CN111657948A - Method, device and equipment for detecting sleep breathing state - Google Patents

Method, device and equipment for detecting sleep breathing state Download PDF

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CN111657948A
CN111657948A CN202010447273.6A CN202010447273A CN111657948A CN 111657948 A CN111657948 A CN 111657948A CN 202010447273 A CN202010447273 A CN 202010447273A CN 111657948 A CN111657948 A CN 111657948A
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sleep breathing
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CN111657948B (en
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罗强
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Shenzhen Vvfly Electronics Co ltd
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    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B5/0826—Detecting or evaluating apnoea events
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    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3601—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation of respiratory organs
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00—Electrotherapy; Circuits therefor
    • A61N1/18—Applying electric currents by contact electrodes
    • A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/36014—External stimulators, e.g. with patch electrodes

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Abstract

The application is suitable for the technical field of medical treatment, and provides a sleep breathing state detection method, which comprises the following steps: monitoring a laryngeal vibration signal of a subject to be detected; determining a respiratory motion trajectory curve according to the laryngeal vibration signal; and determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule. According to the scheme, the sleep breathing state of the object to be detected can be determined by monitoring the vibration data of the upper respiratory airway and the throat of the human body during sleep, so that the obstructive sleep apnea and hypopnea syndrome OSAHS respiratory events can be detected in real time. The medical cost of detection is lower, is applicable to the detection at home, and the interference factor has been reduced to the detection in-process under the normal sleep state of the object of waiting to detect.

Description

Method, device and equipment for detecting sleep breathing state
Technical Field
The application belongs to the technical field of medical treatment, and particularly relates to a sleep breathing state detection method, device and equipment.
Background
With the increasing pace of modern life and work, dietary changes and natural age, Obstructive Sleep Apnea and Hypopnea Syndrome (OSAHS) is increasingly common in the adult population. Whether OSAHS exists can be detected by detecting the sleep breathing state, the traditional detection method of the OSAHS is to carry out Polysomnography (PSG) detection in a specific laboratory or a sleep medical center of a hospital, but the PSG needs professional medical personnel to operate, a plurality of interference factors exist when an object to be detected is in an unfamiliar sleep environment, the detection medical cost is high, and the universality of the popular use is low. .
Disclosure of Invention
The embodiment of the application provides a method, a device and equipment for detecting a sleep breathing state, and can solve the problems that the medical cost is high and the universality of mass use is low.
In a first aspect, an embodiment of the present application provides a method for detecting a sleep breathing state, including:
monitoring a laryngeal vibration signal of a subject to be detected;
determining a respiratory motion trajectory curve according to the laryngeal vibration signal;
and determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule.
Further, the determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule includes:
acquiring sound wave data of the object to be detected, and determining a snore event identifier according to the sound wave data;
if the fluctuation range of the breathing motion trajectory curve is smaller than a first threshold and larger than a second threshold within a preset time period, and the snore event mark is a target mark, determining that the sleep breathing state of the object to be detected is a first state, wherein the first state represents that an obstructive sleep breathing hypopnea event occurs.
Further, the determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule includes:
and if the fluctuation amplitude of the breathing motion trajectory curve is smaller than a second threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a second state, wherein the second state represents an obstructive sleep apnea event.
Further, the determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule includes:
and if the fluctuation amplitude of the breathing motion trajectory curve is larger than a first threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a third state, wherein the third state indicates that no obstructive sleep apnea or low ventilation event occurs.
Further, the determining a respiratory motion trajectory curve according to the laryngeal vibration signal includes:
filtering the throat vibration signal to obtain a target throat vibration signal;
and generating a respiratory motion trajectory curve according to the target laryngeal vibration signal.
Further, the laryngeal vibration signal comprises a Z-axis laryngeal vibration signal acquired by a three-axis acceleration sensor.
Further, still include:
and controlling the electrical stimulation module to perform electrical stimulation operation.
In a second aspect, an embodiment of the present application provides a device for detecting a sleep breathing state, including:
the monitoring unit is used for monitoring a throat vibration signal of the object to be detected;
the first determination unit is used for determining a respiratory motion trajectory curve according to the laryngeal vibration signal;
and the second determination unit is used for determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule.
Further, the second determining unit is specifically configured to:
acquiring sound wave data of the object to be detected, and determining a snore event identifier according to the sound wave data;
if the fluctuation range of the breathing motion trajectory curve is smaller than a first threshold and larger than a second threshold within a preset time period, and the snore event mark is a target mark, determining that the sleep breathing state of the object to be detected is a first state, wherein the first state represents that an obstructive sleep breathing hypopnea event occurs.
Further, the second determining unit is specifically configured to:
and if the fluctuation amplitude of the breathing motion trajectory curve is smaller than a second threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a second state, wherein the second state represents that an obstructive sleep apnea event occurs.
Further, the second determining unit is specifically configured to:
and if the fluctuation amplitude of the breathing motion trajectory curve is larger than a first threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a third state, wherein the third state indicates that no obstructive sleep apnea or low ventilation event occurs.
Further, the first determining unit is specifically configured to:
filtering the throat vibration signal to obtain a target throat vibration signal;
and generating a respiratory motion trajectory curve according to the target laryngeal vibration signal.
Further, the laryngeal vibration signal comprises a Z-axis laryngeal vibration signal acquired by a three-axis acceleration sensor.
Further, the detection apparatus for the sleep breathing state further includes:
and the control unit is used for controlling the electrical stimulation module to execute electrical stimulation operation.
In a third aspect, the present application provides a device for detecting a sleep breathing state, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method for detecting a sleep breathing state according to the first aspect when executing the computer program.
In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program, where the computer program is executed by a processor to implement the method for detecting a sleep breathing state according to the first aspect.
In the embodiment of the application, the throat vibration signal of a subject to be detected is monitored; determining a respiratory motion trajectory curve according to the laryngeal vibration signal; and determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule. According to the scheme, the sleep breathing state of the object to be detected can be determined by monitoring the vibration data of the upper respiratory airway and the throat of the human body during sleep, so that the OSAHS respiratory event can be detected in real time. The medical cost of detection is lower, is applicable to the detection at home, has promoted the universality that masses used to the detection in-process is under the normal sleep state of the object of waiting to detect, has reduced interference factor.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a method for detecting a sleep breathing state according to a first embodiment of the present application;
fig. 2 is a schematic flowchart of a refinement of S102 in a method for detecting a sleep breathing state according to a first embodiment of the present application;
fig. 3 is a schematic flowchart of a refinement of S103 in a method for detecting a sleep breathing state according to a first embodiment of the present application;
fig. 4 is a schematic flowchart of a method for detecting a sleep breathing state according to a first embodiment of the present application;
FIG. 5 is a schematic diagram of a device for detecting sleep breathing state according to a second embodiment of the present application;
fig. 6 is a schematic diagram of a sleep breathing state detection device according to a third embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
Referring to fig. 1, fig. 1 is a schematic flowchart of a method for detecting a sleep breathing state according to a first embodiment of the present application. An execution subject of the method for detecting a sleep breathing state in the present embodiment is a device having a function of detecting a sleep breathing state. The method for detecting the sleep breathing state as shown in fig. 1 may include:
s101: and monitoring the laryngeal vibration signal of the throat of the subject to be detected.
Obstructive Sleep Apnea and Hypopnea Syndrome (OSAHS) is a condition in which the upper respiratory airway repeatedly becomes blocked during Sleep, resulting in hypopnea and Apnea, often accompanied by hypoxia, decreased blood oxygen saturation, increased heart rate, snoring, and daytime sleepiness. Therefore, it is possible to detect whether OSAHS occurs by monitoring the sleep breathing state.
In this embodiment, the device with the detection function of the sleep breathing state comprises a data acquisition module, wherein the data acquisition module comprises an acceleration sensor, and the acceleration sensor is used for acquiring a throat vibration signal of a subject to be detected. The acceleration sensor can be positioned on a fixing piece connected with the equipment, and the fixing piece is stuck to the inner side of the mandibular angle of the neck or the superficial part of the hypoglossal nerve when in use. The fastener can be the paster electrode, and the paster electrode can be connected with equipment through the magnetism electrode button during the use.
The equipment can detect the throat vibration signal of the object to be detected through the data acquisition module, and the throat vibration signal of the object to be detected is the muscle tissue vibration signal at the upper airway throat of the object to be detected.
S102: and determining a respiratory motion trajectory curve according to the laryngeal vibration signal.
The device determines a respiratory motion trajectory curve from the laryngeal vibration signal. The breathing motion trajectory curve marks the change condition of the breathing state of the object to be detected in the sleeping state. The equipment can process the throat vibration signal to obtain a respiratory motion trajectory curve.
Further, in order to accurately acquire the breathing motion trajectory curve and thus detect the sleep breathing state of the object to be detected, S102 may include S1021 to S1022, as shown in fig. 2, where S1021 to S1022 specifically include:
s1021: and filtering the throat vibration signal to obtain a target throat vibration signal.
And the equipment carries out filtering processing on the throat vibration signal to obtain a target throat vibration signal. The process of treatment may be:
firstly, a moving average smoothing process of 100 data points is carried out on the throat vibration signal Z (t), and the moving average formula is as follows:
F(t)＝Z’t＝(Zt-1+Zt-2+Zt-3+…+Zt-n)/n
wherein Z istIs a laryngeal vibration signal of the throat at time t, Z'tThe time t after the moving average is the throat vibration signal, n is 100, and the time series data f (t) is obtained after the moving average smoothing processing.
Secondly, performing first-order difference on the time sequence data F (t) obtained after the moving average smoothing processing, wherein the first-order difference formula is as follows:
D(t)＝ΔFt＝Ft+1-Ft
in the formula,. DELTA.FtAnd obtaining time series data D (t) after the first difference for the laryngeal vibration signal at the time t after the first difference.
Finally, the time series data d (t) is smoothed again by the moving average of 100 data points, and the formula is as follows:
R(t)＝D’t＝(Dt-1+Dt-2+Dt-3+…+Dt-n)/n
wherein, r (t) is the target laryngeal vibration signal, and n is 100.
Further, the laryngeal vibration signal comprises a Z-axis laryngeal vibration signal acquired by a three-axis acceleration sensor. In this embodiment, the throat vibration signal can be collected by the triaxial acceleration sensor, the triaxial acceleration sensor can collect the X-axis throat vibration signal, the Y-axis throat vibration signal and the Z-axis throat vibration signal, and the sampling rate can be set to 200 Hz. The device determines a target laryngeal vibration signal primarily from the Z-axis laryngeal vibration signal.
S1022: and generating a respiratory motion trajectory curve according to the target laryngeal vibration signal.
The equipment generates a respiratory motion trajectory curve according to the target laryngeal vibration signal, acquires a oscillogram of the target laryngeal vibration signal, and takes the waveform of the target laryngeal vibration signal as the respiratory motion trajectory curve.
S103: and determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule.
The device is preset with a detection rule, the preset detection rule is used for determining the sleep breathing state of the object to be detected according to the breathing motion trajectory curve, and the sleep breathing state is used for identifying whether OSAHS occurs currently. The preset detection rule may include a condition that OSAHS occurs and a condition that OSAHS does not occur. If the breathing motion trajectory curve meets the condition of OSAHS generation, determining that the sleep breathing state identifier of the object to be detected generates OSAHS; and if the breathing motion trajectory curve meets the condition that the OSAHS does not occur, determining that the sleep breathing state identifier of the object to be detected does not occur the OSAHS.
Further, in order to accurately determine the sleep respiration state, S103 may include S1031 to S1032, as shown in fig. 3, where S1031 to S1032 are specifically as follows:
s1031: and acquiring sound wave data of the object to be detected, and determining the snore event identification according to the sound wave data.
The equipment acquires sound wave data of an object to be detected, and a snore event identifier is determined according to the sound wave data, wherein the snore event identifier can identify whether a snore event occurs. In one embodiment, the device may perform high-pass filtering processing on the acoustic data of the object to be detected to extract snore event information, determine a snore event identifier based on the snore event information, and the cut-off frequency of the high-pass filtering may be 30 Hz; in another embodiment, the device may determine and process sound wave data of the object to be detected based on a pre-trained snore machine learning model, so as to obtain the snore event identifier.
S1032: if the fluctuation range of the breathing motion trajectory curve is smaller than a first threshold and larger than a second threshold within a preset time period, and the snore event mark is a target mark, determining that the sleep breathing state of the object to be detected is a first state, wherein the first state represents that an obstructive sleep breathing hypopnea event occurs.
In this embodiment, a condition corresponding to the fluctuation range of the breathing motion trajectory curve within a preset time period is set in a preset detection rule. The device firstly obtains the fluctuation range of the breathing motion track curve in a preset time period, wherein the fluctuation range of the breathing motion track curve can be represented by the device through the area of the enclosed area of the breathing motion track curve and a zero axis in the preset time period. The calculation process of the area size of the enclosing region in the preset time period comprises the following steps: calculating the area A (x) of the enclosed area of the breathing motion trajectory curve R (t) and the zero axis in the preset time period by approximate summation, wherein when the preset time period is 5 seconds, the summation formula is as follows:
Figure BDA0002506346830000091
where N is the data length of the breathing trajectory curve r (t), and Δ t is constantly equal to 1.
A first threshold and a second threshold are prestored in the device, and are used for measuring the fluctuation amplitude of the breathing motion track curve within a preset time period. The first threshold and the second threshold may be preset by the device, or may be updated in real time.
The equipment can set a reference fluctuation amplitude, wherein the reference fluctuation amplitude is a breathing motion track curve in a normal breathing state, and the normal breathing state is a state without OSAHS and other interference factors. A first coefficient and a second coefficient are preset in the device, the device determines a first threshold value based on the first coefficient and a reference fluctuation width, and the device determines a second threshold value based on the second coefficient and the reference fluctuation width. For example, the first coefficient is 0.4, the second coefficient is 0.1, the apparatus multiplies the first coefficient 0.4 by the reference fluctuation width to determine the first threshold, and the apparatus determines the second threshold based on the multiplication of the second coefficient 0.1 by the reference fluctuation width.
The equipment can also adjust the reference fluctuation amplitude in real time according to the state of the object to be detected, namely the reference fluctuation amplitude is dynamic, so that the first threshold value and the second threshold value can be updated in real time according to the reference fluctuation amplitude. The setting rule of the dynamic reference fluctuation range can be as follows: firstly, the respiratory motion data is initialized and set after the equipment is started, the equipment acquires the mean value of the fluctuation amplitudes of three continuous preset time periods as the reference fluctuation amplitude, the fluctuation amplitudes of the three continuous preset time periods have to meet the condition that the fluctuation amplitude difference is within 10%, and the initial reference fluctuation amplitude is set. If the fluctuation amplitudes of the breathing motion trajectory curves in the three continuous preset time periods all rise back to more than 90% of the initial reference fluctuation amplitude, and the fluctuation amplitude difference in the three continuous preset time periods is within 10%, the average value of the three continuous fluctuation amplitudes is used as a new reference fluctuation amplitude, otherwise, the reference fluctuation amplitude is not updated and set. And after each OSAHS respiratory event occurs and is finished, the reference fluctuation range is updated in real time, and the setting of the dynamic reference fluctuation range is realized. And multiplying the dynamic reference fluctuation amplitude by the first coefficient and the second coefficient to respectively serve as a dynamic first threshold value and a dynamic second threshold value.
If the fluctuation range of the breathing motion trajectory curve is smaller than a first threshold and larger than a second threshold within a preset time period, and the snore event mark is a target mark, the sleep breathing state of the object to be detected is judged to be a first state, and the first state represents an obstructive sleep breathing hypoventilation event. Wherein the target identification indicates the occurrence of a snoring event.
Further, S103 may include S1033, where S1033 is specifically as follows:
s1033: and if the fluctuation amplitude of the breathing motion trajectory curve is smaller than a second threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a second state, wherein the second state represents that an obstructive sleep apnea event occurs.
In this embodiment, if the fluctuation amplitude of the breathing motion trajectory curve is smaller than the second threshold within the preset time period, it is determined that the sleep breathing state of the object to be detected is the second state, where the second state indicates that an obstructive sleep apnea event occurs. The relevant details in this embodiment may refer to the relevant description in S1032, and are not described herein again.
Further, S103 may include S1034, where S1034 is specifically as follows:
s1034: and if the fluctuation amplitude of the breathing motion trajectory curve is larger than a first threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a third state, wherein the third state indicates that no obstructive sleep apnea or low ventilation event occurs.
In this embodiment, if the fluctuation amplitude of the breathing motion trajectory curve is greater than the first threshold within the preset time period, it is determined that the sleep breathing state of the object to be detected is the third state, where the third state indicates that no obstructive sleep apnea or hypopnea event occurs. The relevant details in this embodiment may refer to the relevant description in S1032, and are not described herein again.
As shown in fig. 4, S1031 to S1032, S1033, and S1034 are relations of alternative execution, which are included in S103 of the present embodiment.
Further, after determining that the sleep breathing state of the object to be detected is the first state and the second state, the method further comprises the following steps: and controlling the electrical stimulation module to perform electrical stimulation operation. The equipment judges that the sleep breathing state of the object to be detected is a first state and a second state, and the equipment can send a control signal to the electrical stimulation module and control the electrical stimulation module to execute electrical stimulation operation. The electrical stimulation operation is forward and reverse pulse voltage stimulation, the stimulation frequency is 53Hz, the pulse width is 60 microseconds, the voltage level is 20-32V, the stimulation time is 4 seconds each time, and before a user uses the device, the self tolerance voltage can be measured firstly, and the maximum stimulation voltage level is preset. If the sleep respiration state of the object to be detected is still the first state or the second state after one submaxillary percutaneous electrical stimulation is finished and is not obviously improved, the electrical stimulation module can be automatically started and continues to execute the electrical stimulation operation at a higher voltage level until the sleep respiration state of the object to be detected is changed into the third state, namely the OSAHS respiratory event is terminated, and the voltage level for terminating the OSAHS respiratory event is automatically constant to be the voltage level for subsequent electrical stimulation.
The electrical stimulation module can control the patch electrode to perform electrical stimulation operation. The whole shape of the patch electrode can be designed according to the shape of cashew, so as to be beneficial to being tightly attached to the submaxillary neck of a human body, the two disc electrodes are symmetrically distributed on the left side and the right side of the adhesive surface of the medical adhesive tape, and the back surface of the disc electrode (namely the adhesive surface of the medical adhesive tape) is provided with a magnetic electrode button. The specific position of the patch electrode stuck under the neck jaw is as follows: the medial aspect of the angle of the mandible is about (1 + -0.011) cm, the mean extramental (0.3 + -0.022) cm, and the vertical distance from the mandibular border (1.5 + -0.023) cm.
In the embodiment of the application, the throat vibration signal of a subject to be detected is monitored; determining a respiratory motion trajectory curve according to the laryngeal vibration signal; and determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule. According to the scheme, the sleep breathing state of the object to be detected can be determined by monitoring the vibration data of the upper respiratory airway and the throat of the human body during sleep, so that the OSAHS respiratory event can be detected in real time. The medical cost of detection is lower, is applicable to the detection at home to the detection in-process is under the normal sleep state of the object to be detected, does not have other interference factor, has promoted the testing result accuracy.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Referring to fig. 5, fig. 5 is a schematic diagram of a device for detecting a sleep breathing state according to a second embodiment of the present application. The units included are used to perform the steps in the embodiments corresponding to fig. 1-4. Please refer to the related description of the embodiments in fig. 1 to 5. For convenience of explanation, only the portions related to the present embodiment are shown. Referring to fig. 5, the detection apparatus 5 of the sleep breathing state includes:
a monitoring unit 510 for monitoring a laryngeal vibration signal of a subject to be detected;
a first determining unit 520, configured to determine a respiratory motion trajectory curve according to the laryngeal vibration signal;
a second determining unit 530, configured to determine a sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule.
Further, the second determining unit 530 is specifically configured to:
acquiring sound wave data of the object to be detected, and determining a snore event identifier according to the sound wave data;
if the fluctuation range of the breathing motion trajectory curve is smaller than a first threshold and larger than a second threshold within a preset time period, and the snore event mark is a target mark, determining that the sleep breathing state of the object to be detected is a first state, wherein the first state represents that an obstructive sleep breathing hypopnea event occurs.
Further, the second determining unit 530 is specifically configured to:
and if the fluctuation amplitude of the breathing motion trajectory curve is smaller than a second threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a second state, wherein the second state represents that an obstructive sleep apnea event occurs.
Further, the second determining unit 530 is specifically configured to:
and if the fluctuation amplitude of the breathing motion trajectory curve is larger than a first threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a third state, wherein the third state indicates that no obstructive sleep apnea or low ventilation event occurs.
Further, the second determining unit 520 is specifically configured to:
filtering the throat vibration signal to obtain a target throat vibration signal;
and generating a respiratory motion trajectory curve according to the target laryngeal vibration signal.
Further, the laryngeal vibration signal comprises a Z-axis laryngeal vibration signal acquired by a three-axis acceleration sensor.
Further, the sleep breathing state detection device 5 further includes:
and the control unit is used for controlling the electrical stimulation module to execute electrical stimulation operation.
Fig. 6 is a schematic diagram of a sleep breathing state detection device according to a third embodiment of the present application. As shown in fig. 6, the detection apparatus 6 of the sleep breathing state of the embodiment includes: a processor 60, a memory 61 and a computer program 62, such as a detection program of a sleep breathing state, stored in said memory 61 and executable on said processor 60. The processor 60, when executing the computer program 62, implements the steps in the above-described embodiments of the method for detecting sleep breathing states, such as the steps 101 to 103 shown in fig. 1. Alternatively, the processor 60, when executing the computer program 62, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the modules 510 to 530 shown in fig. 5.
Illustratively, the computer program 62 may be partitioned into one or more modules/units that are stored in the memory 61 and executed by the processor 60 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 62 in the detection device 6 of the sleep breathing state. For example, the computer program 62 may be divided into a monitoring unit, a first determining unit, and a second determining unit, and each unit has the following specific functions:
the monitoring unit is used for monitoring a throat vibration signal of the object to be detected;
the first determination unit is used for determining a respiratory motion trajectory curve according to the laryngeal vibration signal;
and the second determination unit is used for determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule.
The sleep breathing state detection device may include, but is not limited to, a processor 60 and a memory 61. It will be appreciated by those skilled in the art that fig. 6 is merely an example of the detection device 6 of the sleep breathing state, does not constitute a limitation of the detection device 6 of the sleep breathing state, and may comprise more or less components than those shown, or some components in combination, or different components, for example, the detection device of the sleep breathing state may further comprise an input-output device, a network access device, a bus, etc.
The Processor 60 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 61 may be an internal storage unit of the sleep breathing state detection device 6, such as a hard disk or a memory of the sleep breathing state detection device 6. The memory 61 may also be an external storage device of the sleep breathing state detection device 6, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are equipped on the sleep breathing state detection device 6. Further, the detection device 6 of the sleep breathing state may also comprise both an internal memory unit and an external memory device of the detection device 6 of the sleep breathing state. The memory 61 is used for storing the computer program and other programs and data required by the detection device of the sleep breathing state. The memory 61 may also be used to temporarily store data that has been output or is to be output.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
An embodiment of the present application further provides a network device, where the network device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, the processor implementing the steps of any of the various method embodiments described above when executing the computer program.
The embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps in the above-mentioned method embodiments.
The embodiments of the present application provide a computer program product, which when running on a mobile terminal, enables the mobile terminal to implement the steps in the above method embodiments when executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), random-access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims (10)

1. A method for detecting a sleep breathing state, comprising:
monitoring a laryngeal vibration signal of a subject to be detected;
determining a respiratory motion trajectory curve according to the laryngeal vibration signal;
and determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule.
2. The method for detecting the sleep breathing state according to claim 1, wherein the determining the sleep breathing state of the subject to be detected based on the breathing motion trajectory curve and a preset detection rule comprises:
acquiring sound wave data of the object to be detected, and determining a snore event identifier according to the sound wave data;
if the fluctuation range of the breathing motion trajectory curve is smaller than a first threshold and larger than a second threshold within a preset time period, and the snore event mark is a target mark, determining that the sleep breathing state of the object to be detected is a first state, wherein the first state represents that an obstructive sleep breathing hypopnea event occurs.
3. The method for detecting the sleep breathing state according to claim 1, wherein the determining the sleep breathing state of the subject to be detected based on the breathing motion trajectory curve and a preset detection rule comprises:
and if the fluctuation amplitude of the breathing motion trajectory curve is smaller than a second threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a second state, wherein the second state represents that an obstructive sleep apnea event occurs.
4. The method for detecting the sleep breathing state according to claim 1, wherein the determining the sleep breathing state of the subject to be detected based on the breathing motion trajectory curve and a preset detection rule comprises:
and if the fluctuation amplitude of the breathing motion trajectory curve is larger than a first threshold value within a preset time period, judging that the sleep breathing state of the object to be detected is a third state, wherein the third state indicates that no obstructive sleep apnea or low ventilation event occurs.
5. The method for detecting sleep breathing state according to claim 1, wherein said determining a breathing trajectory curve from said laryngeal vibration signal comprises:
filtering the throat vibration signal to obtain a target throat vibration signal;
and generating a respiratory motion trajectory curve according to the target laryngeal vibration signal.
6. The method of detecting sleep breathing states of claim 5 wherein the laryngeal vibration signal includes a Z-axis laryngeal vibration signal acquired by a three-axis acceleration sensor.
7. The method of detecting a sleep breathing state of any of claims 2 or 3, further comprising:
and controlling the electrical stimulation module to perform electrical stimulation operation.
8. A sleep breathing state detection apparatus, comprising:
the monitoring unit is used for monitoring a throat vibration signal of the object to be detected;
the first determination unit is used for determining a respiratory motion trajectory curve according to the laryngeal vibration signal;
and the second determination unit is used for determining the sleep breathing state of the object to be detected based on the breathing motion trajectory curve and a preset detection rule.
9. A device for detecting a sleep breathing state, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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