CN107811610B - Respiration rate detection method and device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention provides a respiration rate detection method, a respiration rate detection device, electronic equipment and a storage medium, wherein the method comprises the following steps: collecting periodic audio signals generated when a target life object sleeps within a preset distance range, and framing the periodic audio signals by adopting a preset framing length; summing the amplitude absolute value of each frame of signal in the periodic audio signal after framing to obtain an audio energy signal, and acquiring a first signal frequency of the audio energy signal; and under the condition that the first signal frequency meets a preset breathing rate threshold range, taking the first signal frequency as the breathing rate of the target life object during sleeping. By adopting the invention, the detection error of the respiration rate can be reduced.
Description
Technical Field
The present invention relates to the field of electronic technologies, and in particular, to a respiration rate detection method and apparatus, an electronic device, and a storage medium.
Background
The sleep apnea hypopnea syndrome is a disease characterized by recurrent snoring, apnea and wakefulness in sleep, accompanied by a series of clinical manifestations such as daytime sleepiness, hypodynamia, reaction retardation and the like, and the disease is characterized by hypoxemia and sleep structural disorder, wherein the obstructive sleep apnea hypopnea syndrome is the most common. Generally, whether the subject is in a state of illness can be judged by testing the breathing rate of the subject during sleep.
The traditional respiration rate test method is generally completed by adopting contact detection instruments such as a test chest belt, a respiration tube and the like. For example, according to the phenomenon that the breathing tube and the chest and abdomen are periodically deformed by the periodic transformation of expiration and inspiration, the deformation is tried to be sensed to measure the breathing frequency, and for example, according to the characteristic that the temperature change in the nasal cavity is caused when the gas is exchanged with the external gas through the nasal cavity, the temperature change is converted into the change of electric quantity by using certain materials or elements to measure the breathing change, and for example, according to the principle that the breathing changes alternately along with the relaxation of muscles of the chest wall, the thoracic cage and the electrical impedance of body tissues, the alternating high-frequency electric signal is added at two ends of a measuring electrode, and the change is detected, and the breathing signal is extracted, so that the breathing rate is obtained. However, these methods require the person to be tested to wear the detection instrument, and the requirement for the placement position of the detection instrument is high, and the small displacement will cause the error to increase, thereby easily increasing the breathing rate detection error.
Disclosure of Invention
The embodiment of the invention provides a respiration rate detection method and device, electronic equipment and a storage medium, which can solve the problem that detection errors are increased due to movement of a test instrument.
The first aspect of the embodiments of the present invention provides a method for detecting a respiratory rate, including:
collecting periodic audio signals generated when a target life object sleeps within a preset distance range, and framing the periodic audio signals by adopting a preset framing length;
summing the amplitude absolute value of each frame of signal in the periodic audio signal after framing to obtain an audio energy signal, and acquiring a first signal frequency of the audio energy signal;
and under the condition that the first signal frequency meets a preset breathing rate threshold range, taking the first signal frequency as the breathing rate of the target life object during sleeping.
Optionally, the acquiring a first signal frequency of the audio energy signal includes:
acquiring the distance between every two adjacent energy peak points in the audio energy signal;
calculating the average value of the intervals between the adjacent energy peak points;
and taking the quotient of a preset sampling rate and the average value as the first signal frequency.
Optionally, the acquiring a first signal frequency of the audio energy signal includes:
performing chirp Z-transform on the audio energy signal;
acquiring the frequency of a target signal corresponding to a maximum value point in the energy of the audio energy signal after chirp Z conversion;
and taking the target signal frequency as the first signal frequency.
Optionally, after taking the first signal frequency as the breathing rate of the target living subject while sleeping, the method further comprises:
updating the audio energy signal by adopting a preset updating period;
acquiring a second signal frequency of the updated audio energy signal;
and if the variance between the second signal frequency and the first signal frequency is less than or equal to a preset threshold value, caching the second signal frequency.
Optionally, the method further includes:
and if the variance between the second signal frequency and the first signal frequency is greater than the preset threshold value, clearing the cache.
A second aspect of the embodiments of the present invention provides a respiration rate detection apparatus, including:
the signal framing module is used for collecting periodic audio signals generated when a target life object sleeps in a preset distance range and framing the periodic audio signals by adopting a preset framing length;
the first frequency acquisition module is used for summing the amplitude absolute value of each frame of signal in the periodic audio signal after framing processing to obtain an audio energy signal and acquiring a first signal frequency of the audio energy signal;
and the breathing rate determining module is used for taking the first signal frequency as the breathing rate of the target life object in the sleeping process under the condition that the first signal frequency meets a preset breathing rate threshold range.
Optionally, the first frequency obtaining module is specifically configured to:
acquiring the distance between every two adjacent energy peak points in the audio energy signal;
calculating the average value of the intervals between the adjacent energy peak points;
and taking the quotient of a preset sampling rate and the average value as the first signal frequency.
Optionally, the first frequency obtaining module is specifically configured to:
performing chirp Z-transform on the audio energy signal;
acquiring a target signal frequency corresponding to the maximum energy point of the audio energy signal after chirp Z conversion;
and taking the target signal frequency as the first signal frequency.
Optionally, the apparatus further comprises:
the signal updating module is used for updating the audio energy signal by adopting a preset updating period;
the second frequency acquisition module is used for acquiring a second signal frequency of the updated audio energy signal;
and the frequency caching module is used for caching the second signal frequency if the variance between the second signal frequency and the first signal frequency is less than or equal to a preset threshold value.
Optionally, the apparatus further comprises:
and the buffer clearing module is used for clearing the buffer if the variance between the second signal frequency and the first signal frequency is greater than the preset threshold.
A third aspect of embodiments of the present invention provides a computer storage medium, wherein the computer storage medium stores a plurality of instructions, and the instructions are adapted to be loaded by a processor and execute the method of the first aspect.
A fourth aspect of an embodiment of the present invention provides an electronic device, including: a processor and a memory; wherein the memory stores a computer program which, when executed by the processor, implements the method of the first aspect.
A fifth aspect of embodiments of the present invention provides an application program, which includes program instructions, and when executed, is configured to perform the method of the first aspect.
In the embodiment of the invention, the respiration rate detection device acquires periodic audio signals generated when a target life object sleeps within a preset distance range, performs framing processing on the acquired periodic audio signals by adopting a preset framing length, sums the amplitude absolute values of each frame of signals in the periodic audio signals after the framing processing to obtain audio energy signals, acquires a first signal frequency of the audio energy signals, and takes the first signal frequency as the respiration rate of the target life object when the first signal frequency meets a preset respiration rate threshold range. Compared with the prior art, the respiratory rate detection error can be increased by the micro movement of the instrument because a testee can detect the respiratory rate of the testee only by wearing a detection instrument, the testee can automatically acquire a periodic audio signal generated during sleeping in a preset distance range through a respiratory rate detection device without wearing the detection instrument, the periodic audio signal is subjected to signal processing to obtain a signal frequency after the signal processing, the respiratory rate during sleeping can be acquired when the signal frequency is determined to meet the respiratory rate threshold, the detection process is intelligent, simple and quick, the detection error increase caused by the position movement of the respiratory rate detection device can be avoided, and the respiratory rate detection error is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a respiration rate detection method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another respiration rate detection method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of waveforms before and after filtering an audio signal according to an embodiment of the present invention;
FIG. 4 is an interface diagram of the amplitude of an audio signal versus time according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a time domain waveform of an audio signal according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a frequency domain waveform of an audio signal according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a respiration rate detecting apparatus according to an embodiment of the present invention;
FIG. 8 is a schematic structural diagram of another respiration rate detecting device according to an embodiment of the present invention;
fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
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. All other embodiments, which can be obtained by a person skilled in the art without inventive effort based on the embodiments of the present invention, are within the scope of the present invention.
It is to be understood that the terminology used in the embodiments of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. In addition, the terms "first," "second," "third," and "fourth," etc. in the description and claims of the invention and the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
The respiration rate detection method provided by the embodiment of the invention can be applied to application scenes of respiration rate tests, such as: the respiration rate detection device acquires periodic audio signals generated when a target life object sleeps within a preset distance range, performs framing processing on the acquired periodic audio signals by adopting a preset framing length, sums amplitude absolute values of each frame of signals in the framed periodic audio signals to obtain audio energy signals, acquires a first signal frequency of the audio energy signals, and takes the first signal frequency as the respiration rate of the target life object when the first signal frequency meets a preset respiration rate threshold range. Compared with the prior art, the respiratory rate detection error can be increased by the micro movement of the instrument because a testee can detect the respiratory rate of the testee only by wearing a detection instrument, the testee can automatically acquire a periodic audio signal generated during sleeping in a preset distance range through a respiratory rate detection device without wearing the detection instrument, the periodic audio signal is subjected to signal processing to obtain a signal frequency after the signal processing, the respiratory rate during sleeping can be acquired when the signal frequency is determined to meet the respiratory rate threshold, the detection process is intelligent, simple and quick, the detection error increase caused by the position movement of the respiratory rate detection device can be avoided, and the respiratory rate detection error is reduced.
The respiration rate detection device according to the embodiment of the present invention may be any device having storage and test functions, for example: tablet computers, mobile phones, electronic readers, Personal Computers (PCs), notebook computers, vehicle-mounted devices, network televisions, wearable devices, and the like.
The respiration rate detection method provided by the embodiment of the invention will be described in detail below with reference to fig. 1 to 6.
Referring to fig. 1, a flow chart of a respiration rate detection method according to an embodiment of the present invention is schematically shown. As shown in fig. 1, the method of the embodiment of the present invention may include the following steps S101 to S103.
S101, collecting periodic audio signals generated when a target life object sleeps in a preset distance range, and performing framing processing on the periodic audio signals by adopting a preset framing length.
In particular, the target vital object may be a subject having vital signs, such as a human or an animal. The target living subject may generate audio signals such as an expiratory and inspiratory sound signal, a snore signal, etc. while sleeping. Because the time intervals of the snore signals are approximately equal, the amplitudes of the snore signals are basically consistent, the snore signals are closely related to the breathing rhythm of a human body, and the snore signals are periodic signals, the sound frequency detection device is used for collecting audio signals around (nearby, such as within a range of less than 0.3 m) the human or animal is sleeping, extracting the periodic audio signals in the audio signals, preliminarily taking the periodic audio signals as normal snore signals, and then performing framing processing on the extracted periodic audio signals. The framing processing is to set a plurality of continuously sampled points as one frame by using a preset framing length, so as to divide the acquired audio signal into a plurality of frame signals.
It should be noted that signal framing generally requires that a frame signal at least has to contain more than 2 fundamental periods in order to be able to display the characteristics of the audio signal. For example, for a known human voice, the pitch range is about 50Hz to 1000Hz, and if the sampling frequency fs is 8000Hz, the number of points per fundamental period is fs/f 8000/50 to 160 when the pitch f is 50Hz (e.g., a man low-pitched song), so each frame must be at least 320 points, and if the pitch is 1000Hz (e.g., a man high-pitched song), the number of points per fundamental period is 8000/1000 to 8, so each frame must include at least 16 points.
Optionally, the length of each frame signal cannot be too long, too long sub-frames cannot represent the subtle phenomenon that the characteristics of the audio signal change with time, and the calculation amount also becomes large.
S102, summing the absolute amplitude values of each frame of signal in the periodic audio signal after framing processing to obtain an audio energy signal, and acquiring a first signal frequency of the audio energy signal.
Specifically, after the periodic audio signal is subjected to framing processing, the absolute amplitude values of each frame of signal are summed, so that an audio energy signal, that is, a graph of audio signal energy changing with frequency, is obtained, the signal frequency of the graph is obtained, and the obtained signal frequency is used as the first signal frequency.
In a possible embodiment, the distance between each adjacent energy maximum peak point in the audio energy signal is obtained, an average value of the distances between each adjacent energy maximum peak point is calculated, and a quotient of a preset sampling rate and the average value is taken as the first signal frequency.
In another possible implementation manner, Chirp Z (CZT) conversion is performed on the audio energy signal, a target signal frequency corresponding to an energy maximum point in the converted audio energy signal is obtained, and the target signal frequency is taken as the first signal frequency.
In yet another possible embodiment, the distance between each adjacent energy peak point in the audio energy signal is obtained, an average value of the distances between each adjacent energy peak point is calculated, and then a quotient of a preset sampling rate and the average value is calculated. And simultaneously, carrying out CZT conversion on the audio energy signal, and acquiring the target signal frequency corresponding to the energy maximum point in the converted audio energy signal. And calculating the difference value between the quotient and the target signal frequency, determining that the calculation of the first signal frequency is accurate when the difference value does not exceed the range of a preset threshold value, and taking any value of the quotient or the target signal frequency as the first signal frequency. And outputting error early warning information when the difference value exceeds a preset threshold range.
And S103, taking the first signal frequency as the breathing rate of the target life object in the sleeping process under the condition that the first signal frequency meets a preset breathing rate threshold range.
Specifically, under normal conditions, the breathing rate of a human body during sleep is 10-60 times/minute (the breathing rate of an infant can be expanded to 10-80 times/minute), the signal frequency of the snore signal is consistent with the breathing rate, the periodic audio signal preliminarily determined in the step S101 is further judged to be the normal snore signal, if the first signal frequency of the periodic audio signal meets a preset breathing rate threshold range (for example, 10-60 times/minute), it is indicated that the periodic audio signal is the normal snore signal, and then the breathing rate at the moment is the first signal frequency.
In the implementation of the invention, the respiration rate detection device acquires periodic audio signals generated when a target life object sleeps within a preset distance range, performs framing processing on the acquired periodic audio signals by adopting a preset framing length, sums the amplitude absolute values of each frame of signals in the framed periodic audio signals to obtain audio energy signals, acquires a first signal frequency of the audio energy signals, and takes the first signal frequency as the respiration rate of the target life object when the first signal frequency meets a preset respiration rate threshold range. Compared with the prior art, the respiratory rate detection error can be increased by the micro movement of the instrument because a testee can detect the respiratory rate of the testee only by wearing a detection instrument, the testee can automatically acquire a periodic audio signal generated during sleeping in a preset distance range through a respiratory rate detection device without wearing the detection instrument, the periodic audio signal is subjected to signal processing to obtain a signal frequency after the signal processing, the respiratory rate during sleeping can be acquired when the signal frequency is determined to meet the respiratory rate threshold, the detection process is intelligent, simple and quick, the detection error increase caused by the position movement of the respiratory rate detection device can be avoided, and the respiratory rate detection error is reduced.
Referring to fig. 2, a flow chart of another respiration rate detection method according to an embodiment of the invention is shown. As shown in fig. 2, the method of the embodiment of the present invention may include the following steps S201 to S210.
S201, collecting periodic audio signals generated when a target life object sleeps in a preset distance range, and performing framing processing on the periodic audio signals by adopting a preset framing length.
In particular, the target vital object may be a subject having vital signs, such as a human or an animal. The target living subject may generate audio signals such as an expiratory and inspiratory sound signal, a snore signal, etc. while sleeping. Because the time intervals of the snore signals are approximately equal, the amplitudes of the snore signals are basically consistent, the snore signals are closely related to the breathing rhythm of a human body, and the snore signals are periodic signals, the sound frequency detection device is used for collecting audio signals around (nearby, such as within a range of less than 0.3 m) the human or animal is sleeping, extracting the periodic audio signals in the audio signals, preliminarily taking the periodic audio signals as normal snore signals, and then performing framing processing on the extracted periodic audio signals. The framing processing is to set a plurality of continuously sampled points as one frame by using a preset framing length, so as to divide the acquired audio signal into a plurality of frame signals.
It should be noted that signal framing generally requires that a frame signal at least has to contain more than 2 fundamental periods in order to be able to display the characteristics of the audio signal. For example, for a known human voice, the pitch range is about 50Hz to 1000Hz, and if the sampling frequency fs is 8000Hz, the number of points per fundamental period is fs/f 8000/50 to 160 when the pitch f is 50Hz (e.g., a man low-pitched song), so each frame must be at least 320 points, and if the pitch is 1000Hz (e.g., a man high-pitched song), the number of points per fundamental period is 8000/1000 to 8, so each frame must include at least 16 points.
Optionally, the length of each frame signal cannot be too long, too long sub-frames cannot represent the subtle phenomenon that the characteristics of the audio signal change with time, and the calculation amount also becomes large.
S202, summing the absolute value of the amplitude of each frame signal in the periodic audio signal after framing processing to obtain an audio energy signal.
Specifically, after the periodic audio signal is subjected to framing processing, the absolute amplitude values of each frame of signal are summed to obtain an audio energy signal, i.e., a graph of the audio signal energy changing with frequency.
For example, as shown in fig. 3, a periodic audio signal is obtained, and a time domain graph of the signal energy of the audio signal with frequency is shown in fig. 4, wherein the energy curve reaches a preset statistical duration (e.g., 1 min).
Optionally, since the audio energy signal may contain local noise signals such as glitches, in order to reduce the calculation error, the noise in the audio energy signal may be filtered. The noise filtering may be filtering by using a filter, such as a smoothing filter.
For example, the waveforms of the audio energy signal before and after filtering are shown in fig. 5. The waveform has more burrs before filtering, and becomes smooth after filtering.
S203, acquiring the distance between each adjacent signal energy peak point in the audio energy signal.
For example, according to the audio energy signal shown in fig. 4, each energy peak point is recorded, and the energy peak point refers to the instantaneous maximum value of the amplitude or energy within a preset statistical time period, as shown in fig. 4, M1-M16 are all the energy peak points of the audio energy signal, and then the distances between each adjacent energy peak points are calculated as D1, D2, D3, …, Dn.
Optionally, the distance between the maximum values of the energy of each adjacent signal in the audio energy signal after the noise is filtered out as shown in fig. 5 is obtained.
And S204, calculating the average value of the distances between the energy peak points of the adjacent signals.
Specifically, the average value D of the energy peak point distances is (D1+ D2+ D3+ … + Dn)/2, which is obtained from the distances between the adjacent energy peak points.
And S205, taking the quotient of a preset sampling rate and the average value as the first signal frequency.
Specifically, if the preset sampling rate is fs, the first signal frequency is fs/D (times/second) ═ 60 × fs/D (times/min).
Optionally, performing chirp Z-transform on the audio energy signal;
acquiring the frequency of a target signal corresponding to an energy maximum value point in the audio energy signal after chirp Z conversion;
and taking the target signal frequency as the first signal frequency.
Specifically, if Fast Fourier Transform (FFT) is performed on the determined energy curve of the audio energy signal, a corresponding signal spectrum can be obtained. However, the FFT transform causes a low spectral resolution due to insufficient FFT points in the spectral range, which results in a large error of the calculation result. Therefore, in order to improve the spectral resolution, the frequency band in the spectral range may be refined by using the chirp Z transform, that is, the CZT transform, so as to obtain a more accurate spectral curve of the periodic audio signal, obtain a signal frequency corresponding to a maximum signal energy point in the spectral curve, and determine the signal frequency as the frequency of the audio energy signal. For example, if the signal sampling rate is 20Hz, the signal spectrum range is 0-10 Hz, the effective spectrum range of the respiration rate obtained by detecting the maximum range of 10-80 times/minute according to the respiration rate is 0-1.5 Hz, and is only 1/5 of the signal spectrum range, in order to improve the spectrum resolution, CZT conversion can be performed on the audio energy signal within the range of 0-1.5 Hz to directly and compactly take values within the frequency band of 0-1.5 Hz, the number of frequency points is increased, so that the frequency spectrum of the frequency band of 0-1.5 Hz is refined, and then the corresponding spectrum value is calculated, because CZT conversion can analyze the spectrum structure of any narrow-band signal on the frequency axis with specified and high enough resolution.
For example, fig. 6 is obtained by performing CZT conversion on the two signals before and after the filtering in fig. 5, so that the frequency P at the maximum value (main peak) of the amplitude of the spectrum signal can be easily determined and taken as the frequency (first signal frequency) of the periodic audio signal.
And S206, when the first signal frequency meets a preset breathing rate threshold range, taking the first signal frequency as the breathing rate of the target life object during sleeping.
Specifically, under normal conditions, when the breathing rate of a human body during sleep is sound within a range of 10-60 times/minute (the breathing rate of an infant can be expanded to 10-80 times/minute), the signal frequency of a snore signal is consistent with the breathing rate, the periodic audio signal preliminarily determined in the step S101 is further judged to be the normal snore signal, if the first signal frequency of the periodic audio signal meets a preset breathing rate threshold range (for example, 10-60 times/minute), it is indicated that the periodic audio signal is the normal snore signal, and then, the breathing rate at the time is the first signal frequency.
And S207, updating the audio energy signal by adopting a preset updating period.
Specifically, if the preset update period is assumed to be 10s, the respiration rate detection device performs framing processing on the newly acquired audio signal, sums the absolute amplitude value of each frame of signal, adds the result to the last 10s of the energy curve of the cached preset duration (1min), and removes the audio energy signal of the first 10s of the energy curve of the cached preset duration (1min) to complete one-time update.
S208, acquiring the second signal frequency of the updated audio energy signal.
Specifically, the signal frequency of the updated audio energy signal can be obtained by the method described in S203-S205, and the signal frequency is taken as the second signal frequency, which is not described herein again.
S209, if the variance between the second signal frequency and the first signal frequency is less than or equal to a preset threshold, buffering the second signal frequency.
Specifically, if the first signal frequency is f1 and the second signal frequency is f2, the variance S12＝(f22-f12). Assuming that the preset threshold is 5, at S12Is less than or equal toAt time 5, it is stated that the periodic audio signal is still a normal snore signal and the signal is stable, and the second signal frequency is buffered for calculating the third signal frequency after the audio energy signal is updated at a later stage.
Optionally, if the total variance of the signal frequencies after multiple updates is less than or equal to the preset threshold, it indicates that the updated periodic audio signal is a steady-state signal.
S210, if the variance between the second signal frequency and the first signal frequency is larger than the preset threshold value, the cache is cleared.
Specifically, if S12If the frequency of the second signal is not reliable, the cached second signal frequency can be cleared.
Optionally, for accuracy of calculation, the audio energy signal may be updated after the audio signal is acquired for multiple times, and the variance is calculated after each update, and if most or all of the variances calculated for multiple times exceed the preset threshold, the audio signal is not continuously acquired, and the cached unstable frequency value is removed.
In the implementation of the invention, the respiration rate detection device acquires periodic audio signals generated by a target life object in a preset distance range during sleep, performs framing processing on the acquired periodic audio signals by adopting a preset framing length, sums the amplitude absolute values of each frame of signals in the framed periodic audio signals to obtain audio energy signals, acquires a first signal frequency of the audio energy signals, and when the first signal frequency meets a preset respiration rate threshold range, takes the first signal frequency as the respiration rate of the target life object during sleep, periodically updates the periodic audio signals, and re-detects the updated periodic audio signals. Compared with the prior art, the respiratory rate detection error is increased by the tiny movement of the detector because the tested person can detect the respiratory rate of the tested person only by wearing the detector, the tested person in the invention can not wear the detector, a breathing rate detection device automatically collects periodic audio signals generated during sleep in a preset distance range, and the periodic audio signals are subjected to signal processing to obtain signal frequency after the signal processing, when the signal frequency is determined to meet the breathing rate threshold, the breathing rate during sleep can be acquired, on one hand, the detection process is intelligent, simple and quick, the detection error cannot be increased and reduced due to the position movement of the breathing rate detection device, on the other hand, the accuracy of the respiration rate detection is further improved through the updating processing and the stability judgment of the audio energy signal.
Fig. 7 is a schematic structural diagram of a respiration rate detecting device according to an embodiment of the present invention. As shown in fig. 7, the respiration rate detection apparatus 1 according to the embodiment of the present invention may include: a signal framing module 11, a first frequency acquisition module 12 and a respiration rate determination module 13.
The signal framing module 11 is configured to collect a periodic audio signal generated when a target living object sleeps within a preset distance range, and perform framing processing on the periodic audio signal by using a preset framing length.
In particular, the target vital object may be a subject having vital signs, such as a human or an animal. The target living subject may generate audio signals such as an expiratory and inspiratory sound signal, a snore signal, etc. while sleeping. Because the time intervals of the snore signals are approximately equal, the amplitudes of the snore signals are basically consistent, the snore signals are closely related to the breathing rhythm of a human body and are periodic signals, the audio signals around (nearby, such as within the range of less than 0.3 m) when a person or an animal sleeps are collected through the signal framing module, the periodic audio signals in the audio signals are extracted, the periodic audio signals are preliminarily taken as normal snore signals, and then the extracted periodic audio signals are subjected to framing processing. The framing processing is to set a plurality of continuously sampled points as one frame by using a preset framing length, so as to divide the acquired audio signal into a plurality of frame signals.
It should be noted that signal framing generally requires that a frame signal at least has to contain more than 2 fundamental periods in order to be able to display the characteristics of the audio signal. For example, for a known human voice, the pitch range is about 50Hz to 1000Hz, and if the sampling frequency fs is 8000Hz, the number of points per fundamental period is fs/f 8000/50 to 160 when the pitch f is 50Hz (e.g., a man low-pitched song), so each frame must be at least 320 points, and if the pitch is 1000Hz (e.g., a man high-pitched song), the number of points per fundamental period is 8000/1000 to 8, so each frame must include at least 16 points.
Optionally, the length of each frame signal cannot be too long, too long sub-frames cannot represent the subtle phenomenon that the characteristics of the audio signal change with time, and the calculation amount also becomes large.
The first frequency obtaining module 12 is configured to sum absolute values of amplitudes of each frame of signals in the periodic audio signal after the framing processing to obtain an audio energy signal, and obtain a first signal frequency of the audio energy signal.
Specifically, after the periodic audio signal is subjected to framing processing, the absolute amplitude values of each frame of signal are summed, so that audio signal energy, that is, a graph of the audio signal energy changing with frequency, is obtained, the signal frequency of the graph is obtained, and the obtained signal frequency is used as the first signal frequency.
Optionally, the first frequency obtaining module 12 is specifically configured to:
acquiring the distance between every two adjacent energy peak points in the audio energy signal;
calculating the average value of the intervals between the adjacent energy peak points;
and taking the quotient of a preset sampling rate and the average value as the first signal frequency.
Optionally, the first frequency obtaining module 12 is specifically configured to:
performing chirp Z-transform on the audio energy signal;
acquiring a target signal frequency corresponding to the maximum energy point of the audio energy signal after chirp Z conversion;
and taking the target signal frequency as the first signal frequency.
Optionally, the frequency obtaining module 12 is specifically configured to: and acquiring the distance between every two adjacent signal energy peak points in the audio energy signal, calculating the average value of the distances between every two adjacent energy peak points, and calculating the quotient of a preset sampling rate and the average value. And simultaneously, performing chirp Z conversion on the audio energy signal to obtain the target signal frequency corresponding to the maximum value point in the audio signal energy subjected to the chirp Z conversion. And calculating the difference value between the quotient and the target signal frequency, determining that the calculation of the first signal frequency is accurate when the difference value does not exceed the range of a preset threshold value, and taking any value of the quotient or the target signal frequency as the first signal frequency. And outputting error early warning information when the difference value exceeds a preset threshold range.
And the breathing rate determining module 13 is configured to, when the first signal frequency meets a preset breathing rate threshold range, take the first signal frequency as a breathing rate of the target living object during sleep.
Specifically, under normal conditions, the breathing rate of a human body during sleep is 10-60 times/minute (the breathing rate of an infant can be expanded to 10-80 times/minute), the signal frequency of the snore signal is consistent with the breathing rate, the preliminarily determined periodic audio signal is further judged to be the normal snore signal, if the first signal frequency of the periodic audio signal meets a preset breathing rate threshold range (for example, 10-60 times/minute), it is indicated that the periodic audio signal is the normal snore signal, and then the breathing rate at the moment is the first signal frequency.
Optionally, as shown in fig. 8, the apparatus 1 further includes:
a signal updating module 14, configured to update the periodic audio energy signal by using a preset updating period;
a second frequency obtaining module 15, configured to obtain a second signal frequency of the updated audio energy signal;
a frequency buffer module 16, configured to buffer the second signal frequency if a variance between the second signal frequency and the first signal frequency is smaller than or equal to a preset threshold.
In particular, if it is assumed thatThe preset updating period is 10S, the respiration rate detection device performs framing processing on the newly acquired audio signal, sums the amplitude absolute value of each frame of signal, adds the processed audio signal to the energy information of the last 10S in the energy curve of the cached preset duration (1min), and clears the audio energy signal of the first 10S in the energy curve of the cached preset duration (1min) to complete one updating, and can obtain the second signal frequency of the updated audio signal by adopting the same method, if the first signal frequency is f1 and the second signal frequency is f2, the variance is S12＝(f22-f12). Assuming that the preset threshold is 5, at S12And when the signal frequency is less than or equal to 5, the periodic audio signal is still a normal snore signal and is stable, and the second signal frequency is cached for calculating a third signal frequency after the audio energy signal is updated at a later stage.
Optionally, as shown in fig. 8, the apparatus 1 further includes:
a buffer removal module 17, configured to remove the buffer if a variance between the second signal frequency and the first signal frequency is greater than the preset threshold.
Specifically, if S12If the frequency of the second signal is not reliable, the cached second signal frequency can be cleared.
Optionally, for accuracy of calculation, the audio energy signal may be updated after the audio signal is acquired for multiple times, and the variance is calculated after each update, and if most or all of the variances calculated for multiple times exceed the preset threshold, the periodic audio signal is no longer continuously acquired, and the cached unstable frequency value is cleared.
In the implementation of the invention, the respiration rate detection device acquires periodic audio signals generated by a target life object in a preset distance range during sleep, performs framing processing on the acquired periodic audio signals by adopting a preset framing length, sums the amplitude absolute values of each frame of signals in the framed periodic audio signals to obtain audio energy signals, acquires a first signal frequency of the audio energy signals, and when the first signal frequency meets a preset respiration rate threshold range, takes the first signal frequency as the respiration rate of the target life object during sleep, periodically updates the periodic audio signals, and re-detects the updated periodic audio signals. Compared with the prior art, the respiratory rate detection error is increased by the tiny movement of the detector because the tested person can detect the respiratory rate of the tested person only by wearing the detector, the tested person in the invention can not wear the detector, a breathing rate detection device automatically collects periodic audio signals generated during sleep in a preset distance range, and the periodic audio signals are subjected to signal processing to obtain signal frequency after the signal processing, when the signal frequency is determined to meet the breathing rate threshold, the breathing rate during sleep can be acquired, on one hand, the detection process is intelligent, simple and quick, the detection error cannot be increased and reduced due to the position movement of the breathing rate detection device, on the other hand, the accuracy of the respiration rate detection is further improved through the updating processing and the stability judgment of the audio energy signal.
Fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 9, the electronic device 1000 may include: at least one processor 1001, such as a CPU, at least one network interface 1004, a user interface 1003, memory 1005, at least one communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display) and a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a standard wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 1005 may optionally be at least one memory device located remotely from the processor 1001. As shown in fig. 9, memory 1005, which is one type of computer storage medium, may include an operating system, a network communication module, a user interface module, and a breath rate detection application.
In the electronic apparatus 1000 shown in fig. 9, the user interface 1003 is mainly used as an interface for providing input for the user; and the processor 1001 may be configured to invoke the respiration rate detection application stored in the memory 1005 and specifically perform the following operations:
collecting periodic audio signals generated when a target life object sleeps within a preset distance range, and framing the periodic audio signals by adopting a preset framing length;
summing the amplitude absolute value of each frame of signal in the periodic audio signal after framing to obtain an audio energy signal, and acquiring a first signal frequency of the audio energy signal;
and under the condition that the first signal frequency meets a preset breathing rate threshold range, taking the first signal frequency as the breathing rate of the target life object during sleeping.
In one embodiment, when the processor 1001 obtains the first signal frequency of the audio energy signal, it specifically performs the following steps:
acquiring the distance between every two adjacent energy peak points in the audio energy signal;
calculating the average value of the intervals between the adjacent energy peak points;
and taking the quotient of a preset sampling rate and the average value as the first signal frequency.
In one embodiment, when the processor 1001 obtains the first signal frequency of the audio energy signal, it specifically performs the following steps:
performing chirp Z-transform on the audio energy signal;
acquiring the frequency of a target signal corresponding to an energy maximum value point in the audio energy signal after chirp Z conversion;
and taking the target signal frequency as the first signal frequency.
In one embodiment, the processor 1001, after executing the first signal frequency as the breathing rate of the target living subject while sleeping, further executes the steps of:
updating the audio energy signal by adopting a preset updating period;
acquiring a second signal frequency of the updated audio energy signal;
and if the variance between the second signal frequency and the first signal frequency is less than or equal to a preset threshold value, caching the second signal frequency.
In one embodiment, the processor 1001 further performs the steps of:
and if the variance between the second signal frequency and the first signal frequency is greater than the preset threshold value, clearing the cache.
In the implementation of the invention, the respiration rate detection device acquires periodic audio signals generated by a target life object in a preset distance range during sleep, performs framing processing on the acquired periodic audio signals by adopting a preset framing length, sums the amplitude absolute values of each frame of signals in the framed periodic audio signals to obtain audio energy signals, acquires a first signal frequency of the audio energy signals, and when the first signal frequency meets a preset respiration rate threshold range, takes the first signal frequency as the respiration rate of the target life object during sleep, periodically updates the periodic audio signals, and re-detects the updated periodic audio signals. Compared with the prior art, the respiratory rate detection error is increased by the tiny movement of the detector because the tested person can detect the respiratory rate of the tested person only by wearing the detector, the tested person in the invention can not wear the detector, a breathing rate detection device automatically collects periodic audio signals generated during sleep in a preset distance range, and the periodic audio signals are subjected to signal processing to obtain signal frequency after the signal processing, when the signal frequency is determined to meet the breathing rate threshold, the breathing rate during sleep can be acquired, on one hand, the detection process is intelligent, simple and quick, the detection error cannot be increased and reduced due to the position movement of the breathing rate detection device, on the other hand, the accuracy of the respiration rate detection is further improved through the updating processing and the stability judgment of the audio energy signal.
Embodiments of the present invention also provide a computer storage medium (non-transitory computer-readable storage medium) storing a computer program comprising program signaling, which when executed by a computer, which may be part of the above-mentioned respiration rate detection apparatus or electronic device, causes the computer to perform the method according to the aforementioned embodiments.
The non-transitory computer readable storage medium described above may take any combination of one or more computer readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a flash Memory, an optical fiber, a portable compact disc Read Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of Network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The embodiment of the present application also provides a computer program product, and when the instructions in the computer program product are executed by a processor, the respiration rate detection method provided by the embodiment shown in fig. 1 or fig. 2 of the present application can be implemented.
Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions. For the specific working processes of the system, the apparatus and the unit described above, reference may be made to the corresponding processes in the foregoing method embodiments, and details are not described here again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus 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.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
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, the technical solution of the present application may be substantially implemented or contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. A method of breath rate detection, comprising:
collecting periodic audio signals generated when a target life object sleeps within a preset distance range, and framing the periodic audio signals by adopting a preset framing length;
summing the amplitude absolute value of each frame of signal in the periodic audio signal after framing to obtain an audio energy signal, and acquiring a first signal frequency of the audio energy signal;
taking the first signal frequency as the breathing rate of the target life object during sleeping under the condition that the first signal frequency meets a preset breathing rate threshold range;
wherein the obtaining a first signal frequency of the audio energy signal comprises:
acquiring the distance between every two adjacent energy peak points in the audio energy signal;
calculating the average value of the intervals between the adjacent energy peak points;
calculating the quotient of a preset sampling rate and the average value;
performing chirp Z-transform on the audio energy signal;
acquiring a target signal frequency corresponding to the maximum energy point of the audio energy signal after chirp Z conversion;
calculating a difference value between the quotient and the target signal frequency, and taking any value of the quotient or the target signal frequency as a first signal frequency when the difference value does not exceed a preset threshold range;
and outputting error early warning information when the difference value exceeds a preset threshold range.
2. The method of claim 1, wherein after taking the first signal frequency as a breathing rate of the target living subject while sleeping, the method further comprises:
updating the audio energy signal by adopting a preset updating period;
acquiring a second signal frequency of the updated audio energy signal;
and if the variance between the second signal frequency and the first signal frequency is less than or equal to a preset threshold value, caching the second signal frequency.
3. The method of claim 2, further comprising:
and if the variance between the second signal frequency and the first signal frequency is greater than the preset threshold value, clearing the cache.
4. A respiration rate detection device, comprising:
the signal framing module is used for collecting periodic audio signals generated when a target life object sleeps in a preset distance range and framing the periodic audio signals by adopting a preset framing length;
the first frequency acquisition module is used for summing the amplitude absolute value of each frame of signal in the periodic audio signal after framing processing to obtain an audio energy signal and acquiring a first signal frequency of the audio energy signal;
the breathing rate determining module is used for taking the first signal frequency as the breathing rate of the target life object in the sleeping process under the condition that the first signal frequency meets a preset breathing rate threshold range;
the first frequency acquisition module is specifically configured to:
acquiring the distance between every two adjacent energy peak points in the audio energy signal;
calculating the average value of the intervals between the adjacent energy peak points;
calculating the quotient of a preset sampling rate and the average value;
performing chirp Z-transform on the audio energy signal;
acquiring a target signal frequency corresponding to the maximum energy point of the audio energy signal after chirp Z conversion;
calculating a difference value between the quotient and the target signal frequency, and taking any value of the quotient or the target signal frequency as a first signal frequency when the difference value does not exceed a preset threshold range;
and outputting error early warning information when the difference value exceeds a preset threshold range.
5. The apparatus of claim 4, further comprising:
the signal updating module is used for updating the audio energy signal by adopting a preset updating period;
the second frequency acquisition module is used for acquiring a second signal frequency of the updated audio energy signal;
and the frequency caching module is used for caching the second signal frequency if the variance between the second signal frequency and the first signal frequency is less than or equal to a preset threshold value.
6. The apparatus of claim 5, further comprising:
and the buffer clearing module is used for clearing the buffer if the variance between the second signal frequency and the first signal frequency is greater than the preset threshold.
7. A computer storage medium having stored thereon a plurality of instructions adapted to be loaded by a processor and to perform the method according to any of claims 1 to 3.
8. An electronic device, comprising: a processor and a memory; wherein the memory stores a computer program which, when executed by the processor, implements the method of any of claims 1 to 3.
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