Snore monitoring method based on respiratory rate analysis

Abstract

The invention relates to the technical field of snore monitoring, in particular to a snore monitoring method based on respiratory rate analysis, which comprises the following steps: on the basis of using an optical fiber detection band as a monitoring tool to monitor respiration in real time, forming a respiration monitoring waveform, setting a respiration monitoring waveform under a normal respiration condition, setting a monitoring waveform of abnormal respiration, and comparing in real time, so as to obtain a snore monitoring result; if set data difference occurs, judging that breathing is abnormal. The optical fiber detection band is used as a monitoring tool to monitor breathing in real time as a basis, non-inductive recognition is achieved, the accuracy is higher through the breathing frequency, accurate monitoring of the snoring condition is achieved by monitoring and analyzing breathing frequency data in real time and combining with other physiological parameters, the limitation of a sound collection and recognition technology in a complex environment is avoided, and the intelligent snoring monitoring system is suitable for popularization and application. Meanwhile, a breathing monitoring waveform is formed, a breathing monitoring waveform under the normal breathing condition is set, a monitoring waveform under the abnormal breathing condition is set, and comparison is conducted in real time, so that the snoring behavior can be accurately found at the first time in subsequent sleep every time.

Description

Technical Field

[0001] The present invention relates to the technical field of snoring monitoring, and in particular to a snoring monitoring method based on respiratory frequency analysis. Background Art

[0002] One third of a person's life is spent sleeping. Sleep is a necessity of life and people cannot live without sleep. Sleep quality plays a vital role in human health, and the sleep missed every day must be made up. Everyone must follow the basic rules of normal sleep. If this most basic rule is disturbed, such as the lack of rapid eye movement sleep (REM) or non-rapid eye movement sleep (NREM), or the arrangement of NREM and REM is disordered, that is, REM instead of NREM appears just after falling asleep, then it must be a sleep disorder. Obstructive sleep apnea-hypopnea syndrome, also known as snoring, is a disease caused by partial or complete collapse of the upper airway due to various reasons during sleep, resulting in respiratory arrest. The disease is characterized by sleep apnea and hypopnea, and its main victims are obese middle-aged people, but the symptoms also appear in children and adolescents of different age groups. The disease is related to many factors such as obesity, age and gender, family history, drinking and drugs, smoking, and related diseases. The main symptoms of the disease are snoring during sleep and daytime drowsiness. In severe cases, it can cause high blood pressure, arrhythmia, cognitive dysfunction, abnormal glucose metabolism, etc. If the disease is serious, the patient should seek medical attention as soon as possible. During the diagnosis process, the doctor will ask the patient about the sleep history in detail, and conduct necessary physical examinations and special examinations. In general, for patients with obstructive sleep apnea hypopnea syndrome, as long as the cause is treated promptly and appropriately, the condition can be significantly improved.

[0003] For example, the patent document with the announcement number CN 115363544 A discloses a method for monitoring respiratory frequency and sleep breathing disorders based on wearable devices, the method comprising: the wearable device obtains physiological characteristic data including the pulse wave signal and electrocardiogram signal of the monitored user; pre-processes the pulse wave signal and the electrocardiogram signal to remove power frequency interference, baseline drift and motion artifacts, and uploads them to the big data center; establishes a respiratory frequency and sleep breathing disorder learning model based on the organ model, disease model and physiological characteristic data, and monitors the user's respiratory frequency and sleep breathing disorders in real time. The present invention only requires the monitoring user to wear a wearable device, which is easy to use and highly operable. Compared with a portable respiratory detector, it is low in cost and more convenient; the wearable device has strong real-time monitoring and can obtain the physiological characteristic data of the monitored user in real time, which is incomparable to a portable respiratory detector; in addition, the monitored user can make personalized healthy life adjustments based on the feedback data.

[0004] However, due to the limitation of its structure, the existing snoring monitoring method based on respiratory rate analysis currently uses a sound sensor to realize real-time respiratory monitoring. The monitoring sensitivity is relatively high, and the surrounding sounds will affect its judgment, resulting in the respiratory rate analysis, which often cannot reflect the snoring monitoring data most realistically. In addition, the device needs to be worn during the monitoring process, which affects normal sleep operations. At the same time, when the device determines snoring, the device cannot immediately perform deeper snoring data monitoring, and complete the adjustment or wake-up operation under the snoring state, which cannot meet daily use needs. Therefore, it is urgent to design a snoring monitoring method based on respiratory rate analysis to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a snoring monitoring method based on respiratory frequency analysis to solve the problem of the existing snoring monitoring method based on respiratory frequency analysis proposed in the above background technology. Due to the limitation of its own structure, the conventional way to judge snoring is to realize real-time respiratory monitoring through sound sensors. The monitoring sensitivity is relatively high, and the surrounding sounds will affect its judgment, resulting in the respiratory frequency analysis. It is often unable to reflect the snoring monitoring data most realistically, and the device needs to be worn during the monitoring process, affecting normal sleep operations. At the same time, when the device determines snoring, the device cannot immediately perform deeper snoring data monitoring, and complete the adjustment or wake-up operation under the snoring state, and cannot meet the daily use needs.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a snoring monitoring method based on respiratory frequency analysis: the optical fiber detection belt is used as a monitoring tool to monitor breathing in real time as a basis, a respiratory monitoring waveform is formed, a respiratory monitoring waveform under normal breathing conditions is set, and a monitoring waveform for abnormal breathing is set at the same time, and a real-time comparison is performed. If there is a difference in the set data, it is judged as abnormal breathing.

[0007] Preferably, if the breathing is abnormal three times within every five minutes, it is determined that the current state is snoring.

[0008] Preferably, if the system determines that the breathing is abnormal once or the system determines that the breathing is abnormal twice, it will be determined as normal.

[0009] Preferably, if the system determines that the breathing is abnormal three times, it will be determined as a snoring state.

[0010] Preferably, in the normal sleeping state, the device only checks the breathing state through the optical fiber detection belt, which will not affect normal sleep and avoid sleep disturbance caused by monitoring.

[0011] Preferably, in the abnormal snoring state, the bed side sensor can be connected with the patient's body through active docking to perform a deeper snoring monitoring operation, and the user's sleep state can be further analyzed in combination with heart rate data, body movement data, etc. According to the characteristic parameters of respiratory rate and sleep state, reasonable thresholds and judgment rules can be set to judge whether the user is in a snoring state, and the judgment result can be output in real time.

[0012] Preferably, once the snoring state is determined, an alarm mechanism on the bedside sensor is triggered immediately. At this time, the sensor emits a sound prompt, a vibration prompt, etc. to wake up the user or remind the guardian to avoid breathing obstruction.

[0013] Preferably, the monitoring data is sent to the pillow as soon as the snoring state is determined. At this time, an airbag mechanism is provided inside the pillow, which can automatically adjust the height, softness or tilt angle of the pillow according to algorithm instructions, guiding the user to adjust to a sleeping position that is less prone to snoring and avoid breathing obstruction.

[0014] Preferably, the monitoring data is sent to the mattress as soon as the snoring state is determined. At this time, a mechanical adjustment mechanism is provided inside the mattress, which can automatically adjust the height, hardness or tilt angle of each position of the mattress according to the algorithm instructions, guiding the user to adjust to a sleeping position that is not prone to snoring and avoid breathing obstruction.

[0015] Preferably, the data generated during each snoring process can be uploaded to the cloud, and a user sleep database can be established to analyze snoring patterns and trends, and provide personalized sleep improvement suggestions. When similar snoring states occur subsequently, the various devices can cooperate and start at the first time to ensure that snoring is suppressed in time.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The snoring monitoring method based on respiratory frequency analysis uses a fiber optic detection belt as a monitoring tool to monitor breathing in real time as the basis, and recognizes the breathing frequency without feeling, with higher accuracy. It can realize accurate monitoring of snoring through real-time monitoring and analysis of respiratory frequency data in combination with other physiological parameters, avoiding the limitations of sound collection and recognition technology in complex environments. At the same time, a respiratory monitoring waveform is formed, a respiratory monitoring waveform under normal breathing conditions is set, a monitoring waveform for abnormal breathing is set, and a comparison is made in real time. Snoring behavior can be accurately detected at the first time during each subsequent sleep, reflecting the practicality of the device design.

[0018] The snoring monitoring method based on respiratory frequency analysis, the patent of the present invention realizes accurate monitoring of snoring behavior by real-time monitoring of respiratory data and analyzing respiratory waveform characteristics, thereby improving monitoring accuracy. After detecting snoring behavior, the snoring behavior is promptly suppressed through the efficient cooperation of three groups of alarm devices, pillows and mattress structures, and the real-time data is uploaded so that the most effective suppression program can be started at the first time each subsequent snoring behavior occurs, reflecting the practicality of the device design. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the monitoring procedure of the present invention;

[0020] Figure 2 It is a schematic diagram of respiratory data of the present invention. DETAILED DESCRIPTION

[0021] 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.

[0022] See also Figure 1-2 , an embodiment provided by the present invention:

[0023] A snoring monitoring method based on respiratory frequency analysis uses an optical fiber detection belt as a monitoring tool to monitor breathing in real time, form a respiratory monitoring waveform, set the respiratory monitoring waveform under normal breathing conditions, and set the monitoring waveform of abnormal breathing at the same time, and compare them in real time. If there is a difference in the set data, it is judged as abnormal breathing. Within every five minutes, if the breathing is abnormal three times, it is determined to be a snoring state. The data generated during the entire snoring process can be uploaded to the cloud, and a user sleep database can be established to analyze snoring patterns and trends, and provide personalized sleep improvement suggestions. When a similar snoring state occurs later, the various devices can be coordinated and started at the first time to ensure that snoring is suppressed in time.

[0024] If the system determines that breathing is abnormal once or twice, it will be determined as normal. In a normal sleep state, the device only checks the breathing status through the optical fiber detection belt, which will not affect normal sleep and avoid sleep disturbances caused by monitoring.

[0025] If the system determines that the breathing is abnormal three times, it will be determined as a snoring state. In the abnormal snoring state, the active docking of the sensor on the side of the bed can be used to contact the patient's body to conduct a deeper snoring monitoring operation. Combined with heart rate data, body movement data, etc., the user's sleep state is further analyzed. According to the characteristic parameters of respiratory frequency and sleep state, reasonable thresholds and judgment rules are set to determine whether the user is in a snoring state. The judgment result can be output in real time. After the snoring state is determined, the alarm mechanism on the sensor on the side of the bed is triggered as soon as possible. At this time, the sensor wakes up the user or reminds the guardian by issuing sound prompts, vibration prompts, etc. to avoid respiratory obstruction. After the snoring state is determined, the monitoring data is sent to the pillow as soon as possible. At this time, the pillow is equipped with an airbag mechanism, which can automatically adjust the height, hardness or tilt angle of the pillow according to the algorithm instructions, and guide the user to adjust to a sleeping position that is not prone to snoring, avoiding respiratory obstruction. After the snoring state is determined, the monitoring data is sent to the mattress as soon as possible. At this time, the mattress is equipped with a mechanical adjustment mechanism, which can automatically adjust the height, hardness or tilt angle of each position of the mattress according to the algorithm instructions, and guide the user to adjust to a sleeping position that is not prone to snoring, avoiding respiratory obstruction.

[0026] The patent of the present invention uses an optical fiber detection belt as a monitoring tool to monitor breathing in real time as the basis, and non-sensing identification is achieved through breathing frequency with higher accuracy. By real-time monitoring and analysis of breathing frequency data, combined with other physiological parameters, accurate monitoring of snoring is achieved, avoiding the limitations of sound collection and recognition technology in complex environments, and forming a breathing monitoring waveform at the same time, setting the breathing monitoring waveform under normal breathing conditions, setting the monitoring waveform of abnormal breathing, and making a real-time comparison. Each subsequent sleep can accurately detect snoring behavior at the first time. By real-time monitoring of breathing data and analyzing breathing waveform characteristics, accurate monitoring of snoring behavior is achieved, and monitoring accuracy is improved. After detecting snoring behavior, the alarm device, pillow and mattress structure are used to efficiently cooperate with each other to complete the timely suppression of snoring behavior, and the real-time data is uploaded to facilitate the start of the most effective suppression program at the first time of each subsequent snoring behavior. The above is the entire working principle of the present invention.

[0027] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A snoring monitoring method based on respiratory frequency analysis, characterized in that: The optical fiber detection belt is used as a monitoring tool to monitor breathing in real time as a basis to form a breathing monitoring waveform, set the breathing monitoring waveform under normal breathing conditions, and set the monitoring waveform of abnormal breathing at the same time, and compare them in real time. If there is a difference in the setting data, it is judged as abnormal breathing.

2. A snoring monitoring method based on respiratory frequency analysis according to claim 1, characterized in that: If the breathing is abnormal three times within every five minutes, it is determined that the current state is snoring.

3. A snoring monitoring method based on respiratory frequency analysis according to claim 1, characterized in that: If the system determines that the breathing is abnormal once or the system determines that the breathing is abnormal twice, it will be determined as normal.

4. The snoring monitoring method based on respiratory frequency analysis according to claim 1, characterized in that: If the system determines that the breathing is abnormal three times, it will be determined as a snoring state.

5. The snoring monitoring method based on respiratory frequency analysis according to claim 3, characterized in that: In the normal sleep state, the device only checks the breathing state through the optical fiber detection belt, which will not affect normal sleep and avoid sleep disturbance caused by monitoring.

6. A snoring monitoring method based on respiratory frequency analysis according to claim 4, characterized in that: In the abnormal snoring state, the bed side sensor can be connected with the patient's body through active docking to perform deeper snoring monitoring operations, and combine heart rate data, body movement data, etc. to further analyze the user's sleep state. According to the characteristic parameters of respiratory rate and sleep state, reasonable thresholds and judgment rules are set to judge whether the user is in a snoring state, and the judgment result can be output in real time.

7. A snoring monitoring method based on respiratory frequency analysis according to claim 6, characterized in that: Once the snoring state is confirmed, the alarm mechanism on the bedside sensor is triggered immediately. At this time, the sensor emits a sound prompt, a vibration prompt, etc. to wake up the user or remind the guardian to avoid breathing obstruction.

8. The snoring monitoring method based on respiratory frequency analysis according to claim 6, characterized in that: After the snoring state is determined, the monitoring data is sent to the pillow as soon as possible. At this time, an airbag mechanism is installed inside the pillow, which can automatically adjust the height, softness or tilt angle of the pillow according to the algorithm instructions, guiding the user to adjust to a sleeping position that is not prone to snoring and avoid breathing obstruction.

9. The snoring monitoring method based on respiratory frequency analysis according to claim 6, characterized in that: After the snoring state is determined, the monitoring data is sent to the mattress as soon as possible. At this time, a mechanical adjustment mechanism is provided inside the mattress, which can automatically adjust the height, hardness or tilt angle of each position of the mattress according to the algorithm instructions, guiding the user to adjust to a sleeping position that is not prone to snoring and avoid breathing obstruction.

10. The snoring monitoring method based on respiratory frequency analysis according to claim 1, characterized in that: The data generated during each snoring process can be uploaded to the cloud, and a user sleep database can be established to analyze snoring patterns and trends, and provide personalized sleep improvement suggestions. When similar snoring states occur subsequently, the various devices can cooperate and start at the first time to ensure that snoring is suppressed in time.

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