CN110013221B - Nasal pressure detection method and device and nasal pressure detector - Google Patents
Nasal pressure detection method and device and nasal pressure detector Download PDFInfo
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- CN110013221B CN110013221B CN201910182719.4A CN201910182719A CN110013221B CN 110013221 B CN110013221 B CN 110013221B CN 201910182719 A CN201910182719 A CN 201910182719A CN 110013221 B CN110013221 B CN 110013221B
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Abstract
The embodiment of the invention relates to the technical field of sleep monitoring, and particularly discloses a nasal pressure detection method, a nasal pressure detection device, a nasal pressure detector and a computer storage medium, wherein the method comprises the following steps: acquiring nasal pressure data in a nasal pressure detection sliding window; judging whether a characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is smaller than a preset first threshold value or not; if so, a loss of nasal pressure event is determined to be present. Therefore, by using the scheme of the invention, the condition of nasal pressure loss of the user can be judged, thereby providing a basis for judging whether the user has apnea.
Description
Technical Field
The embodiment of the invention relates to the technical field of sleep monitoring, in particular to a nasal pressure detection method and device, a nasal pressure detector and a computer storage medium.
Background
Apnea syndrome is an obstructive or central sleep apnea syndrome, separate from sleep, in which the patient repeatedly experiences cessation of respiratory airflow during sleep for periods exceeding 10 seconds or less than 20% of normal airflow.
And the user with sleep apnea syndrome inhales less oxygen than normal people due to apnea in the sleep process, so that the oxygen in blood is reduced, and the memory is influenced. And the condition of nasal pressure loss of the user can effectively reflect the condition of apnea of the user. Therefore, a method for checking the absence of nasal pressure of a user is urgently needed.
Disclosure of Invention
In view of the above, embodiments of the present invention are proposed in order to provide a method, an apparatus, a nasal pressure detector and a computer storage medium for monitoring apnea that overcome the above problems or at least partially solve the above problems.
In order to solve the technical problem, one technical scheme adopted by the embodiment of the invention is as follows: the nasal pressure detection method comprises the steps of obtaining nasal pressure data in a nasal pressure detection sliding window; judging whether a characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is smaller than a preset first threshold value or not; if so, a loss of nasal pressure event is determined to be present.
Optionally, the obtaining of nasal pressure data in the nasal pressure detection sliding window specifically includes: in the nasal pressure detection sliding window, sampling nasal pressure data are acquired according to a preset sampling step length, and the nasal pressure detection sliding window slides backwards according to the sampling step length.
Optionally, acquire the nose and press the data that detects in the sliding window, specifically do: in the nasal pressure detection sliding window, sampling nasal pressure data are acquired according to a preset sampling step length, and the nasal pressure detection sliding window slides backwards according to the length of the nasal pressure detection sliding window.
Optionally, the characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is: and in the nasal pressure detection sliding window, the absolute value of the difference value of the sampled maximum nasal pressure data and the sampled minimum nasal pressure data.
Optionally, the method further comprises: determining the number of times of loss of nasal pressure based on the loss of nasal pressure event; the determining the number of times of loss of nasal pressure according to the loss of nasal pressure event specifically comprises: and dividing the times of the continuous occurrence of the nasal pressure missing events by a preset second threshold value, and then rounding upwards, and determining the rounded value as the nasal pressure missing times.
Optionally, the method further comprises: determining whether apnea exists according to the nasal pressure loss times; the determining whether apnea exists according to the nasal pressure loss times specifically comprises: and summing all the missing nasal pressure times in the sleep period, judging whether the summed missing nasal pressure times are greater than a preset third threshold value, and if so, determining that the apnea exists.
Optionally, the method further comprises: determining whether apnea exists according to the nasal pressure loss times; the determining whether apnea exists according to the nasal pressure loss times specifically comprises the following steps: counting the maximum value of all nasal pressure loss times in the sleep period, judging whether the maximum value is greater than a preset fourth threshold value, and if so, determining that apnea exists.
In order to solve the above technical problem, another technical solution adopted by the embodiment of the present invention is: provided is a nasal pressure detection device including: the acquisition module is used for acquiring nasal pressure data in the nasal pressure detection sliding window; the judging module is used for judging whether the maximum nasal pressure difference in the nasal pressure detection sliding window is smaller than a preset first threshold value or not; a first determination module to determine that a nasal pressure loss event exists.
In order to solve the above technical problem, another technical solution adopted in the embodiments of the present invention is: there is provided a nasal pressure detector comprising: the nasal pressure acquisition device comprises a nasal pressure acquisition device, a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus; the nasal pressure acquisition device is used for acquiring nasal pressure data of a user and sending the acquired nasal pressure data to the processor; the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the nasal pressure detection method.
In order to solve the above technical problem, another technical solution adopted in the embodiments of the present invention is: a computer storage medium is provided, which stores at least one executable instruction, which causes a processor to execute operations corresponding to a nasal pressure detection method as described above.
The embodiment of the invention has the beneficial effects that: different from the prior art, the embodiment of the invention judges the condition of nasal pressure loss of the user by detecting the discrete degree of the nasal pressure data in the sliding window through the nasal pressure, thereby providing a basis for judging whether the user has apnea.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more comprehensible.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart of a method for detecting nasal pressure according to an embodiment of the present invention;
FIG. 2 is a schematic view of a sliding manner of a sliding window of the nasal pressure detection method according to the embodiment of the present invention;
FIG. 3 is a schematic view of another sliding manner of a sliding window of the nasal pressure detection method according to the embodiment of the present invention;
FIG. 4 is a flow chart of a nasal pressure detection method according to another embodiment of the present invention;
FIG. 5 is a schematic diagram of a continuous absence of nasal pressure event in an embodiment of the method of detecting nasal pressure of the present invention;
FIG. 6 is a flowchart illustrating a nasal pressure detection method according to a third embodiment of the present invention;
FIG. 7 is a diagram of an apparatus according to an embodiment of a nasal pressure detection apparatus of the present invention;
fig. 8 is a schematic diagram of the internal structure of an embodiment of the nasal pressure detector of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the method is mainly applied to the nasal pressure detector, the nasal pressure detector can collect the nasal pressure data of the user through the pressure sensor and analyze the collected nasal pressure data to judge whether the nasal pressure of the user is normal.
Referring to fig. 1, fig. 1 is a flowchart illustrating a nasal pressure detecting method according to an embodiment of the invention. The method comprises the following steps:
step S101: obtaining nasal pressure data within the nasal pressure detection sliding window.
The nasal pressure detection sliding window refers to a detection period. And the nasal pressure data in the nasal pressure detection sliding window can be understood as the nasal pressure data collected by the pressure sensor in the long time of the detection period. The specific duration of the detection period is not limited, and different values can be set according to different ages, and the detection period is generally set as the breathing period of a normal person. For example: healthy adults breathe about 16 to 18 times per minute at rest, i.e. the detection period may be 3.5 seconds. It should be noted that: the following two specific embodiments of step S101 are possible.
(1) In the nasal pressure detection sliding window, sampling nasal pressure data are acquired according to a preset sampling step length, and the nasal pressure detection sliding window slides backwards according to the sampling step length.
Wherein, the sampling step length is according to the sampling cycle of nasal pressure data, for example: if the sampling frequency of the nasal pressure data is 25Hz, the sampling period of the nasal pressure data is 0.04 seconds, and when the detection period is 3.5 seconds, the number of nasal pressure data in one detection period is 3.5 × 25, and is 88. When the sliding window for detecting the nasal pressure slides backwards, the earliest nasal pressure data in the sliding window for detecting the nasal pressure is replaced by the newly entered nasal pressure data. Because the sliding window for detecting the nasal pressure slides according to the sampling step length, the sliding window for detecting the nasal pressure slides backwards for 1 datum every time the sliding window slides. As shown in fig. 2, the sliding window for nasal pressure detection (r) includes data from a1 to a88, and slides backward by a sampling step to become the sliding window for nasal pressure detection (r) which includes data from a2 to a 89.
(2) In the nasal pressure detection sliding window, sampling nasal pressure data are acquired according to a preset sampling step length, and the nasal pressure detection sliding window slides backwards according to the length of the nasal pressure detection sliding window.
Compared with the sliding mode of sliding backwards according to the sampling step length, the sliding mode of sliding backwards according to the length of the sliding window for detecting the nasal pressure has more updated nasal pressure data, for example: when the sampling frequency is 25Hz, the sliding window of the nasal pressure detection is 3.5 seconds, and the sliding window of the nasal pressure detection slides once, 88 data can be pressed backwards, so that the nasal pressure data in the sliding window of the nasal pressure detection is changed into the next 88 data. As shown in fig. 3, the sliding window for detecting nasal pressure (c) includes 88 data a1 to a88, and slides backward once, and the sliding window for detecting nasal pressure (c) includes 88 data a89 to a 176.
It can be understood that: the step size of sliding the nasal pressure detection sliding window is not limited to the above-described step size, and may be other step sizes, and is not limited herein.
Step S102: and judging whether the characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is smaller than a preset first threshold value. If yes, go to step S103 a. If not, step S103b is executed.
The specific value of the preset first threshold is not limited, and can be determined through experiments.
Step S103 a: determining the presence of a loss of nasal pressure event.
A loss of nasal pressure event is when the user breathes particularly poorly, or not. Because the difference of the air pressure generated by expiration and inspiration is large when the human body breathes normally, in contrast, if the dispersion degree of the nasal pressure data in the nasal pressure detection sliding window is small, namely the difference of the nasal pressure data of expiration and inspiration is small, the breath of the user can be indicated to be weak, and therefore the user can be considered to have a nasal pressure loss event. In short, the characteristic values reflecting the degree of dispersion of nasal pressure data in the nasal pressure detection sliding window are: and in the nasal pressure detection sliding window, the absolute value of the difference value of the sampled maximum nasal pressure data and the sampled minimum nasal pressure data. In some embodiments, the absolute value may be understood as a range of nasal pressure data within a sliding window of nasal pressure detection, and the range of nasal pressure data is a relatively common characteristic value for evaluating the dispersion of a set of data, which may effectively reflect the fluctuation range of the set of data. Of course, the characteristic value reflecting the degree of dispersion of the nasal pressure data in the sliding window for detecting the nasal pressure is not limited to extreme differences, and may be other characteristic values reflecting the degree of dispersion, such as: such as variance and standard deviation, etc.
Step S103 b: determining the absence of a nasal pressure loss event.
Referring to fig. 4, fig. 4 is a flowchart illustrating a nasal pressure detecting method according to another embodiment of the present invention, which is different from the above embodiment in that after step S103a, the method further includes:
and step S104, determining the number of times of nasal pressure loss according to the nasal pressure loss event.
Specifically, when the event of loss of nasal pressure occurs alone, it is recorded as loss of nasal pressure once.
And when the nasal pressure loss event continuously occurs, dividing the frequency of the continuous occurrence of the nasal pressure loss event by a preset second threshold value and then rounding the frequency upwards, and determining the rounded value as the nasal pressure loss frequency.
The continuous occurrence of nasal pressure loss events is mainly caused by that the user breathes weakly for a period of time, for example: the user breathes faintly for 5 seconds. If the user continues to breathe weakly for too long, but it is still not reasonable to consider only one absence of nasal pressure, so the preset second threshold in this step is to define the maximum duration of one absence of nasal pressure to avoid this unreasonable effect. For convenience of understanding, when it is determined that the absence of nasal pressure event exists, the nasal pressure detector may be regarded as outputting 1, and when the absence of nasal pressure event does not exist, the nasal pressure detector may be regarded as outputting 0, so that each time the sliding window for nasal pressure detection slides backward, the nasal pressure detector outputs 1 or 0. As shown in fig. 5, 1 of the consecutive occurrences is 17 times, that is, the number of consecutive occurrences of the absent nasal pressure event is 17, and if the preset second threshold is 5, the result of rounding up after dividing 17 by 5 is 4, so that the consecutive occurrences of 17 absent nasal pressure events can be regarded as 4 absent nasal pressure events.
The specific value of the preset second threshold is not limited and can be determined by experiment. Referring to fig. 6, fig. 6 is a flowchart of a nasal pressure detecting method according to a third embodiment of the present invention, which is different from the above embodiments in that after step S104, the method further includes:
step S105: determining whether an apnea exists according to the number of times of nasal pressure loss.
If the user has an apnea, the user draws less oxygen than normal, thereby affecting his health and memory. The number of times of nasal pressure loss can reflect the nasal airflow of the user and the duration of the abnormal breathing of the user, so that the number of times of nasal pressure loss can be used as a basis for judging whether the user has apnea.
Specifically, determining whether an apnea exists according to the number of times of nasal pressure loss includes the following two ways.
(1) And summing all the missing nasal pressure times in the sleep period, judging whether the summed missing nasal pressure times are greater than a preset third threshold value, and if so, determining that the apnea exists.
The sleep cycle refers to the time period for which the user sleeps, for example: the time to sleep at night. The user can turn on the nasal pressure detector before sleeping, and turn off the nasal pressure detector after waking up to can acquire the nasal pressure disappearance condition during its sleep. If the user has only 1 or two nasal pressure drops during sleep, this may be a sporadic event and not enough to consider the user to have an apnea. Conversely, if the user has a large number of nasal pressure drops during sleep, the user may be considered to have an apnea. The preset third threshold value may also be determined by experiment.
(2) Counting the maximum value of all nasal pressure loss times in the sleep period, judging whether the maximum value is greater than a preset fourth threshold value, and if so, determining that apnea exists.
One of the symptoms of the apnea syndrome is that the respiratory airflow is weak during the sleeping process of the patient and the duration time exceeds 10 seconds, but the maximum value in the step can reflect the maximum time of continuous nasal pressure loss during the sleeping period of the user, and in contrast, the maximum value can be compared with a preset fourth threshold value to judge whether the user has apnea.
The specific value of the preset fourth threshold is not limited, and can be determined by experiment.
The embodiment of the invention judges the condition of nasal pressure loss of the user through the nasal pressure data discrete degree in the nasal pressure detection sliding window, and provides a basis for judging whether the user has apnea, so that the user can find out the abnormal breathing in time.
In an embodiment of the nasal pressure detecting device, as shown in fig. 7, the nasal pressure detecting device 100 includes an obtaining module 101, a determining module 102, and a first determining module 103.
The obtaining module 101 is configured to obtain nasal pressure data in the nasal pressure detection sliding window. The judging module 102 is configured to judge whether a characteristic value reflecting a nasal pressure data dispersion degree in the nasal pressure detection sliding window is smaller than a preset first threshold. A first determination module 103 for determining the presence of a loss of nasal pressure event.
In some embodiments, the obtaining module 101 is configured to obtain nasal pressure data in a sliding window of nasal pressure detection, specifically: in the nasal pressure detection sliding window, sampling nasal pressure data are acquired according to a preset sampling step length, and the nasal pressure detection sliding window slides backwards according to the sampling step length.
In other embodiments, the obtaining module 101 is configured to obtain nasal pressure data in a sliding window of nasal pressure detection, specifically: in the nasal pressure detection sliding window, sampling nasal pressure data are acquired according to a preset sampling step length, and the nasal pressure detection sliding window slides backwards according to the length of the nasal pressure detection sliding window.
In other embodiments, the characteristic value reflecting the degree of dispersion of the nasal pressure data in the nasal pressure detection sliding window is: and in the nasal pressure detection sliding window, the absolute value of the difference value of the sampled maximum nasal pressure data and the sampled minimum nasal pressure data.
Further, the nasal pressure detecting device 100 further includes a second determining module 104. A second determining module 104, configured to determine a number of times of nasal pressure loss according to the nasal pressure loss event.
In some embodiments, the second determining module 104 is configured to determine the number of nasal pressure loss events according to the nasal pressure loss events, specifically: and dividing the times of the continuous occurrence of the nasal pressure missing events by a preset second threshold value, and then rounding upwards, and determining the rounded value as the nasal pressure missing times.
Further, the nasal pressure detecting device 100 further includes a third determining module 105. A third determining module 105, configured to determine whether an apnea exists according to the number of times of nasal pressure loss.
In some embodiments, the third determination module 105 is configured to determine whether an apnea exists according to the number of times the nasal pressure loss occurs, specifically: and summing all the missing nasal pressure times in the sleep cycle, judging whether the summed missing nasal pressure times are larger than a preset third threshold value, and if so, determining that the apnea exists.
In other embodiments, the third determining module 105 is configured to determine whether an apnea exists according to the number of times of nasal pressure loss, specifically: counting the maximum value of all nasal pressure loss times in the sleep period, judging whether the maximum value is greater than a preset fourth threshold value, and if so, determining that apnea exists.
According to the embodiment of the invention, the nasal pressure data of the user are acquired through the acquisition module 101, and then the condition of nasal pressure loss of the user is judged according to the discrete degree of the nasal pressure data.
The embodiment of the application provides a non-volatile computer storage medium, wherein the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute the nasal pressure detection method in any method embodiment.
Fig. 8 is a schematic diagram of an internal structure of an embodiment of the nasal pressure detector of the present invention, and the specific implementation of the nasal pressure detector is not limited by the embodiment of the present invention.
As shown in fig. 8, the nasal pressure detector may include: a processor (processor)902, a communication Interface (Communications Interface)904, a memory (memory)906, a communication bus 908, and a nasal pressure acquisition device 903.
Wherein:
the processor 902, communication interface 904, and memory 906 communicate with one another via a communication bus 908.
A communication interface 904 for communicating with network elements of other devices, such as clients or other servers.
And the nasal pressure acquisition device 903 is connected with the communication interface 904 and is used for acquiring nasal pressure data of the user and sending the acquired nasal pressure data to the processor 902 through the communication interface 904.
The processor 902 is configured to execute the procedure 910, and may specifically execute the relevant steps in the above-described embodiment of the nasal pressure detection method.
In particular, the program 910 may include program code that includes computer operating instructions.
The processor 902 may be a central processing unit CPU, or an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement an embodiment of the invention. The computing device includes one or more processors, which may be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
A memory 906 for storing a program 910. The memory 906 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 910 may specifically be configured to cause the processor 902 to perform the following operations:
acquiring nasal pressure data in a nasal pressure detection sliding window;
judging whether a characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is smaller than a preset first threshold value or not;
if so, a loss of nasal pressure event is determined to be present.
In an alternative manner, the program 910 may specifically be further configured to cause the processor 902 to perform the following operations:
in the nasal pressure detection sliding window, sampling nasal pressure data are acquired according to a preset sampling step length, and the nasal pressure detection sliding window slides backwards according to the sampling step length.
In an alternative manner, the program 910 may specifically be further configured to cause the processor 902 to perform the following operations:
in the nasal pressure detection sliding window, sampling nasal pressure data are acquired according to a preset sampling step length, and the nasal pressure detection sliding window slides backwards according to the length of the nasal pressure detection sliding window.
In an alternative manner, the program 910 may specifically be further configured to cause the processor 902 to perform the following operations:
determining a number of nasal pressure deficits based on the nasal pressure loss event.
In an alternative manner, the program 910 may specifically be further configured to cause the processor 902 to perform the following operations:
and dividing the times of the continuous occurrence of the nasal pressure missing events by a preset second threshold value, and then rounding upwards, and determining the rounded value as the nasal pressure missing times.
In an alternative manner, the program 910 may specifically be further configured to cause the processor 902 to perform the following operations:
determining whether an apnea exists according to the number of times of nasal pressure loss.
In an alternative manner, the program 910 may specifically be further configured to cause the processor 902 to perform the following operations:
and summing all the missing nasal pressure times in the sleep period, judging whether the summed missing nasal pressure times are greater than a preset third threshold value, and if so, determining that the apnea exists.
In an alternative manner, the program 910 may specifically be further configured to cause the processor 902 to perform the following operations:
counting the maximum value of all nasal pressure loss times in the sleep period, judging whether the maximum value is greater than a preset fourth threshold value, and if so, determining that apnea exists.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose preferred embodiments of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in a nasal pressure detection device according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Claims (4)
1. The nasal pressure detection device is characterized in that the nasal pressure detection device collects nasal pressure data of a user during sleep through a pressure sensor, and analyzes the collected nasal pressure data to judge whether the nasal pressure of the user is normal; the method comprises the following steps:
the acquisition module is used for acquiring nasal pressure data in the nasal pressure detection sliding window; in the nasal pressure detection sliding window, acquiring nasal pressure data according to a preset sampling step length, and sliding the nasal pressure detection sliding window backwards according to the length of the nasal pressure detection sliding window;
the judging module is used for judging whether a characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is smaller than a preset first threshold value or not; the characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is as follows: in the nasal pressure detection sliding window, the absolute value of the difference value of the sampled maximum nasal pressure data and the sampled minimum nasal pressure data;
a first determination module to determine that a loss of nasal pressure event exists;
further, the first determining module is further configured to:
dividing the frequency of the continuous occurrence of the nasal pressure loss events by a preset second threshold value, and then rounding upwards, and determining the rounded value as the nasal pressure loss frequency;
and summing all the missing nasal pressure times in the sleep period, judging whether the summed missing nasal pressure times are greater than a preset third threshold value, and if so, determining that the apnea exists.
2. The nasal pressure detector is characterized by comprising a nasal pressure acquisition device, a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface are communicated with each other through the communication bus; the nasal pressure acquisition device acquires nasal pressure data of a user during sleep through the pressure sensor, and analyzes the acquired nasal pressure data to judge whether the nasal pressure of the user is normal;
the nasal pressure acquisition device is used for acquiring nasal pressure data and sending the acquired nasal pressure data to the processor;
the memory is configured to store at least one executable instruction that causes the processor to:
acquiring nasal pressure data in a nasal pressure detection sliding window; in the nasal pressure detection sliding window, acquiring nasal pressure data according to a preset sampling step length, and sliding the nasal pressure detection sliding window backwards according to the length of the nasal pressure detection sliding window;
judging whether a characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is smaller than a preset first threshold value or not; the characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is as follows: in the nasal pressure detection sliding window, the absolute value of the difference value of the sampled maximum nasal pressure data and the sampled minimum nasal pressure data;
if so, determining that a loss of nasal pressure event exists;
dividing the frequency of the continuous occurrence of the nasal pressure missing events by a preset second threshold value, and then rounding upwards, and determining the rounded value as the nasal pressure missing frequency;
and summing all the missing nasal pressure times in the sleep period, judging whether the summed missing nasal pressure times are greater than a preset third threshold value, and if so, determining that the apnea exists.
3. The nasal pressure detector of claim 2, wherein the executable instructions cause the processor to:
counting the maximum value of all nasal pressure loss times in the sleep period, judging whether the maximum value is greater than a preset fourth threshold value, and if so, determining that apnea exists.
4. A computer storage medium having stored therein at least one executable instruction that causes a processor to:
acquiring nasal pressure data in a nasal pressure detection sliding window; in the nasal pressure detection sliding window, acquiring nasal pressure data according to a preset sampling step length, and sliding the nasal pressure detection sliding window backwards according to the length of the nasal pressure detection sliding window;
judging whether a characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is smaller than a preset first threshold value or not; the characteristic value reflecting the nasal pressure data discrete degree in the nasal pressure detection sliding window is as follows: in the nasal pressure detection sliding window, the absolute value of the difference value between the sampled maximum nasal pressure data and the sampled minimum nasal pressure data;
if so, determining that a loss of nasal pressure event exists;
dividing the frequency of the continuous occurrence of the nasal pressure missing events by a preset second threshold value, and then rounding upwards, and determining the rounded value as the nasal pressure missing frequency;
and summing all the missing nasal pressure times in the sleep cycle, judging whether the summed missing nasal pressure times are larger than a preset third threshold value, and if so, determining that the apnea exists.
Priority Applications (1)
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| US9950112B2 (en) * | 2010-08-17 | 2018-04-24 | University Of Florida Research Foundation, Incorporated | Intelligent drug and/or fluid delivery system to optimizing medical treatment or therapy using pharmacodynamic and/or pharamacokinetic data |
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| US20160296165A1 (en) * | 2015-04-10 | 2016-10-13 | Dymedix Corporation | Screening system for assessing sleep abnormalities |
| WO2017185128A1 (en) * | 2016-04-26 | 2017-11-02 | Resmed Limited | Diagnosis and monitoring of respiratory disorders |
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| CN104545888A (en) * | 2014-12-27 | 2015-04-29 | 迪姆软件(北京)有限公司 | Sleep apnea collecting and analyzing system based on dynamic electrocardiogram and respiratory wave collection |
| CN104688239A (en) * | 2015-03-26 | 2015-06-10 | 北京怡和嘉业医疗科技有限公司 | Method and system for determining categories of sleep-related breathing events |
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