CN114947767A

CN114947767A - Respiration rate processing method and device and computer readable storage medium

Info

Publication number: CN114947767A
Application number: CN202210429443.7A
Authority: CN
Inventors: 李晴
Original assignee: DO Technology Co ltd
Current assignee: DO Technology Co ltd
Priority date: 2022-04-22
Filing date: 2022-04-22
Publication date: 2022-08-30

Abstract

The embodiment of the invention provides a method and a device for processing a respiration rate and a computer readable storage medium. The method comprises the following steps: acquiring a PPG signal of a PPG sensor; acquiring a first signal feature of at least one dimension based on the PPG signal; processing the first signal characteristics to obtain second signal characteristics, and converting the second signal characteristics from a time domain to a frequency domain to obtain a frequency domain energy map; fusing the frequency domain energy map to obtain a fused frequency domain energy map; based on the fused frequency domain energy graph, according to a pre-constructed fused frequency domain energy scoring model and the fused frequency domain energy scoring model, selecting a frequency value with the highest score, and determining a respiration rate value corresponding to the frequency value with the highest score. By means of fusing the frequency domain energy diagram, on one hand, PPG signals with signal quality meeting requirements are screened out, on the other hand, a frequency value with the highest score is determined before the respiratory rate is calculated, and then the corresponding respiratory rate value is calculated, so that the calculated amount is reduced, and the calculation efficiency is improved.

Description

Respiration rate processing method and device and computer readable storage medium

Technical Field

The present invention relates to the field of wearable device technologies, and in particular, to a method and an apparatus for processing a respiration rate, and a computer-readable storage medium.

Background

With the improvement of living standard of people, health indexes become one of the focuses of people's eager attention, and the respiratory function is more and more paid attention. The important parameter of the respiratory function is respiratory frequency, so that it is important to accurately monitor respiratory rate for the prevention and identification of respiratory diseases. Respiratory rate monitoring typically employs respiratory airflow methods, including temperature, carbon dioxide, moisture content, etc., or direct measurements such as respiratory sound measurements, thoracic barrier methods, etc. Indirect measurements include respiratory signals obtained based on myoelectrical, electrocardiographic or infrared imaging. The method is mostly used for medical clinical respiratory monitoring, and measurement is difficult to use in daily life. Respiration rate information can be indirectly acquired using a photoplethysmography (PPG) signal monitoring method. PPG is a photoelectric technique, which can monitor the change of blood volume in human tissue within the cardiac cycle, has the characteristics of non-invasive, and has the advantages of non-invasive and simple operation.

Along with the development of the intelligent wearing industry, the user expects the intelligence degree of wearing equipment to be higher and higher, but at present intelligent wearing equipment measures respiratory rate, receives the influence of user's environment easily to influence the accuracy of measuring respiratory rate.

Disclosure of Invention

In view of the above, the present application provides a method for processing a respiration rate to detect a respiration rate value of a user. According to the method, by means of fusing a frequency domain energy diagram, on one hand, PPG signals with signal quality meeting requirements are screened out, on the other hand, a frequency value with the highest score is determined before the respiratory rate is calculated, and then the corresponding respiratory rate value is calculated, so that the calculated amount is reduced, and the calculation efficiency is improved; then, based on the fused frequency domain energy graph, a frequency value with the highest score is selected according to the fused frequency domain energy scoring model, and a respiration rate value corresponding to the frequency value with the highest score is determined, so that the accuracy of a respiration rate measurement value is improved.

In a first aspect of the present application, a method for processing a respiration rate is provided, the method comprising: acquiring a PPG signal of a PPG sensor;

acquiring a first signal feature of at least one dimension based on the PPG signal;

processing the first signal characteristics to obtain second signal characteristics, and converting the second signal characteristics from a time domain to a frequency domain to obtain a frequency domain energy map;

fusing the frequency domain energy map to obtain a fused frequency domain energy map;

based on the fused frequency domain energy graph, according to a pre-constructed fused frequency domain energy scoring model and the fused frequency domain energy scoring model, selecting a frequency value with the highest score, and determining a respiration rate value corresponding to the frequency value with the highest score.

Optionally, with reference to the first aspect, in a possible implementation manner, the first signal feature includes an envelope and an RR interval.

Optionally, with reference to the first aspect, in a possible implementation manner, the acquiring a first signal feature of at least one dimension based on the PPG signal includes:

acquiring first signal features of at least two dimensions based on the PPG signal, the first signal features including an envelope and an RR interval.

Optionally, with reference to the first aspect, in a possible implementation manner, the processing the first signal feature to obtain a second signal feature, and converting the second signal feature from a time domain to a frequency domain to obtain a frequency-domain energy map includes:

filtering the first envelope characteristic to obtain a second envelope characteristic; carrying out Fourier transform on the second envelope characteristic to obtain an envelope frequency domain energy diagram;

preprocessing the RR intervals to obtain fused RR intervals; and converting the fused RR interval from a time domain to a frequency domain to obtain an RR interval frequency domain energy map.

Optionally, with reference to the first aspect, in a possible implementation manner, the filtering the first envelope characteristic to obtain a second envelope characteristic includes:

filtering the upper envelope to obtain an upper envelope characteristic; and/or the presence of a gas in the gas,

and filtering the lower envelope to obtain the lower envelope characteristic.

Optionally, with reference to the first aspect, in a possible implementation manner, if the obtained upper envelope feature is obtained, the fusing the frequency domain energy values to obtain fused frequency domain energy includes:

and fusing the upper envelope frequency domain energy graph and the RR interval frequency domain energy graph to obtain a first fused frequency domain energy graph.

Optionally, with reference to the first aspect, in a possible implementation manner, if the obtained lower envelope characteristic is obtained, the fusing the frequency domain energy values to obtain fused frequency domain energy includes:

and fusing the lower envelope frequency domain energy graph and the RR interval frequency domain energy graph to obtain a second fused frequency domain energy graph.

Optionally, with reference to the first aspect, in a possible implementation manner, if the obtained upper envelope characteristic and the obtained lower envelope characteristic are obtained, the fusing the frequency domain energy values to obtain fused frequency domain energy includes:

and fusing the upper envelope frequency domain energy graph, the lower envelope frequency domain energy graph and the RR interval frequency domain energy graph to obtain a third fused frequency domain energy graph.

Optionally, with reference to the first aspect, in a possible implementation manner, the respiration rate processing method further includes:

and transforming the PPG signal from the time domain to the frequency domain to obtain a PPG signal frequency domain energy graph.

Optionally, with reference to the first aspect, in a possible implementation manner, the fusing the frequency domain energy values to obtain a fused frequency domain energy map includes:

and fusing the envelope frequency domain energy graph, the RR interval frequency domain energy graph and the PPG signal frequency domain energy graph to obtain a fused frequency domain energy graph.

Optionally, with reference to the first aspect, in a possible implementation manner, before acquiring a PPG signal of a PPG sensor, the method further includes: if the measurement mode is the first measurement mode, judging whether the wearable equipment is static according to the acceleration signal, and if the wearable equipment is static, starting a PPG signal; if the measurement mode is the second measurement mode, whether the user falls asleep is identified according to a sleep algorithm, and if the user falls asleep, the PPG signal of the second time is started at the first interval; the second time is less than the first time.

Optionally, with reference to the first aspect, in a possible implementation manner, the PPG signal is a green light signal, and then the method further includes: judging the signal quality of the PPG signal according to the interval characteristic of the PPG signal; the interval characteristic of the PPG signal is obtained by the interval difference of adjacent peaks; when the adjacent intervals continuously generate mutation, the signal quality is judged to be not in accordance with the preset condition; and if the signal quality meets the preset condition, reading the signal, preprocessing the PPG signal, and removing the baseline signal to obtain a preprocessed PPG signal.

Optionally, with reference to the first aspect, in a possible implementation manner, acquiring a first signal feature of at least one dimension based on the PPG signal includes: acquiring the wave crest and the wave trough of the preprocessed PPG signal; and respectively interpolating the wave crest and the wave trough to obtain the upper and lower envelope characteristics of the green light signal.

Optionally, with reference to the first aspect, in a possible implementation manner, the acquiring peaks and troughs of the preprocessed PPG signal includes: judging whether the PPG point of the preprocessed PPG signal is a maximum value or a minimum value;

if the window length is the maximum value, judging whether the window length is the maximum value of N; if the peak value is the maximum value, the peak value is a valid peak; wherein the selection of N is determined according to the frequency of the PPG signal; if the window length is the minimum value, judging whether the window length is the minimum value of the adjacent window length N; if the minimum value is the minimum value, the effective trough is obtained; wherein the selection of N is determined according to the frequency of the PPG signal.

In a second aspect of the present application, there is provided a respiratory rate processing apparatus, comprising:

a first acquisition module configured to acquire a PPG signal of a PPG sensor;

a second acquisition module configured to acquire a first signal feature of at least one dimension based on the PPG signal;

a conversion module configured to process the first signal feature to obtain a second signal feature, and convert the second signal feature from a time domain to a frequency domain to obtain a frequency domain energy map;

optionally, with reference to the second aspect, in a possible implementation manner, the fusion calculation module is configured to fuse the frequency domain energy maps to obtain a fused frequency domain energy map;

optionally, with reference to the second aspect, in a possible implementation manner, the determining module is configured to select a highest-scoring frequency value according to a pre-constructed fusion frequency domain energy scoring model and a fusion frequency domain energy scoring model based on the fusion frequency domain energy map, and determine a respiratory rate value corresponding to the highest-scoring frequency value.

Optionally, with reference to the second aspect, in a possible implementation manner, the second obtaining module includes:

an acquisition unit configured to acquire first signal features of at least two dimensions based on the PPG signal, the first signal features including an envelope and an RR interval.

Optionally, with reference to the second aspect, in a possible implementation manner, the conversion module includes:

a first transformation unit configured to filter the first envelope characteristic to obtain a second envelope characteristic; carrying out Fourier transform on the second envelope characteristic to obtain an envelope frequency domain energy diagram;

the second transformation unit is configured to preprocess the RR intervals to obtain fused RR intervals; and converting the fused RR interval from a time domain to a frequency domain to obtain an RR interval frequency domain energy map.

Optionally, with reference to the second aspect, in a possible implementation manner, the first transformation unit includes:

a first filtering subunit, configured to filter the upper envelope to obtain an upper envelope characteristic; and/or the presence of a gas in the gas,

and the second filtering subunit is configured to filter the lower envelope to obtain the lower envelope characteristic.

Optionally, with reference to the second aspect, in a possible implementation manner, the fusion calculation module includes:

and the first fusion calculation unit is configured to fuse the upper envelope frequency domain energy map and the RR interval frequency domain energy map to obtain a first fusion frequency domain energy map.

and the second fusion calculation unit is configured to fuse the lower envelope frequency domain energy map and the RR interval frequency domain energy map to obtain a second fusion frequency domain energy map.

and the third fusion calculation unit is configured to fuse the upper envelope frequency domain energy map, the lower envelope frequency domain energy map and the RR interval frequency domain energy map to obtain a third fusion frequency domain energy map.

Optionally, with reference to the second aspect, in a possible implementation manner, the processing device of the breathing rate further includes:

and the third acquisition module is configured to transform the PPG signal from the time domain to the frequency domain to obtain a PPG signal frequency domain energy map.

and the fourth fusion calculation unit is configured to fuse the envelope frequency domain energy map, the RR interval frequency domain energy map and the PPG signal frequency domain energy map to obtain a fusion frequency domain energy map.

Optionally, with reference to the second aspect, in a possible implementation manner, the processing device of the respiration rate further includes:

the first judgment module is configured to judge whether the wearable equipment is static according to the acceleration signal if the wearable equipment is in the first measurement mode, and open the PPG signal if the wearable equipment is static;

the second judgment module is configured to identify whether the user falls asleep or not according to a sleep algorithm if the user falls asleep in a second measurement mode, and start the PPG signal at a second time every first time if the user falls asleep; the second time is less than the first time.

the signal quality judging module is configured to judge the signal quality of the PPG signal according to the interval characteristics of the PPG signal; the interval characteristic of the PPG signal is obtained by the interval difference of adjacent peaks;

the preprocessing module is configured to judge that the signal quality does not meet a preset condition when adjacent intervals continuously mutate; and if the signal quality meets the preset condition, reading the signal, preprocessing the PPG signal, and removing the baseline signal to obtain a preprocessed PPG signal.

a second obtaining unit configured to obtain a peak and a trough of the preprocessed PPG signal;

the difference unit is configured to interpolate the wave crest and the wave trough respectively to obtain the upper envelope characteristic and the lower envelope characteristic of the green light signal;

an interval calculation unit configured to calculate an interval between peaks and troughs of the PPG signal; and obtaining the RR interval characteristics according to adjacent peaks or adjacent valleys.

Optionally, with reference to the second aspect, in a possible implementation manner, the second obtaining unit includes:

the judging subunit is configured to judge whether the PPG point of the preprocessed PPG signal is a maximum value or a minimum value;

if the window length is the maximum value, judging whether the window length is the maximum value of N; if the peak value is the maximum value, the peak value is a valid peak; wherein the selection of N is determined according to the frequency of the PPG signal;

if the window length is the minimum value, judging whether the window length is the minimum value of the adjacent window length N; if the minimum value is the minimum value, the effective trough is obtained; wherein the selection of N is determined according to the frequency of the PPG signal.

In a third aspect of the present application, there is provided a wearable device comprising a processor and a memory, the memory storing a computer program executable by the processor, the computer program, when executed by the processor, implementing the method according to the first aspect and any one of the possible implementations.

In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method according to the first aspect and any one of the possible implementations.

One of the schemes provided by the present application includes: acquiring a PPG signal of a PPG sensor; obtaining a first signal feature in at least one dimension based on the PPG signal; processing the first signal characteristics to obtain second signal characteristics, and converting the second signal characteristics from a time domain to a frequency domain to obtain a frequency domain energy diagram; fusing the frequency domain energy map to obtain a fused frequency domain energy map; based on the fused frequency domain energy graph, according to a pre-constructed fused frequency domain energy scoring model and the fused frequency domain energy scoring model, selecting a frequency value with the highest score, and determining a respiration rate value corresponding to the frequency value with the highest score. As an embodiment of the invention, at first, more than two first signal features of at least one dimension are obtained, and then the frequency domain energy graphs are fused by obtaining at least two frequency domain energy graphs corresponding to the first signal features to obtain a fused frequency domain energy graph; based on the fused frequency domain energy graph, a frequency value with the highest score is selected according to the fused frequency domain energy scoring model, and a respiration rate value corresponding to the frequency value with the highest score is determined, so that the accuracy of a respiration rate measurement value is improved. By means of fusing the frequency domain energy diagram, on one hand, PPG signals with signal quality meeting requirements are screened out, on the other hand, a frequency value with the highest score is determined before the respiratory rate is calculated, and then the corresponding respiratory rate value is calculated, so that the calculated amount is reduced, and the calculation efficiency is improved. According to the embodiment of the application, the deviation of the accuracy of the respiratory rate measured value caused by the error of the first signal characteristic of a certain dimension due to external factors is avoided.

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 schematic diagram of a waveform modulation effect of a respiration process on a PPG signal provided in an embodiment of the present application;

fig. 2 is a flowchart of a method for processing respiration rate data according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a respiration rate data processing apparatus according to an embodiment of the present application;

fig. 4 is a module schematic diagram of a wearable device provided in an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.

It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The respiratory rate (respirator) is the number of breaths per unit time. The amount of light absorbed by the muscles of the human body group and the venous blood is constant, and when the heart beats, the volume of the arterial blood also changes periodically. When the heart beats strongly and the blood content in the blood vessel is high, the absorption amount of the blood to light is large, and the detected projection or reflection light intensity is small; when the heart beat is weak and the blood content in the blood vessel is small, the amount of light absorbed by the blood is small, and the amount of projected or reflected light detected is large. The velocity of blood flow changes with the change in respiration rate, and the received PPG signal strength also changes. The respiration rate can therefore be acquired from the PPG signal.

Under a calm state, the normal respiratory frequency of an adult is about 16-20 times/minute. Women are slightly faster than men's breathing rate by 2-3 times/min on average. The respiratory rate of the newborn is about 40 to 50 times/minute at the fastest speed, and about 30 to 40 times/minute within 1 year of age. The respiratory rate of adults aged 7 or older is basically consistent.

Specifically, the measurement principle of the respiration rate is as follows: the measured portion is irradiated with a light emitting diode, and then transmitted/reflected light is received with a photodiode, and an optical signal is converted into an electrical signal.

Referring to fig. 1, the modulation effect of the respiration process on the PPG waveform includes baseline modulation (BW) and pulse Amplitude Modulation (AM). The baseline modulation is such that varying intrathoracic pressures cause venous blood reflux throughout the respiratory cycle. Intrathoracic pressure decreases during inspiration, causing a decrease in central venous pressure and an increase in venous return. The expiration process is the opposite of the inspiration process, i.e., the intrathoracic pressure increases during expiration, causing an increase in central venous pressure and a decrease in venous return. As more blood is continuously shunted to the low pressure venous system, the modulation acts on the baseline (Nomod baseline), moving the baseline waveform up and down. Pulse amplitude modulation is due to changes in intrathoracic pressure during inspiration, with each ventricular beat, a reduction in blood stroke volume, resulting in a reduction in the amplitude of the respiratory pulse, as shown by the AM waveform in FIG. 1, with the amplitude of some respiratory waves being reduced from baseline.

As an embodiment of the present invention, referring to fig. 2, a respiratory rate processing method is provided, which is applied to a wearable device, and the method specifically includes:

s101: a PPG signal of the PPG sensor is acquired.

Wherein the PPG sensor comprises one or more green LEDs and a photodetector. The green light is selected as the light source in consideration of the following characteristics: the melanin of the skin absorbs a large number of shorter wavelength waves; moisture on the skin also absorbs a significant amount of the UV and IR portion of the light; the green (500nm) -yellow (600nm) light entering the skin tissue will be mostly absorbed by the red blood cells; red light and light near IR pass through skin tissue more easily than other wavelengths; blood absorbs more light than other tissues; green (green-yellow) light can be absorbed by oxyhemoglobin and deoxyhemoglobin compared to red light. In summary, both green and red light can be used as the measurement light source. Green light is used as the light source to obtain a better signal and the signal to noise ratio is better than other light sources, so green light is used as the light source in this example. But considering the difference in skin condition (skin tone, sweat), as a preferred embodiment, the PPG sensor comprises one or more green LEDs, one or more infrared LEDs and a photodetector, with multiple light sources of green, red and IR being automatically used and switched according to the situation. For example, in a high-temperature environment, when a user swings sweat in a gymnasium like rain, the moisture on the surface of the skin increases, and because more green light is absorbed, the detection of the subcutaneous reflected green light is difficult, the green light can be automatically turned off and converted into infrared light to adapt to various different scenes, and the accuracy of the measured respiratory rate is ensured.

S102: a first signal feature is acquired in at least one dimension based on the PPG signal.

Therein, dimensions can be understood as categories. One class of first signal features may be envelope features, which may be either or both of upper and lower envelope features. It will be appreciated that both the upper envelope and the lower envelope belong to the first signal feature in this dimension of the envelope. Another category of first signal features may be RR interval features. Wherein, RR interval is the interval between two adjacent peaks (or adjacent valleys). The first signal characteristic may also be of other kinds, which are not limited herein.

S103: and processing the first signal characteristic to obtain a second signal characteristic, and converting the second signal characteristic from a time domain to a frequency domain to obtain a frequency domain energy map.

The processing method may be filtering, including but not limited to IIR, FIR or sliding filtering. And filtering to enable the second signal characteristics to be located at a respiration rate frequency band of 3-50 hz, and then carrying out Fourier transform on the second signal characteristics to obtain a frequency domain energy diagram, namely obtaining the frequency domain energy diagrams corresponding to different second signal characteristics. The frequency-domain energy maps corresponding to different second signal features may include, but are not limited to, an envelope frequency-domain energy map and an RR-interval frequency-domain energy map.

S104: and fusing the frequency domain energy maps to obtain a fused frequency domain energy map.

In this embodiment, since the first signal features of different dimensions are obtained in S102, the frequency domain energy map corresponds to the first signal feature of each dimension, and the frequency domain energy maps corresponding to the first signal features of each dimension are fused to obtain a fused frequency domain energy map. By means of fusing the frequency domain energy diagram, on one hand, PPG signals with signal quality meeting requirements are screened out, on the other hand, a frequency value with the highest score is determined before the respiratory rate is calculated, and then the corresponding respiratory rate value is calculated, so that the calculated amount is reduced, and the calculation efficiency is improved.

S105: based on the fused frequency domain energy graph, according to a pre-constructed fused frequency domain energy scoring model and the fused frequency domain energy scoring model, selecting a frequency value with the highest score, and determining a respiration rate value corresponding to the frequency value with the highest score.

In this embodiment, for the fused frequency domain energy map obtained in S104, the respiration rate at each time point is determined according to the fused frequency domain energy map. Specifically, for each time point, a highest-scoring frequency value is selected according to a pre-constructed fusion frequency domain energy scoring model through the pre-constructed fusion frequency domain energy scoring model, so that a respiration rate value of each time point is obtained.

In one aspect, the present application provides a method, including: acquiring a PPG signal of a PPG sensor; acquiring a first signal feature of at least one dimension based on the PPG signal; processing the first signal characteristics to obtain second signal characteristics, and converting the second signal characteristics from a time domain to a frequency domain to obtain a frequency domain energy map; fusing the frequency domain energy map to obtain a fused frequency domain energy map; based on the fused frequency domain energy graph, according to a pre-constructed fused frequency domain energy scoring model and the fused frequency domain energy scoring model, selecting a frequency value with the highest score, and determining a respiration rate value corresponding to the frequency value with the highest score. As an embodiment of the invention, at first, more than two first signal features of at least one dimension are obtained, and then the frequency domain energy graphs are fused by obtaining at least two frequency domain energy graphs corresponding to the first signal features to obtain a fused frequency domain energy graph; based on the fused frequency domain energy graph, a frequency value with the highest score is selected according to the fused frequency domain energy scoring model, and a respiration rate value corresponding to the frequency value with the highest score is determined, so that the accuracy of a respiration rate measurement value is improved. Through the mode of fusing the frequency domain energy diagram, the PPG signal with the signal quality meeting the requirements is screened out on one hand, and on the other hand, the frequency value with the highest score is determined before the respiratory rate is calculated, and then the corresponding respiratory rate value is calculated, so that the calculated amount is reduced, and the calculation efficiency is improved. According to the embodiment of the application, the deviation of the accuracy of the respiratory rate measured value caused by the error of one first signal characteristic due to external factors is avoided.

As an embodiment of the present invention, S103 may include the steps of:

s201: filtering the first envelope characteristic to obtain a second envelope characteristic; and carrying out Fourier transform on the second envelope characteristic to obtain an envelope frequency domain energy diagram.

S202: preprocessing the RR intervals to obtain fused RR intervals; and converting the fused RR interval from a time domain to a frequency domain to obtain an RR interval frequency domain energy map.

For S201, an envelope frequency-domain energy map of the envelope feature is obtained. For S202, an RR-interval frequency-domain energy map is obtained.

For S201, in a possible implementation manner, the filtering the first envelope characteristic to obtain a second envelope characteristic includes:

s301: filtering the upper envelope to obtain an upper envelope characteristic; and/or the presence of a gas in the gas,

s302: and filtering the lower envelope to obtain the lower envelope characteristic.

It is understood that the second envelope characteristic obtained by filtering the first envelope characteristic may be an upper envelope characteristic, a lower envelope characteristic, or an upper envelope characteristic and a lower envelope characteristic.

Corresponding to the above S301 and S302, if the obtained upper envelope feature is the upper envelope feature, S104 includes the following steps:

s401: and fusing the upper envelope frequency domain energy graph and the RR interval frequency domain energy graph to obtain a first fused frequency domain energy graph.

Corresponding to the above S301 and S302, if the lower envelope feature is obtained, S104 includes the following steps:

s402: and fusing the lower envelope frequency domain energy graph and the RR interval frequency domain energy graph to obtain a second fused frequency domain energy graph.

Corresponding to the above S301 and S302, if the upper envelope characteristic and the lower envelope characteristic are obtained, S104 includes the following steps:

s403: and fusing the upper envelope frequency domain energy graph, the lower envelope frequency domain energy graph and the RR interval frequency domain energy graph to obtain a third fused frequency domain energy graph.

As an embodiment of the present invention, after S101, the respiration rate processing method further includes the steps of:

s106: and transforming the PPG signal from the time domain to the frequency domain to obtain a PPG signal frequency domain energy graph.

Corresponding to the above-mentioned embodiment of S106, then S104 includes:

s404: and fusing the envelope frequency domain energy graph, the RR interval frequency domain energy graph and the PPG signal frequency domain energy graph to obtain a fused frequency domain energy graph.

The envelope frequency-domain energy map may be an upper envelope frequency-domain energy map, a lower envelope frequency-domain energy map, an upper envelope frequency-domain energy map, and a lower envelope frequency-domain energy map, which are not described herein again.

As an embodiment of the invention, the fusion frequency domain energy diagram of the first characteristic of three dimensions is fused, and only one fusion is needed, so that the calculation times of time domain to frequency domain conversion are reduced, and the calculation efficiency is improved; in addition, the first characteristic of three dimensions is added on the basis of the first two dimensions, so that the accuracy of the later respiration rate value is further improved.

It should be noted that the above method for processing the respiration rate can be applied to wearable devices, such as a bracelet watch. During application, the method may include, but is not limited to, two usage scenarios. First, click respiration rate measurement. I.e. the user clicks on the breathing rate measurement from the graphical interface of the wearable device, the breathing rate of the user is measured. Second, the whole day respiratory rate measurement, namely the whole day real-time measurement of the respiratory rate of the user.

As an embodiment of the present invention, before S101, the method further includes:

s107: if the measurement mode is the first measurement mode, whether the wearable equipment is static or not is judged according to the acceleration signal, and if the measurement mode is static, the PPG signal is started.

Wherein the first measurement mode may be a click respiration rate measurement mode.

S108: if the measurement mode is the second measurement mode, whether the user falls asleep is identified according to a sleep algorithm, and if the user falls asleep, the PPG signal of the second time is started at the first interval; the second time is less than the first time.

Wherein the second measurement mode may be an all-day respiration rate measurement mode. The sleep algorithm may be performed by ACC amplitude recognition, which is not limited herein. For convenience of description, the second time may be three minutes, and the first time may be one minute. And if the user is judged to fall asleep, turning on a three-minute green light signal every ten minutes for signal extraction.

As an embodiment of the present invention, if the PPG signal is a green light signal, before S101, the method further includes:

s109: judging the signal quality of the PPG signal according to the interval characteristic of the PPG signal; the interval characteristic of the PPG signal is obtained by the interval difference of adjacent peaks.

S110: when the adjacent intervals continuously generate mutation, the signal quality is judged to be not in accordance with the preset condition; and if the signal quality meets the preset condition, reading the signal, preprocessing the PPG signal, and removing the baseline signal to obtain a preprocessed PPG signal.

On the basis of the corresponding embodiments of S109 and S110, the following describes an acquisition manner of the envelope characteristic, and as an embodiment of the present invention, S102 specifically includes:

s701: and acquiring the wave crest and the wave trough of the preprocessed PPG signal.

S702: and respectively interpolating the wave crest and the wave trough to obtain the upper and lower envelope characteristics of the green light signal.

The interpolation method may include, but is not limited to, cubic spline interpolation, discrete smooth interpolation, and the like.

S703: based on peaks and troughs of the PPG signal; and obtaining the RR interval characteristics according to adjacent peaks or adjacent valleys.

As an embodiment of the present invention, S701 specifically includes:

s801: and judging whether the PPG point of the preprocessed PPG signal is a maximum value or a minimum value.

S802: if the window length is the maximum value, judging whether the window length is the maximum value of N; if the peak value is the maximum value, the peak value is a valid peak; wherein the selection of N is determined according to the frequency of the PPG signal.

S803: if the window length is the minimum value, judging whether the window length is the minimum value of the adjacent window length N; if the minimum value is the minimum value, the effective trough is obtained; wherein the selection of N is determined according to the frequency of the PPG signal.

And for S801-S803, judging whether the PPG point after pretreatment is larger than adjacent points, judging whether the PPG point is the maximum value of the adjacent window length N, and if the PPG point is the maximum value, determining the PPG point is an effective peak. And judging whether the preprocessed PPG point is smaller than the adjacent points, judging whether the preprocessed PPG point is the minimum value of the adjacent window length N, and if the preprocessed PPG point is the minimum value, judging that the preprocessed PPG point is an effective trough. The choice of N is determined from the PPG signal frequency. The method has strong noise interference resistance and is easy to calculate.

As an embodiment of the present invention, there is provided a respiratory rate processing apparatus including:

a first acquisition module configured to acquire a PPG signal of a PPG sensor;

Optionally, with reference to the second aspect, in a possible implementation manner, the converting module includes:

the first judging module is configured to judge whether the wearable equipment is static according to the acceleration signal if the wearable equipment is in the first measurement mode, and open the PPG signal if the wearable equipment is static;

Optionally, with reference to the second aspect, in a possible implementation manner, the processing apparatus of the respiration rate further includes:

the signal quality judging module is configured to judge the signal quality of the PPG signal according to the interval characteristic of the PPG signal; the interval characteristic of the PPG signal is obtained by the interval difference of adjacent peaks;

the preprocessing module is configured to judge that the signal quality does not meet a preset condition when the adjacent intervals continuously mutate; and if the signal quality meets the preset condition, reading the signal, preprocessing the PPG signal, and removing the baseline signal to obtain a preprocessed PPG signal.

the difference unit is configured to interpolate the wave crests and the wave troughs respectively to obtain upper and lower envelope characteristics of the green light signals;

In one aspect, the present application provides a method, including: acquiring a PPG signal of a PPG sensor; acquiring a first signal feature of at least one dimension based on the PPG signal; processing the first signal characteristics to obtain second signal characteristics, and converting the second signal characteristics from a time domain to a frequency domain to obtain a frequency domain energy map; fusing the frequency domain energy map to obtain a fused frequency domain energy map; based on the fused frequency domain energy graph, according to a pre-constructed fused frequency domain energy scoring model and the fused frequency domain energy scoring model, selecting a frequency value with the highest score, and determining a respiration rate value corresponding to the frequency value with the highest score. As an embodiment of the invention, at first, more than two first signal features of at least one dimension are obtained, and then the frequency domain energy graphs are fused by obtaining at least two frequency domain energy graphs corresponding to the first signal features to obtain a fused frequency domain energy graph; based on the fused frequency domain energy graph, a frequency value with the highest score is selected according to the fused frequency domain energy scoring model, and a respiration rate value corresponding to the frequency value with the highest score is determined, so that the accuracy of a respiration rate measurement value is improved. By means of fusing the frequency domain energy diagram, on one hand, PPG signals with signal quality meeting requirements are screened out, on the other hand, a frequency value with the highest score is determined before the respiratory rate is calculated, and then the corresponding respiratory rate value is calculated, so that the calculated amount is reduced, and the calculation efficiency is improved. According to the embodiment of the application, the deviation of the accuracy of the respiratory rate measured value caused by the error of one first signal characteristic due to external factors is avoided.

As shown in fig. 4, wearable device 100 may include one or more processors 101, memory 102, communication module 103, sensor module 104, display 105, audio module 106, speaker 107, microphone 108, camera module 109, motor 110, keys 111, indicators 112, battery 113, power management module 114. These components may communicate over one or more communication buses or signal lines.

The processor 101 is a final execution unit of information processing and program execution, and may execute an operating system or an application program to execute various functional applications and data processing of the wearable device 100. Processor 101 may include one or more processing units, such as: the Processor 101 may include a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an Image Signal Processor (ISP), a sensor hub Processor or a Communication Processor (CP) Application Processor (AP), and the like. In some embodiments, processor 101 may include one or more interfaces. The interface is used to couple peripheral devices to the processor 101 to transmit instructions or data between the processor 101 and the peripheral devices. In the embodiment of the present application, the processor 101 is further configured to identify a type of target motion corresponding to the motion data collected by the acceleration sensor and the gyroscope sensor, for example, walking/running/riding/swimming. Specifically, the processor 101 compares the motion waveform characteristics corresponding to the received motion data with the motion waveform characteristics corresponding to the target motion type, so as to identify the target motion type corresponding to the motion data, the processor 101 is further configured to determine whether the motion data in the preset time period all meet the preset motion intensity requirement associated with the target motion type, and when it is determined that the motion data in the preset time period all meet the preset motion intensity requirement associated with the target motion type, the processor 101 controls to turn on the sensor group associated with the target motion type.

The memory 102 may be used to store computer-executable program code, which includes instructions. The memory 102 may include a program storage area and a data storage area. The storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required by at least one function, and the like. The stored data area may store data created during use of the wearable device 100, such as exercise parameters of each exercise of the user, such as number of steps, stride, pace, heart rate, respiration rate, blood glucose concentration, energy expenditure (calories), and the like. The memory may include a high-speed random access memory, and may further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, a universal flash memory (UFS), and the like. In the embodiment of the present application, the memory 102 can store sensor waveform rule characteristic data corresponding to target motion such as walking, running, riding, or swimming.

The communication module 103 may enable the wearable device 100 to communicate with networks and mobile terminals via wireless communication technologies. The communication module 103 converts an electrical signal into an electromagnetic signal to transmit, or converts a received electromagnetic signal into an electrical signal. The communication module 103 may include one or more of a cellular mobile communication module, a short-range wireless communication module, a wireless internet module, and a location information module. The mobile communication module may transmit or receive wireless signals based on a technical standard of mobile communication, and may use any mobile communication standard or protocol, including but not limited to global system for mobile communications (GSM), Code Division Multiple Access (CDMA), code division multiple access 2000(CDMA2000), wideband CDMA (wcdma), time division synchronous code division multiple access (TD-SCDMA), Long Term Evolution (LTE), LTE-a (long term evolution advanced), and the like. The wireless internet module may transmit or receive wireless signals via a communication network according to wireless internet technology, including wireless lan (wlan), wireless fidelity (Wi-Fi), Wi-Fi direct, Digital Living Network Alliance (DLNA), wireless broadband (WiBro), and the like. The short-distance wireless communication module can send or receive wireless signals according to short-distance communication technologies, and the technologies comprise Bluetooth, Radio Frequency Identification (RFID), infrared data communication (IrDA), Ultra Wide Band (UWB), ZigBee, Near Field Communication (NFC), wireless fidelity (Wi-Fi), Wi-Fi direct connection, wireless USB (wireless universal serial bus) and the like. The location information module may obtain the location of the wearable device based on a Global Navigation Satellite System (GNSS), which may include one or more of a Global Positioning System (GPS), a global satellite navigation system (Glonass), a beidou satellite navigation system, and a galileo satellite navigation system.

The sensor module 104 is used to measure a physical quantity or detect an operation state of the wearable device 100. The sensor module 104 may include an acceleration sensor 104A, a gyroscope sensor 104B, an air pressure sensor 104C, a magnetic sensor 104D, a biometric sensor 104E, a proximity sensor 104F, an ambient light sensor 104G, a touch sensor 104H, and the like. The sensor module 104 may also include control circuitry for controlling one or more sensors included in the sensor module 104.

Among other things, the acceleration sensor 104A may detect the magnitude of acceleration of the wearable device 100 in various directions. The magnitude and direction of gravity may be detected when the wearable device 100 is stationary. The wearable device 100 can also be used for recognizing the gesture of the wearable device 100, and is applied to horizontal and vertical screen switching, pedometers and other applications. In one embodiment, the acceleration sensor 104A may be used in conjunction with the gyroscope sensor 104B to monitor the stride length, stride frequency, pace, etc. of the user during exercise.

The gyroscope sensor 104B may be used to determine the motion pose of the wearable device 100. In some embodiments, the angular velocity of wearable device 100 about three axes (i.e., x, y, and z axes) may be determined by gyroscope sensor 104B.

The air pressure sensor 104C is used to measure air pressure. In some embodiments, wearable device 100 calculates altitude, aiding in positioning and navigation from barometric pressure values measured by barometric pressure sensor 104C.

The GPS sensor 104D may be used to record a track of user activity to determine the user's location.

The biometric sensor 104E is used to measure physiological parameters of the user including, but not limited to, Photoplethysmography (PPG) sensors, ECG sensors, EMG sensors, blood glucose sensors, temperature sensors. For example, the wearable device 100 may measure heart rate, respiration rate, blood pressure data of the user via signals of a photoplethysmographic sensor and/or an ECG sensor, and identify a blood glucose value of the user based on data generated by a blood glucose sensor. In this embodiment of the application, the PPG sensor is used to detect the heart rate of the user, and specifically, the PPG sensor can continuously detect signal data related to the heart rate of the user after being turned on and transmit the signal data to the processor 101, and then the processor 101 calculates the heart rate value through a heart rate algorithm. In this embodiment of the application, the temperature sensor is configured to detect a first temperature of a wrist skin of a user, and specifically, the temperature sensor can continuously obtain temperature data of the wrist skin of the user after being turned on and transmit the temperature data to the processor 101, and then the processor 101 calculates a corresponding physical temperature value from electrical signal data of the temperature sensor through a temperature algorithm.

The proximity sensor 104F is used to detect the presence of an object near the wearable device 100 without any physical contact. In some embodiments, the proximity sensor 104F may include a light emitting diode and a light detector. The light emitting diodes may be infrared light and the wearable device 100 uses a light detector to detect reflected light from nearby objects. When the reflected light is detected, it may be determined that there is an object near the wearable device 100. The wearable device 100 may detect its wearing state using the proximity sensor 104F.

The ambient light sensor 104G is used to sense ambient light level. In some embodiments, wearable device 100 may adaptively adjust display screen brightness according to perceived ambient light levels to reduce power consumption.

The touch sensor 104H is used to detect a touch operation applied thereto or nearby, and is also referred to as a "touch device". The touch sensor 104H can be disposed on the display screen 105, and the touch sensor 104H and the display screen 105 form a touch screen.

The display screen 105 is used to display a graphical User Interface (UI) that may include graphics, text, icons, video, and any combination thereof. The Display 105 may be a Liquid Crystal Display (lcd), an Organic Light-Emitting Diode (OLED) Display, or the like. When the display screen 105 is a touch display screen, the display screen 105 can capture a touch signal on or over the surface of the display screen 105 and input the touch signal as a control signal to the processor 101.

An audio module 106, a speaker 107, a microphone 108, etc. providing audio functions between the user and the wearable device 100, such as listening to music or talking; for another example, when the wearable device 100 receives a notification message from the mobile terminal, the processor 101 controls the audio module 106 to output a preset audio signal, and the speaker 107 emits a sound to remind the user. The audio module 106 converts the received audio data into an electrical signal and sends the electrical signal to the speaker 107, and the speaker 107 converts the electrical signal into sound; or the microphone 108 converts the sound into an electrical signal and sends the electrical signal to the audio module 106, and then the audio module 106 converts the electrical audio signal into audio data.

The camera module 111 is used to capture still images or video. The camera module 111 may include an image sensor, an Image Signal Processor (ISP), and a Digital Signal Processor (DSP). The image sensor converts an optical signal into an electrical signal, the image signal processor converts the electrical signal into a digital image signal, and the digital signal processor converts the digital image signal into an image signal of a standard format (RGB, YUV). The image sensor may be a Charge Coupled Device (CCD) or a metal-oxide-semiconductor (CMOS).

The motor 110 may convert the electrical signal into mechanical vibrations to produce a vibratory effect. The motor 110 may be used for vibration prompts for incoming calls, messages, and also for touch vibration feedback. The keys 109 include a power-on key, a volume key, and the like. The keys 109 may be mechanical keys (physical buttons) or touch keys. The indicator 112 is used to indicate the state of the wearable device 100, such as indicating a charging state, a change in charge level, and may also be used to indicate a message, a missed call, a notification, and the like. In some embodiments, wearable device 100 provides vibration feedback upon receiving a notification message from the mobile terminal application.

The battery 113 is used to provide power to the various components of the wearable device 100. The power management module 114 is used for managing charging and discharging of the battery, and monitoring parameters such as battery capacity, battery cycle number, battery health (whether leakage occurs, impedance, voltage, current, and temperature). In some embodiments, the power management module 114 may charge the battery in a wired or wireless manner.

It should be understood that in some embodiments, wearable device 100 may be comprised of one or more of the foregoing components, and wearable device 100 may include more or fewer components than shown, or combine certain components, or split certain components, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

It should be understood that in some embodiments, the wearable device may be comprised of one or more of the aforementioned components, and the wearable device may include more or fewer components than illustrated, or combine certain components, or split certain components, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described method of processing a respiration rate.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist alone, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, or a part thereof, which essentially contributes to the prior art, may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method of processing a respiration rate, the method comprising:

acquiring a PPG signal of a PPG sensor;

based on the fusion frequency domain energy graph, according to a pre-constructed fusion frequency domain energy scoring model and the fusion frequency domain energy scoring model, selecting a frequency value with the highest score, and determining a respiration rate value corresponding to the frequency value with the highest score.

2. The method of processing the respiration rate of claim 1, wherein the first signal characteristics comprise an envelope and an RR interval.

3. The processing method of claim 2, wherein the obtaining a first signal feature in at least one dimension based on the PPG signal comprises:

4. The processing method of claim 2, wherein said processing the first signal feature to obtain a second signal feature and converting the second signal feature from the time domain to the frequency domain to obtain a frequency domain energy map comprises:

5. The processing method of claim 4, wherein filtering the first envelope characteristic to obtain the second envelope characteristic comprises:

filtering the upper envelope to obtain an upper envelope characteristic; and/or the presence of a gas in the atmosphere,

and filtering the lower envelope to obtain the lower envelope characteristic.

6. The processing method of claim 5, wherein if the obtained upper envelope feature is obtained, said fusing the frequency-domain energy values to obtain fused frequency-domain energy comprises:

7. The processing method of claim 5, wherein if the obtained lower envelope feature is obtained, said fusing the frequency domain energy values to obtain fused frequency domain energy comprises:

8. The processing method of claim 5, wherein if an upper envelope characteristic and a lower envelope characteristic are obtained, said fusing the frequency domain energy values to obtain a fused frequency domain energy comprises:

9. The processing method of claim 4, further comprising:

10. The process of claim 9, wherein fusing the frequency domain energy values to obtain a fused frequency domain energy map, comprises:

11. The processing method of any one of claims 1 to 10, further comprising, prior to acquiring the PPG signal of the PPG sensor:

if the measurement mode is the first measurement mode, judging whether the wearable equipment is static according to the acceleration signal, and if the wearable equipment is static, starting a PPG signal;

if the measurement mode is the second measurement mode, whether the user falls asleep is identified according to a sleep algorithm, and if the user falls asleep, the PPG signal of the second time is started at the first interval; the second time is less than the first time.

12. The processing method of claim 11, wherein the PPG signal is a green light signal, further comprising:

judging the signal quality of the PPG signal according to the interval characteristic of the PPG signal; the interval characteristic of the PPG signal is obtained by the interval difference of adjacent peaks;

when the adjacent intervals continuously generate mutation, the signal quality is judged to be not in accordance with the preset condition; and if the signal quality meets the preset condition, reading the signal, preprocessing the PPG signal, and removing the baseline signal to obtain a preprocessed PPG signal.

13. The processing method of claim 12, wherein acquiring a first signal feature of at least one dimension based on the PPG signal comprises:

acquiring the wave crest and the wave trough of the preprocessed PPG signal;

respectively interpolating the wave crest and the wave trough to obtain the upper and lower envelope characteristics of the green light signal;

based on peaks and troughs of the PPG signal; and obtaining the RR interval characteristics according to adjacent peaks or adjacent valleys.

14. The processing method of claim 13, wherein the obtaining peaks and troughs of the pre-processed PPG signal comprises:

judging whether the PPG point of the preprocessed PPG signal is a maximum value or a minimum value;

15. A device for processing a breathing rate, the device comprising:

a first acquisition module configured to acquire a PPG signal of a PPG sensor;

the fusion calculation module is configured to fuse the frequency domain energy maps to obtain a fused frequency domain energy map;

and the determining module is configured to select a frequency value with the highest score according to a pre-constructed fusion frequency domain energy scoring model and the fusion frequency domain energy scoring model based on the fusion frequency domain energy map, and determine a respiration rate value corresponding to the frequency value with the highest score.

16. A wearable device comprising a processor and a memory, the memory storing a computer program executable by the processor, the computer program when executed by the processor implementing the method of any of claims 1-14.

17. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-14.