CN114431841A - Pulse signal detection method, wearable device and storage medium - Google Patents
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Abstract
The invention is suitable for the technical field of pulse detection, and provides a pulse signal detection method, wearable equipment and a storage medium.
Description
Technical Field
The invention belongs to the technical field of pulse detection, and particularly relates to a pulse signal detection method, wearable equipment and a storage medium.
Background
The pulse is an artery pulse which can be touched on the superficial surface of a human body, and the existing pulse detection technology can be divided into ear artery pulse detection, brachial artery pulse detection, radial artery pulse detection, finger tip artery pulse detection and the like on the basis of detection positions; the pulse detection sensor can be classified into a photoelectric sensor, a pressure sensor, and the like. The photoelectric pulse sensor converts the change of light transmittance of the blood vessel in the pulse beating process into an electric signal to be output, and the pressure type pulse sensor converts the pressure change generated in the artery beating process into an electric signal to be output.
The wearable equipment that uses commonly in daily life such as bracelet, earphone, no matter when motion or leisure, all can facilitate the use. The method for detecting the pulse through the wearable device becomes an effective method for monitoring the health condition of people, and the pulse detection technology based on the wearable device has important significance for enriching the application scene of the wearable device and improving the comfort and the convenience of pulse detection. Currently, wearable devices typically detect pulse by means of photoelectric or pressure type sensors.
Disclosure of Invention
In view of this, embodiments of the present invention provide a pulse signal detection method, a wearable device, and a storage medium, which can acquire pulse data of a human body through a three-axis acceleration sensor, and perform filtering processing on Z-axis data of the three-axis acceleration sensor to obtain a pulse signal of the human body, and the detection method is simple and has high accuracy.
The first aspect of the embodiments of the present invention provides a pulse signal detection method, which is applied to wearable equipment, and the pulse signal detection method includes:
acquiring pulse data of a human body through a three-axis acceleration sensor, wherein the pulse data comprises Z-axis data of the three-axis acceleration sensor;
and filtering the Z-axis data to obtain a pulse signal of the human body.
A second aspect of the embodiments of the present invention provides a wearable device, including a data processing module, and a data acquisition module, a power module, and a storage module connected to the data processing module, where the data acquisition module includes a triaxial acceleration sensor, the storage module stores therein a computer program operable on the data processing module, and the data processing module implements, when executing the computer program, the steps of the pulse signal detection method according to the first aspect of the embodiments of the present invention.
A third aspect of embodiments of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the pulse signal detection method according to the first aspect of embodiments of the present invention.
According to the pulse signal detection method provided by the first aspect of the embodiment of the invention, the pulse data of the human body is acquired through the three-axis acceleration sensor of the wearable device, and the Z-axis data of the three-axis acceleration sensor included in the pulse data is filtered to obtain the pulse signal of the human body.
It is to be understood that, the beneficial effects of the second aspect and the third aspect may refer to the relevant description in the first aspect, and are not described herein again.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a first flowchart illustrating a pulse signal detection method according to an embodiment of the present invention;
FIG. 2 is a second flowchart illustrating a pulse signal detection method according to an embodiment of the present invention;
FIG. 3 is a third flowchart illustrating a method for detecting a pulse signal according to an embodiment of the present invention;
FIG. 4 is a fourth flowchart illustrating a pulse signal detecting method according to an embodiment of the present invention;
FIG. 5 is a fifth flowchart illustrating a pulse signal detecting method according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a wearable device provided in an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present invention and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present invention. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
The pulse signal detection method provided by the embodiment of the invention can be applied to wearable devices such as an ear-hang earphone, an intelligent ring (e.g., an intelligent neck ring, an intelligent bracelet, an intelligent ring, an intelligent foot ring and the like), intelligent glasses with the ear-hang earphone, and an intelligent helmet with the ear-hang earphone, wherein the intelligent glasses with the ear-hang earphone and the intelligent helmet with the ear-hang earphone can be Augmented Reality (AR) or Virtual Reality (VR) devices.
As shown in fig. 1, the pulse signal detecting method according to the embodiment of the present invention includes:
s101, pulse data of a human body are acquired through a three-axis acceleration sensor, wherein the pulse data comprise Z-axis data of the three-axis acceleration sensor;
and S102, filtering the Z-axis data to obtain a pulse signal of the human body.
In application, the three-axis acceleration sensor may be an existing device already existing in the wearable device, and for the wearable device without the three-axis acceleration sensor, the three-axis acceleration sensor may be additionally added to the wearable device. The three-axis acceleration sensor can be used for collecting pulse data of a human body and motion data of the human body during motion. The sampling frequency of the triaxial acceleration sensor can be set according to actual needs, for example, 500 Hz.
It should be understood that the pulse data and the motion data are actually acceleration data collected by a three-axis acceleration sensor, the acceleration data specifically includes two indexes, namely an acceleration value and an acceleration direction, the acceleration direction includes an X-axis direction, a Y-axis direction and a Z-axis direction of the acceleration sensor, and the acceleration value includes acceleration components in the three directions, namely, an X-axis component, a Y-axis component and a Z-axis component. The directions of the X axis, the Y axis and the Z axis of the three-axis acceleration sensor can be defined according to actual needs, for example, the direction of the X axis is defined as the horizontal plane direction, the direction of the Y axis is defined as the gravity direction, and the direction of the Z axis is defined as the direction perpendicular to the X axis and the Y axis.
In application, a user can set the three-axis acceleration sensor to be only used for acquiring pulse data or motion data of human body motion in a certain preset time period through any human-computer interaction mode supported by the wearable device according to actual needs. For example, the three-axis acceleration sensor may be set for collecting pulse data when the human body is in a stationary state (e.g., standing, sitting, or sleeping state); when the human body is in a non-stationary state (e.g., walking, running, jumping), the three-axis acceleration sensor is configured to acquire motion data.
In one embodiment, the pulse signal detection method further includes:
setting the triaxial acceleration sensor to be used for acquiring pulse data in a first preset time period, wherein the first preset time period comprises the time when the human body is in a static state;
and setting the three-axis acceleration sensor to be used for acquiring motion data of the human body during motion in a second preset time period, wherein the second preset time period comprises the time when the human body is in a non-static state.
On the other hand, the artery pulsation amplitude of the human body is far smaller than the motion amplitude of the human body during motion, and the acceleration value of the triaxial acceleration sensor during collection of the pulse data is far smaller than the acceleration value during collection of the motion data, so that a first acceleration threshold value and a second acceleration threshold value can be set, and when the acceleration value of the acceleration data collected by the triaxial acceleration sensor is smaller than the first acceleration threshold value, the acceleration data collected by the triaxial acceleration sensor is taken as the pulse data; and when the acceleration value of the acceleration data acquired by the triaxial acceleration sensor is greater than a second acceleration threshold value, taking the acceleration data acquired by the triaxial acceleration sensor as the motion data, wherein the first acceleration threshold value is far smaller than the second acceleration threshold value.
In one embodiment, the pulse signal detection method further includes:
acquiring an acceleration value of acceleration data acquired by a triaxial acceleration sensor;
when the acceleration value is smaller than a first acceleration threshold value, taking acceleration data acquired by a three-axis acceleration sensor as pulse data;
when the acceleration value is larger than a second acceleration threshold value, taking acceleration data acquired by a three-axis acceleration sensor as motion data;
wherein the first acceleration threshold is much smaller than the second acceleration threshold.
In application, the Z-axis data in step S101 and step S102 particularly refers to a Z-axis component of an acceleration value in the acceleration data acquired by the three-axis acceleration sensor when the three-axis acceleration sensor is used for acquiring pulse data, and the pulse data may further include an X-axis component and a Y-axis component of the acceleration value. The Z-axis direction is the pulse direction of the human artery.
As shown in fig. 2, in one embodiment, step S102 includes:
step S201, performing band-pass filtering on the Z-axis data through a band-pass filter to obtain a pulse signal of a human body;
or, in step S202, the Z-axis data is low-pass filtered by a low-pass filter to obtain a pulse signal of the human body.
In application, a software-based filter or a hardware filter can be adopted to perform filtering processing on the Z-axis data, and noise in the original data is removed to obtain an accurate pulse signal. The filter can be a band-pass filter or a low-pass filter according to actual needs, for example, a Kaiser (Kaiser) window band-pass filter with a cut-off frequency of 0.5Hz-12Hz, a Butterworth (Butterworth) low-pass filter with a cut-off frequency of 12Hz, and the like.
As shown in fig. 3, in one embodiment, step S201 includes:
s301, acquiring time series data of the Z-axis data;
step S302, according to a preset pulse period, performing band-pass filtering on the time sequence data through a Kaiser window band-pass filter to obtain a pulse signal of a human body;
step S202 includes:
and S303, performing low-pass filtering on the Z-axis data through a Butterworth low-pass filter to obtain a pulse signal of the human body.
In application, the preset pulse period is in a range of a normal pulse (or heart rate) period of a human body, and the preset pulse period is used for setting a cut-off frequency of the band-pass filter. The time sequence data of the Z-axis data is data obtained by arranging Z-axis components in the pulse data acquired by the triaxial acceleration sensor according to the time sequence.
In application, the Kaiser window band-pass filter is used for carrying out band-pass filtering on the time series data, and signals such as high-frequency pulse noise, narrow-band noise and the like can be filtered out, so that the pulse signal with baseline drift and power frequency interference removed is obtained. The low pass filtering of the time series data by means of a butterworth low pass filter has a similar filtering effect as the casser window band pass filter.
As shown in fig. 4, in one embodiment, step S302 includes:
and S401, convolving the time sequence data with the unit impulse response of the Kaiser window band-pass filter to obtain the pulse signal of the human body.
In application, the convolution formula of the pulse signal of the human body obtained based on step S401 is as follows:
wherein P1(t) is a pulse signal of a human body, h (N) is a unit impulse response of the Kaiser window band-pass filter, X (t) is the time sequence data, N is a window length of a Kaiser window function of the Kaiser window band-pass filter, and N is greater than or equal to 0 and less than or equal to N-1.
As shown in fig. 4, in one embodiment, before step S401, the method includes:
step S402, obtaining the unit impulse response of the Kaiser window band-pass filter according to the Kaiser window function of the Kaiser window band-pass filter and the target frequency response function of the ideal band-pass filter.
In application, the formula for obtaining the unit impulse response of the cassar window band-pass filter based on step S402 is as follows:
h(n)＝hd(n)wk(n)；
wherein h (n) is the unit impulse response of the Kaiser window band-pass filter, wk(n) is the Kaiser window function, h, of the Kaiser window band-pass filterd(n) is a target frequency response function of the ideal band pass filter.
In application, the expansion of the Kaiser window function of a Kaiser window band-pass filter is as follows:
wherein, wk(n) is the Kaiser window function of the Kaiser window band-pass filter, I0(x) Is a modified zero-order Bessel function of the first kind, I0(x) The expansion of (a) is as follows:
n and beta can be obtained by the preset transition bandwidth and the preset stop band attenuation of the Kaiser window band-pass filter, and the obtaining formula of N and beta is as follows:
wherein, the preset transition bandwidth Δ ω is 0.4(2 pi/500), and the preset stop band attenuation as＝60dB。
As shown in fig. 4, in one embodiment, before step S402, the method includes:
step S403, obtaining window length and shape parameters of a Kaiser window function of the Kaiser window band-pass filter according to a preset transition bandwidth and preset stop band attenuation of the Kaiser window band-pass filter;
step S404, according to the window length, the preset upper cut-off frequency and the preset lower cut-off frequency of the Kaiser window function, the frequency response function of the ideal band-pass filter is transformed, and the target frequency response function of the ideal band-pass filter is obtained.
In application, the expansion of the target frequency response function of an ideal band-pass filter is as follows:
wherein h isd(N) is a target frequency response function of the ideal band-pass filter, a is (N-1)/2, and an upper cutoff frequency omega is presetc10.2 (pi/500), preset lower cut-off frequency ωc2＝24(π/500)，0≤n≤N-1。
As shown in fig. 5, in an embodiment, after step S102, the method further includes:
step S501, taking an absolute value of the pulse signal P1(t) to obtain a pulse signal P2(t) with all positive amplitudes;
step S502, carrying out moving average smoothing treatment on a preset number of data points on the pulse signals P2(t) with all positive amplitudes to obtain the human pulse wave signals P (t) after noise reduction;
step S503, performing waveform feature extraction on the pulse wave signal p (t), to obtain a waveform feature.
In application, the waveform characteristics include at least one of pulse rate, peak, trough, etc., and the pulse rate can be calculated according to the number of peaks per unit time or the time interval between two adjacent peaks in the pulse wave signal.
In application, in step S502, the moving average smoothing process of a preset number of data points is performed on the pulse wave signals P2(t) with all positive amplitudes, and the formula of the pulse wave signals P (t) of the human body after noise reduction is obtained as follows:
P(t)＝(P2t-1+P2t-2+P2t-3+…+P2t-n)/n；
wherein P (t) is the pulse wave signal of the human body after noise reduction, P2tThe amplitude of the pulse signal P2(t) at time t, whose amplitudes are all positive, is equal to n 150.
In one embodiment, the pulse signal detection method further includes:
and sending the pulse signal and/or the pulse wave signal to a user terminal.
In an application, the wearable device may communicate with the user terminal through its communication module to send the pulse signal and the pulse wave signal to the user terminal. Wearable equipment and user terminal can all possess the arbitrary human-computer interaction mode of accessible its support, inform the function of user with pulse signal and pulse wave signal, can also carry out the storage to pulse signal and pulse wave signal through storage module. The man-machine interaction mode can be that the pulse signals and the pulse wave signals are displayed through a display screen or broadcasted through a voice device.
In application, the Communication module may include a Wireless Local Area Network (WLAN) (e.g., a Wi-Fi network) module, a bluetooth module, a Zigbee module, a mobile Communication network module, a Global Navigation Satellite System (GNSS) module, a Frequency Modulation (FM) module, a Near Field Communication (NFC) module, an Infrared (IR) module, and the like. The communication module may be one or more devices integrating at least one communication processing module. The communication module may include an antenna, and the antenna may have only one array element, or may be an antenna array including a plurality of array elements. The communication module can receive electromagnetic waves through the antenna, frequency modulation and filtering processing are carried out on electromagnetic wave signals, and the processed signals are sent to the data processing module of the wearable device. The communication module can also receive a signal to be sent from the data processing module, frequency-modulate and amplify the signal, and convert the signal into electromagnetic wave to radiate the electromagnetic wave through the antenna.
In Application, the data Processing module may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In an application, the storage module of the wearable device may be an internal storage unit of the wearable device, such as a wearable device memory. The memory module may also be an external memory device of the wearable device, such as a Smart Media Card (SMC), Secure Digital (SD) Card, Flash memory Card (Flash Card), or the like provided on the wearable device. Further, the memory module may also include both an internal memory unit and an external memory device. The storage module is used for storing an operating system, an application program, a Boot Loader (Boot Loader), data, other programs, and the like, such as program codes of the computer programs. The storage module may also be used to temporarily store data that has been output or is to be output.
In application, the user terminal may be a Mobile phone, a tablet Computer, a vehicle-mounted device, an augmented reality or virtual reality device, a notebook Computer, an Ultra-Mobile Personal Computer (UMPC), a netbook, a Personal Digital Assistant (PDA), and the like.
According to the pulse signal detection method provided by the embodiment of the invention, the pulse data of the human body is acquired through the three-axis acceleration sensor of the wearable device, and the Z-axis data of the three-axis acceleration sensor included in the pulse data is filtered to obtain the pulse signal of the human body.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The embodiment of the invention also provides a pulse signal detection device, which is used for executing the steps in the pulse signal detection method embodiment. The pulse signal detection device may be a virtual appliance (virtual application) in the wearable device, operated by a data processing module of the wearable device, or may be the wearable device itself. The pulse signal detection device includes:
the device comprises a collecting unit, a processing unit and a processing unit, wherein the collecting unit is used for collecting pulse data of a human body through a three-axis acceleration sensor, and the pulse data comprises Z-axis data of the three-axis acceleration sensor;
and the processing unit is used for carrying out filtering processing on the Z-axis data to obtain a pulse signal of the human body.
In one embodiment, the acquisition unit is further configured to:
setting the triaxial acceleration sensor to be used for acquiring pulse data in a first preset time period, wherein the first preset time period comprises the time when the human body is in a static state;
and setting the three-axis acceleration sensor to be used for acquiring motion data of the human body during motion in a second preset time period, wherein the second preset time period comprises the time when the human body is in a non-static state.
In one embodiment, the acquisition unit is further configured to:
acquiring an acceleration value of acceleration data acquired by a triaxial acceleration sensor;
when the acceleration value is smaller than a first acceleration threshold value, taking acceleration data acquired by a three-axis acceleration sensor as pulse data;
when the acceleration value is larger than a second acceleration threshold value, taking acceleration data acquired by a three-axis acceleration sensor as motion data;
wherein the first acceleration value is much smaller than the second acceleration value.
In one embodiment, the processing unit is further configured to obtain a unit impulse response of the kaiser window band-pass filter according to a kaiser window function of the kaiser window band-pass filter and a target frequency response function of the ideal band-pass filter.
In one embodiment, the processing unit is further configured to:
according to a preset transition bandwidth and preset stop band attenuation of the Kaiser window band-pass filter, obtaining window length and shape parameters of a Kaiser window function of the Kaiser window band-pass filter;
and transforming the frequency response function of the ideal band-pass filter according to the window length, the preset upper cut-off frequency and the preset lower cut-off frequency of the Kaiser window function to obtain the target frequency response function of the ideal band-pass filter.
In one embodiment, the processing unit is further configured to:
taking an absolute value of the pulse signals to obtain the pulse signals with all positive amplitudes;
carrying out moving average smoothing treatment on the pulse signals with all positive amplitudes on a preset number of data points to obtain the pulse wave signals of the human body after noise reduction;
and extracting waveform characteristics of the pulse wave signals to obtain the waveform characteristics.
In one embodiment, the pulse signal detection apparatus further includes:
and the communication unit is used for transmitting the pulse signal and/or the pulse wave signal to a user terminal.
In application, each module in the pulse signal detection device may be a software program module, may also be implemented by different logic circuits integrated in the data processing module, and may also be implemented by a plurality of distributed processors, for example, the acquisition unit, the processing unit, and the communication unit are respectively a data acquisition module, a data processing module, and a communication module of the wearable device.
As shown in fig. 6, the wearable device 100 provided by the present invention includes a data processing module 1, and a data acquisition module 2, a power supply module 3, and a storage module 4 connected to the data processing module 1, where the data acquisition module 2 includes a triaxial acceleration sensor 21, the storage module 4 stores a computer program operable on the data processing module, and the data processing module 1 implements the steps of the pulse signal detection method in the above embodiment when executing the computer program.
As shown in fig. 6, in one embodiment, the wearable device 100 further comprises a communication module 5 connected to the data processing module 1, the communication module 5 is used for communicating with the user terminal 200 to transmit the pulse signal to the user terminal 200.
In an application, the wearable device may further include a human-computer interaction module such as a display screen, keys, voice devices (e.g., microphone, speaker), etc. When the wearable device is or includes an ear-hook earphone, it necessarily includes a microphone, a speaker, and other speech devices.
In application, the power module can be a battery or receive power input of the battery, a charger and the like, and supplies power to the data processing module, the data acquisition module, the storage module, the communication module, the human-computer interaction module and the like.
In one embodiment, the wearable device is or includes an ear-hook earphone, and the three-axis acceleration sensor is in contact with an ear artery of the human body to acquire pulse data at the ear artery when the human body wears the wearable device.
In one embodiment, the wearable device comprises two of said three-axis acceleration sensors when being an ear-hook headset; the three-axis acceleration sensor is arranged at the position where the ear-hung earphone is contacted with the ear artery of one ear of the user and is used for acquiring the pulse data of the ear artery of one ear of the user; the other three-axis acceleration sensor is arranged at the position where the ear-hung earphone is in contact with the ear artery of the other ear of the user and is used for acquiring the pulse data of the ear artery of the other ear of the user.
In application, the pulse data of the two ear arteries are collected, the two pulse signals and the two pulse waveform signals can be obtained through processing respectively, and then the pulse signal and the pulse waveform signal with the better quality in the two pulse signals and the two pulse waveform signals are selected to inform a user.
It should be noted that, because the contents of information interaction, execution process, and the like between the above-mentioned apparatuses/units are based on the same concept as the method embodiment of the present invention, specific functions and technical effects thereof can be referred to specifically in the method embodiment section, and are not described herein again.
It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the apparatus may be divided into different functional units or modules to perform all or part of the above described functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
An embodiment of the present invention further provides a network device, where the network device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, the processor implementing the steps in the various pulse signal detection method embodiments described above when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps in the above-mentioned embodiments of the pulse signal detection method.
Embodiments of the present invention provide a computer program product, which, when running on a wearable device, enables the wearable device to implement the steps in the above-mentioned pulse signal detection method embodiments when executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may be implemented by a computer program, which may be stored in a computer-readable storage medium and used for instructing related hardware to implement the steps of the embodiments of the method according to the embodiments of the present invention. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or apparatus capable of carrying computer program code to a wearable device, a recording medium, computer Memory, Read-Only Memory (ROM), Random-Access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided by the present invention, it should be understood that the disclosed apparatus/device and method can be implemented in other ways. For example, the above-described apparatus/device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A pulse signal detection method is applied to wearable equipment and comprises the following steps:
acquiring pulse data of a human body through a three-axis acceleration sensor, wherein the pulse data comprises Z-axis data of the three-axis acceleration sensor;
and filtering the Z-axis data to obtain a pulse signal of the human body.
2. The method for detecting pulse signals according to claim 1, wherein the filtering the Z-axis data to obtain the pulse signals of the human body comprises:
and performing band-pass filtering on the Z-axis data through a band-pass filter to obtain a pulse signal of the human body, or performing low-pass filtering on the Z-axis data through a low-pass filter to obtain the pulse signal of the human body.
3. The method for detecting pulse signals according to claim 2, wherein the band-pass filtering the Z-axis data by a band-pass filter to obtain the pulse signals of the human body comprises:
acquiring time series data of the Z-axis data;
according to a preset pulse period, performing band-pass filtering on the time sequence data through a Kaiser window band-pass filter to obtain a pulse signal of the human body;
the low-pass filtering is performed on the Z-axis data through a low-pass filter to obtain a pulse signal of a human body, and the method comprises the following steps:
and carrying out low-pass filtering on the Z-axis data through a Butterworth low-pass filter to obtain a pulse signal of the human body.
4. The pulse signal detecting method according to claim 3, wherein the band-pass filtering the time-series data by a Caesar window band-pass filter to obtain the pulse signal of the human body comprises:
and convolving the time sequence data with the unit impulse response of the Kaiser window band-pass filter to obtain the pulse signal of the human body.
5. The pulse signal detection method according to claim 4, wherein before convolving the time-series data with a unit impulse response of a Kaiser window band-pass filter to obtain the pulse signal of the human body, the method comprises:
and obtaining the unit impulse response of the Kaiser window band-pass filter according to the Kaiser window function of the Kaiser window band-pass filter and the target frequency response function of the ideal band-pass filter.
6. The pulse signal detecting method according to claim 5, wherein before obtaining the unit impulse response of the Kaiser window band-pass filter based on the Kaiser window function of the Kaiser window band-pass filter and the target frequency response function of the ideal band-pass filter, the method comprises:
according to a preset transition bandwidth and preset stop band attenuation of the Kaiser window band-pass filter, obtaining window length and shape parameters of a Kaiser window function of the Kaiser window band-pass filter;
and transforming the frequency response function of the ideal band-pass filter according to the window length, the preset upper cut-off frequency and the preset lower cut-off frequency of the Kaiser window function to obtain the target frequency response function of the ideal band-pass filter.
7. The method for detecting pulse signals according to any one of claims 1 to 6, wherein the filtering the Z-axis data to obtain the pulse signals of the human body comprises:
taking an absolute value of the pulse signals to obtain the pulse signals with all positive amplitudes;
carrying out moving average smoothing treatment on the pulse signals with all positive amplitudes on a preset number of data points to obtain the pulse wave signals of the human body after noise reduction;
and extracting waveform characteristics of the pulse wave signals to obtain waveform characteristics, wherein the waveform characteristics comprise at least one of pulse rate, wave crest and wave trough.
8. Wearable device, comprising a data processing module and a data acquisition module, a power supply module and a storage module connected to the data processing module, wherein the data acquisition module comprises a triaxial acceleration sensor, wherein the storage module stores a computer program operable on the data processing module, and wherein the data processing module, when executing the computer program, implements the steps of the pulse signal detection method according to any one of claims 1 to 7.
9. The wearable device of claim 8, further comprising a communication module connected with the data processing module, the communication module to communicate with a user terminal to send the pulse signal to the user terminal.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the pulse signal detection method according to any one of claims 1 to 7.
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