得到心跳分离信号。
即从原始的心跳呼吸采样信号中减去对其进行形态学滤波运算的结果，可得到原始的心跳呼吸采样信号中被去除的峰谷信号，即心跳分离信号，其中，心跳分离信号指的是从心跳呼吸采集信号中分离出来的心跳信号。
可以理解，由于原始的心跳呼吸采样信号包括呼吸信号与心跳信号，当利用步骤101与步骤102获取呼吸分离信号后，从原始的心跳呼吸采样信号中减去该呼吸分离信号即为心跳分离信号。
可选的，在所述方法的其他实施例中，如图6所示，所述方法还包括获取呼吸频率信息和心率信息的步骤，如下：
步骤301：获取心跳呼吸采样信号；
步骤302：基于预设结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，得到呼吸分离信号，所述预设结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期；
步骤303：根据所述呼吸分离信号获得呼吸频率信息；
步骤304：将所述心跳呼吸采样信号减去所述呼吸分离信号得到心跳分离信号；
步骤305：根据所述心跳分离信号获得心率信息。
值得说明的是，上述步骤303也可以在步骤304或步骤305之后执行，本申请不做限制。
其中，上述方法适用的监测装置可以为睡眠监测产品、心率监测产品、呼吸频率监测产品或者其他需要获得心率信息或者呼吸频率信息的产品。
相应的，本申请实施例还提供了一种生理信息测量装置，如图7所示，所述装置包括：
采样模块401，用于获取心跳呼吸采样信号；
信号处理模块402，用于基于预设结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，得到呼吸分离信号，所述预设结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期；
其中，所述根据预设的结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，包括：
对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理；或者，
对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理；或者，
对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理，获得第一信号；
对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理，获得第二信号；
对所述第一信号和第二信号进行平均处理。
本申请实施例，通过对互相干扰的心跳呼吸采样信号进行开运算处理和闭运算处理，由于开、闭运算可以去除信号中脉冲宽度不超过所选择结构元素的宽度的噪声，因此通过使结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期，就可去除相互干扰的心跳呼吸采样信号中的心跳信号，从而分离出呼吸信号。由于该数据处理过程只涉及加减运算，不涉及乘除运算，因此计算量小，实时性好。
如图8所示，为所述生理信息测量装置的又一实施例的结构示意图，在该实施例中，所述生理信息测量装置除了采样模块501、信号处理模块502之外，还包括：
呼吸频率信息获取模块503，用于根据所述呼吸分离信号获得呼吸频率信息；
心跳信号分离模块504，用于将所述心跳呼吸采样信号减去所述呼吸分离信号得到心跳分离信号；
心率信息获取模块505，用于根据所述心跳分离信号获得心率信息。
需要说明的是，上述装置可执行本申请实施例所提供的方法，具备执行方法相应的功能模块和有益效果。未在本实施例中详尽描述的技术细节，可参见本申请实施例所提供的方法。
请参照图9，本申请实施例还提供了一种生理信息监测装置20，生理信息监测装置20包括压电传感器21和控制处理单元23。其中，
压电传感器21用于接收人体呼吸和心脏跳动产生的机械振动压力信号，并将所述机械振动压力信号转化为心跳呼吸电信号。
可选的，在某些实施例中，所述压电传感器可以选择压电薄膜传感器或者其他压电传感器，压电薄膜传感器对机械振动的压力变化感测非常灵敏，常用于医疗领域对人体生物参数的测量。
可选的，在某些实施例中，所述生理信息监测装置还包括模拟信号处理单元22，模拟信号处理单元22用于接收压电传感器发送的心跳呼吸电信号，并对所述心跳呼吸电信号进行模拟信号预处理。具体地，该模拟信号预处理包括模拟放大处理与滤波处理等模拟信号处理。
可选地，在本申请的一个实施例中，该模拟信号处理单元22可以包括模拟放大子单元221，用于对所述心跳呼吸电信号进行模拟放大处理，模拟滤波子单元222，用于对所述心跳呼吸电信号进行滤波处理。
控制处理单元23用于接收心跳呼吸电信号，并对所述心跳呼吸电信号进行数据处理分离出呼吸分离信号和/或心跳分离信号，以及进一步输出心率信息和/或呼吸频率信息。
可选的，控制处理单元23可以采用MCU控制器或者数字信号处理(Digital Signal Processing，DSP)控制器。
控制处理单元23包括：至少一个处理器232(图9中以一个处理器举例说明)和存储器231，其中，存储器231可以内置在控制处理单元23中，也可以外置在控制处理单元外部，存储器231还可以是远程设置的存储器，通过网络连接所述控制处理单元23(图9中以存储器内置于控制处理单元为例说明)。处理器232和存储器231可以通过总线或者其他方式连接，图9中以通过总线连接为例。
存储器231用于存储非易失性软件程序、非易失性计算机可执行程序以及模块，如本申请实施例中的生理信息测量方法对应的程序指令/模块(例如，附图7所示的采样模块401)。处理器232通过运行存储在存储器231中的非易失性软件程序、指令以及模块，从而执行各种功能应用以及数据处理，即实现上述方法实施例的生理信息测量方法。
存储器231可以包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需要的应用程序；存储数据区可存储使用生理信息监测装置的过程中所创建的数据等。此外，存储器231可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。在一些实施例中，存储器231可选包括相对于处理器232远程设置的存储器，这些远程存储器可以通过网络连接至生理信息监测装置。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
所述一个或者多个模块存储在所述存储器231中，当被所述一个或者多个处理器232执行时，执行上述任意方法实施例中的生理信息监测方法，例如，执行以上描述的图4中的方法步骤101-102，图5中的方法步骤201至步骤203，图6中的方法步骤301至步骤305；实现图7中的模块401-402，图8中模块501-505的功能。
本申请实施例，通过对互相干扰的心跳呼吸采样信号进行开运算处理和闭运算处理，由于开、闭运算可以去除信号中脉冲宽度不超过所选择结构元素的宽度的噪声，因此通过使结构元素的宽度大于或等于预设心跳周期小于预设呼吸周期，就可去除呼吸干扰的心跳呼吸采样信号中的心跳信号，从而分离出呼
吸信号。由于该数据处理过程只涉及加减运算，不涉及乘除运算，因此计算量小，实时性好。
上述生理信息监测装置可执行本申请实施例所提供的方法，具备执行方法相应的功能模块和有益效果。未在本实施例中详尽描述的技术细节，可参见本申请实施例所提供的方法。
本申请实施例提供了一种存储介质，所述存储介质存储有计算机可执行指令，该计算机可执行指令被一个或多个处理器执行，例如图9中的一个处理器232可使得上述一个或多个处理器可执行上述任意方法实施例中的生理信息测量方法，例如，执行以上描述的图4中的方法步骤101-102，图5中的方法步骤201至步骤203，图6中的方法步骤301至步骤305；实现图7中的模块401-402，图8中模块501-505的功能。
请参照图9，本申请实施例提供了一种生理信息监测设备，所述设备包括：监测本体10和上述的生理信息监测装置20，所述生理信息监测装置20包括压电传感器21和控制处理单元23。其中，监测本体10用于承载人体或人体的部位，例如床垫或者枕头等。压电传感器21可以放置在检测本体10中，用于接收人体呼吸运动和心脏跳动产生的机械振动压力信号，并将所述机械振动压力信号转化为心跳呼吸电信号。所述生理信息监测装置20还可以包括模拟信号处理单元22，用于接收压电传感器发送的心跳呼吸电信号，并对所述心跳呼吸电信号进行模拟信号预处理。控制处理单元23用于接收心跳呼吸电信号，并对所述心跳呼吸电信号进行数据处理分离出呼吸分离信号和/或心跳分离信号，以输出心率信息和/或呼吸频率信息。
本申请实施例，通过对互相干扰的心跳呼吸采样信号进行开运算处理和闭运算处理，由于开、闭运算可以去除信号中脉冲宽度不超过所选择结构元素的宽度的噪声，因此通过使结构元素的宽度大于或等于预设心跳周期小于预设呼吸周期，就可去除呼吸干扰的心跳呼吸采样信号中的心跳信号，从而分离出呼吸信号。由于该数据处理过程只涉及加减运算，不涉及乘除运算，因此计算量小，实时性好。
以上所描述的实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。
通过以上的实施例的描述，本领域普通技术人员可以清楚地了解到各实施例可借助软件加通用硬件平台的方式来实现，当然也可以通过硬件。本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程是可以通过计算机程序来指令相关的硬件来完成，所述的程序可存储于一计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实施例的流程。其中，所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory,ROM)或随机存储记忆体(Random Access Memory,RAM)等。
最后应说明的是：以上实施例仅用以说明本申请的技术方案，而非对其限制；在本申请的思路下，以上实施例或者不同实施例中的技术特征之间也可以进行组合，步骤可以以任意顺序实现，并存在如上所述的本申请的不同方面的许多其它变化，为了简明，它们没有在细节中提供；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的范围。
Claims (12)
- 一种生理信息监测装置，其特征在于，所述装置包括：压电传感器，用于接收人体呼吸和心脏跳动产生的机械振动压力信号，并将所述机械振动压力信号转化为心跳呼吸电信号；控制处理单元，用于对所述心跳呼吸电信号进行处理，所述控制处理单元包括：至少一个处理器；所述处理器与控制处理单元内置或者外置的存储器通信连接；其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行：基于所述心跳呼吸电信号获取数字化的心跳呼吸采样信号,所述心跳呼吸采样信号包括相互干扰的呼吸信号与心跳信号，所述呼吸信号为周期信号，所述心跳信号为周期信号，所述呼吸信号的周期大于所述心跳信号的周期；基于预设结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，得到呼吸分离信号，所述预设结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期。
- 根据权利要求1所述的监测装置，其特征在于，所述控制处理单元的处理器还能够执行：将所述心跳呼吸采样信号减去所述呼吸分离信号得到心跳分离信号。
- 根据权利要求1所述的监测装置，其特征在于，所述控制处理单元的处理器还能够执行：根据所述呼吸分离信号获得呼吸频率信息。
- 根据权利要求2所述的监测装置，其特征在于，所述控制处理单元的处理器还能够执行：根据所述心跳分离信号获得心率信息。
- 根据权利要求1-4任一项所述的监测装置，其特征在于，所述基于预设的结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，包括：对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理；或者，对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理；或者，对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理，获得第一信号；对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理，获得第二信号；对所述第一信号和第二信号进行平均处理。
- 一种生理信息测量方法，其特征在于，所述方法包括：获取心跳呼吸采样信号,所述心跳呼吸采样信号包括相互干扰的呼吸信号与心跳信号，所述呼吸信号为周期信号，所述心跳信号为周期信号，所述呼吸信号的周期大于所述心跳信号的周期；基于预设结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，得到呼吸分离信号，所述预设结构元素的宽度大于或等于预设心跳周期且小于预设呼吸周期。
- 根据权利要求6所述的生理信息测量方法，其特征在于，所述方法还包括：将所述心跳呼吸采样信号减去所述呼吸分离信号得到心跳分离信号。
- 根据权利要求6所述的生理信息测量方法，其特征在于，所述方法还包括：根据所述呼吸分离信号获得呼吸频率信息。
- 根据权利要求7所述的生理信息测量方法，其特征在于，所述方法还包括：根据所述心跳分离信号获得心率信息。
- 根据权利要求6-9任一项所述的生理信息测量方法，其特征在于，所述基于预设的结构元素对所述心跳呼吸采样信号进行开运算处理以及闭运算处理，包括：对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理；或者，对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理；或者，对所述心跳呼吸采样信号先进行开运算处理再进行闭运算处理，获得第一信号；对所述心跳呼吸采样信号先进行闭运算处理再进行开运算处理，获得第二信号；对所述第一信号和第二信号进行平均处理。
- 一种存储介质，其特征在于，所述存储介质存储有可执行指令，所述可执行指令被生理信息监测装置执行时，使所述生理信息监测装置执行权利要求6-10任一项所述的方法。
- 一种生理信息监测设备，其特征在于，所述生理信息监测设备包括：监测本体，用于承载人体或人体的部位；以及权利要求1-5的任一项所述的生理信息监测装置，所述生理信息监测装置中的压电传感器设置于所述监测本体中。
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