Method and system for intelligent identification of breathing based on low-frequency therapeutic apparatus

Abstract

The invention discloses a low-frequency therapeutic instrument-based intelligent identification method and system for calling, and relates to the technical field of calling identification. Comprising S1, a first threshold value; s2, a second threshold value; s3, a third threshold value; and S4, comprehensively judging. According to the medical phenomenon that when the sleep apnea obstructive hypopnea syndrome occurs, the blood oxygen saturation decline change of a human body occurs, the increase of the blood oxygen saturation decline change serves as an identification condition for triggering low-frequency stimulation by equipment for auxiliary treatment of the disease; in combination with microphone snore data collection and local body movement vibration data collection, whether the human body needs low-frequency stimulation adjuvant therapy or not is comprehensively judged.

Description

Technical Field

[0001] The present invention relates to the technical field of snoring recognition, and in particular to a method and system for intelligent snoring recognition based on a low-frequency therapeutic device. Background Art

[0002] When sleep apnea-obstructive hypopnea syndrome occurs, snoring will occur, and the body's blood oxygen level will decrease to a certain extent.

[0003] Currently, low-frequency therapeutic devices that assist in the treatment of this disease generally use a microphone to collect snoring sounds during snoring, perform sound feature analysis to identify whether it is snoring, or use body motion sensors to sense the vibration characteristics of human tissues such as the chin during snoring, and conduct comprehensive analysis to intelligently identify whether snoring sounds occur. The low-frequency therapeutic device remains in standby mode or starts low-frequency treatment to stimulate the throat muscle groups to maintain tension, open blocked airways, and restore normal breathing.

[0004] The defects of the existing technology are that due to the large differences in snoring volume and frequency between individuals, the large differences in snoring vibration levels, and the various noises or abnormal movements that may occur in the environment, it is impossible to accurately determine whether the patient is snoring only through sound and body movement, which can easily trigger the low-frequency therapeutic device for ineffective or excessive pulse treatment; it may also fail to identify and not treat, thus prolonging the efficacy of the treatment. Both of these will cause patients to question and affect their acceptance of treatment, which will not be conducive to patients getting treatment and alleviating their symptoms as soon as possible. Optimizing the intelligent recognition model requires the collection and establishment of a large number of databases, which undoubtedly increases the difficulty and investment in research and development for enterprises, and also only reduces the possibility of false triggering or non-triggering.

[0005] Therefore, it is an urgent problem for those skilled in the art to propose a method and system for intelligent snoring recognition based on a low-frequency therapeutic device to solve the difficulties existing in the prior art. Summary of the invention

[0006] In view of this, the present invention provides a method and system for intelligent snoring recognition based on a low-frequency therapeutic device, which meets the accuracy requirements of auxiliary treatment, ensures the treatment effect without affecting normal sleep, effectively reduces the treatment cost, and also helps patients relieve their symptoms as soon as possible.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] A method for intelligent snoring recognition based on a low-frequency therapeutic device comprises the following steps:

[0009] S1. First threshold: Collect the blood oxygen saturation drop change data, and send the blood oxygen saturation drop change data to the low-frequency therapeutic device as the first threshold to trigger low-frequency stimulation;

[0010] S2. Second threshold: collecting snoring data based on the sound sensor, and sending the snoring data to the low-frequency therapeutic device as the second threshold for triggering low-frequency stimulation;

[0011] S3. The third threshold: collecting vibration data of local body movement based on the vibration sensor, and sending the vibration data to the low-frequency therapeutic device as the third threshold for triggering low-frequency stimulation;

[0012] S4. Comprehensive judgment: Based on S1-S3, it is determined whether the human body needs auxiliary treatment with low-frequency stimulation.

[0013] In the above method, optionally, in S1, a blood oxygen sensor is used to collect blood oxygen saturation data values, thereby obtaining blood oxygen saturation decrease change data. The low-frequency therapeutic device and the blood oxygen sensor are connected in real time. When the blood oxygen saturation drops to a preset value, the low-frequency therapeutic device triggers pulse therapy through an intervention module.

[0014] In the above method, optionally, the real-time connection between the low-frequency therapeutic device and the blood oxygen sensor includes one or more of Bluetooth, 4G, wireless network, and cable connection.

[0015] In the above method, optionally, in S2, snoring data is collected based on a microphone in the low-frequency therapeutic device as a second threshold for triggering low-frequency stimulation.

[0016] In the above method, optionally, in S3, vibration data of local body movement is collected based on a vibration sensor in the low-frequency therapeutic device as a third threshold for triggering low-frequency stimulation.

[0017] In the above method, optionally, the specific content of S4 comprehensively judging whether the human body should undergo auxiliary treatment with low-frequency stimulation according to S1-S3 is:

[0018] When the low-frequency therapeutic device simultaneously receives data indicating that the blood oxygen saturation decreases to a preset value, the microphone detects snoring data, and the vibration sensor collects local body movement vibration data, the low-frequency therapeutic device emits a pulse current to stimulate the throat muscles for auxiliary treatment; otherwise, no auxiliary treatment is performed.

[0019] A system for intelligent snoring recognition based on a low-frequency therapeutic apparatus, applying any of the above-mentioned methods for intelligent snoring recognition based on a low-frequency therapeutic apparatus, comprising a first threshold module, a second threshold module, a third threshold module, and a comprehensive judgment module connected in sequence;

[0020] A first threshold module is used to collect the blood oxygen saturation drop change data, and send the blood oxygen saturation drop change data to the low-frequency therapeutic device as a first threshold to trigger low-frequency stimulation;

[0021] A second threshold module, used for collecting snoring data based on the sound sensor, and sending the snoring data to the low-frequency therapeutic device as a second threshold for triggering low-frequency stimulation;

[0022] A third threshold module, used for collecting vibration data of local body movement based on a vibration sensor, and sending the vibration data to the low-frequency therapeutic device as a third threshold for triggering low-frequency stimulation;

[0023] The comprehensive judgment module is used to comprehensively judge whether the human body needs auxiliary treatment with low-frequency stimulation.

[0024] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides a method and system for intelligent snoring recognition based on a low-frequency therapeutic device, which has the following beneficial effects:

[0025] (1) The present invention is based on the medical phenomenon that when sleep apnea-obstructive hypopnea syndrome occurs, the human body will experience a decrease in blood oxygen saturation, and adds the decrease in blood oxygen saturation as an identification condition for triggering low-frequency stimulation of the device for auxiliary treatment of the disease. The present invention combines the snoring data collected by the microphone with the vibration data collected by the local body movement, so as to comprehensively judge whether the human body needs low-frequency stimulation auxiliary treatment;

[0026] (2) Adding the recognition condition of decreased blood oxygen saturation will make the intelligent recognition of the device more targeted to each individual, which will inevitably avoid the false triggering of the device caused by environmental interference. It will also greatly reduce the possibility of inaccurate individual triggering due to the inherent deficiency of intelligent recognition of snoring caused by the large differences in snoring volume and frequency between individuals and the large differences in snoring vibration degree. It will meet the requirements of the correctness of auxiliary treatment, ensure the treatment effect without affecting normal sleep, effectively reduce the cost of treatment, and also help patients relieve their symptoms as soon as possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0028] Figure 1 A flow chart of a method for intelligent snoring recognition based on a low-frequency therapeutic apparatus provided by the present invention;

[0029] Figure 2 A system structure block diagram of a low-frequency therapeutic apparatus for intelligent snoring recognition provided by the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] Reference Figure 1 As shown, the present invention discloses a method for intelligent snoring recognition based on a low-frequency therapeutic device, comprising the following steps:

[0032] S1. First threshold: Collect the blood oxygen saturation drop change data, and send the blood oxygen saturation drop change data to the low-frequency therapeutic device as the first threshold to trigger low-frequency stimulation;

[0033] S2. Second threshold: collecting snoring data based on the sound sensor, and sending the snoring data to the low-frequency therapeutic device as the second threshold for triggering low-frequency stimulation;

[0034] S3. The third threshold: collecting vibration data of local body movement based on the vibration sensor, and sending the vibration data to the low-frequency therapeutic device as the third threshold for triggering low-frequency stimulation;

[0035] S4. Comprehensive judgment: Based on S1-S3, it is determined whether the human body needs auxiliary treatment with low-frequency stimulation.

[0036] Furthermore, in S1, a blood oxygen sensor is used to collect blood oxygen saturation data values, thereby obtaining blood oxygen saturation decrease change data. The low-frequency therapeutic device and the blood oxygen sensor are connected in real time. When the blood oxygen saturation drops to a preset value, the low-frequency therapeutic device triggers pulse therapy through the intervention module.

[0037] Specifically, when the blood oxygen saturation drops to less than 95%, the low-frequency therapeutic device triggers pulse therapy through the intervention module, and the blood oxygen saturation preset value can also be specifically set according to different user types.

[0038] Furthermore, the real-time connection method between the low-frequency therapeutic device and the blood oxygen sensor includes one or more of Bluetooth, 4G, wireless network, and cable connection.

[0039] Furthermore, in S2, snoring data is collected based on the microphone in the low-frequency therapeutic device as a second threshold for triggering low-frequency stimulation.

[0040] Specifically, when the frequency range of the snoring data is 30 Hz-120 Hz, the second threshold of the low-frequency stimulation is triggered.

[0041] Furthermore, in S3, vibration data of local body movement is collected based on the vibration sensor in the low-frequency therapeutic device as the third threshold for triggering low-frequency stimulation.

[0042] Specifically, the threshold value of the vibration data of local body movement collected by the vibration sensor in the low-frequency therapeutic device can be specifically set according to the user type.

[0043] Furthermore, the specific content of S4 comprehensively judging whether the human body should undergo auxiliary treatment with low-frequency stimulation according to S1-S3 is:

[0044] When the low-frequency therapeutic device simultaneously receives data indicating that the blood oxygen saturation decreases to a preset value, the microphone detects snoring data, and the vibration sensor collects local body movement vibration data, the low-frequency therapeutic device emits a pulse current to stimulate the throat muscles for auxiliary treatment; otherwise, no auxiliary treatment is performed.

[0045] In a specific embodiment, the following are included

[0046] Collect the blood oxygen saturation decrease change data, and send the blood oxygen saturation decrease change data to the low-frequency therapeutic device as the first threshold to trigger low-frequency stimulation; collect snoring data based on the sound sensor, and send the snoring data to the low-frequency therapeutic device as the second threshold to trigger low-frequency stimulation; collect vibration data of local body movement based on the vibration sensor, and send the vibration data to the low-frequency therapeutic device as the third threshold to trigger low-frequency stimulation;

[0047] When the low-frequency therapeutic device simultaneously receives data indicating that the blood oxygen saturation decreases to a preset value, the microphone detects snoring data, and the vibration sensor collects local body movement vibration data, the low-frequency therapeutic device emits a pulse current to stimulate the throat muscles for auxiliary treatment; otherwise, no auxiliary treatment is performed.

[0048] In another specific embodiment, the following are included

[0049] The conditions for triggering the three at the same time are: when receiving the blood oxygen saturation decrease change data, it is also necessary to judge whether the snoring data and local body movement and vibration data have reached the set threshold. That is, when receiving the snoring data and local body movement and vibration data, it is also necessary to judge whether there is blood oxygen saturation decrease change data before deciding whether to trigger. Therefore, snoring data and local body movement and vibration data can be collected all the time, or snoring data and local body movement and vibration data can be collected after receiving the blood oxygen saturation decrease change data for judgment.

[0050] and Figure 1 Corresponding to the method described above, the embodiment of the present invention also provides a system for intelligent snoring recognition based on a low-frequency therapeutic apparatus, which is used to Figure 1 The specific implementation of the method is shown in the following diagram: Figure 2 As shown, it includes a first threshold module, a second threshold module, a third threshold module, and a comprehensive judgment module connected in sequence;

[0051] A first threshold module is used to collect the blood oxygen saturation drop change data, and send the blood oxygen saturation drop change data to the low-frequency therapeutic device as a first threshold to trigger low-frequency stimulation;

[0052] A second threshold module, used for collecting snoring data based on the sound sensor, and sending the snoring data to the low-frequency therapeutic device as a second threshold for triggering low-frequency stimulation;

[0053] A third threshold module, used for collecting vibration data of local body movement based on a vibration sensor, and sending the vibration data to the low-frequency therapeutic device as a third threshold for triggering low-frequency stimulation;

[0054] The comprehensive judgment module is used to comprehensively judge whether the human body needs auxiliary treatment with low-frequency stimulation.

[0055] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0056] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for intelligent snoring recognition based on a low-frequency therapeutic device, characterized in that: The following steps are involved: S1. First threshold: Collect the blood oxygen saturation drop change data, and send the blood oxygen saturation drop change data to the low-frequency therapeutic device as the first threshold to trigger low-frequency stimulation; S2. Second threshold: collecting snoring data based on the sound sensor, and sending the snoring data to the low-frequency therapeutic device as the second threshold for triggering low-frequency stimulation; S3. The third threshold: collecting vibration data of local body movement based on the vibration sensor, and sending the vibration data to the low-frequency therapeutic device as the third threshold for triggering low-frequency stimulation; S4. Comprehensive judgment: Based on S1-S3, it is determined whether the human body needs auxiliary treatment with low-frequency stimulation.

2. According to claim 1, a method for intelligent snoring recognition based on a low-frequency therapeutic apparatus is characterized in that: In S1, a blood oxygen sensor is used to collect blood oxygen saturation data values, thereby obtaining blood oxygen saturation decrease change data. The low-frequency therapeutic device and the blood oxygen sensor are connected in real time. When the blood oxygen saturation drops to the preset value, the low-frequency therapeutic device triggers pulse therapy through the intervention module.

3. According to claim 2, a method for intelligent snoring recognition based on a low-frequency therapeutic apparatus is characterized in that: The real-time connection method between the low-frequency therapeutic device and the blood oxygen sensor includes one or more of Bluetooth, 4G, wireless network, and cable connection.

4. The method for intelligent snoring recognition based on a low-frequency therapeutic apparatus according to claim 1, characterized in that: In S2, snoring data is collected based on the microphone in the low-frequency therapeutic device as the second threshold for triggering low-frequency stimulation.

5. The method for intelligent snoring recognition based on a low-frequency therapeutic apparatus according to claim 1, characterized in that: In S3, the vibration data of local body movement is collected based on the vibration sensor in the low-frequency therapeutic device as the third threshold for triggering low-frequency stimulation.

6. The method for intelligent snoring recognition based on a low-frequency therapeutic apparatus according to claim 1, characterized in that: The specific content of S4 for comprehensively judging whether the human body should undergo auxiliary treatment with low-frequency stimulation based on S1-S3 is: When the low-frequency therapeutic device simultaneously receives data indicating that the blood oxygen saturation decreases to a preset value, the microphone detects snoring data, and the vibration sensor collects local body movement vibration data, the low-frequency therapeutic device emits a pulse current to stimulate the throat muscles for auxiliary treatment; otherwise, no auxiliary treatment is performed.

7. A system for intelligent snoring recognition based on a low-frequency therapeutic device, characterized in that: A method for intelligent snoring recognition based on a low-frequency therapeutic device according to any one of claims 1 to 6 is applied, comprising a first threshold module, a second threshold module, a third threshold module, and a comprehensive judgment module connected in sequence; A first threshold module is used to collect the blood oxygen saturation decrease change data, and send the blood oxygen saturation decrease change data to the low-frequency therapeutic device as a first threshold to trigger low-frequency stimulation; A second threshold module, used for collecting snoring data based on the sound sensor, and sending the snoring data to the low-frequency therapeutic device as a second threshold for triggering low-frequency stimulation; A third threshold module, used for collecting vibration data of local body movement based on a vibration sensor, and sending the vibration data to the low-frequency therapeutic device as a third threshold for triggering low-frequency stimulation; The comprehensive judgment module is used to comprehensively judge whether the human body needs auxiliary treatment with low-frequency stimulation.

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