A healthy sleep management system and method

Abstract

The present invention relates to a healthy sleep management system and method. The system includes a first sleep monitor and a second sleep monitor. The first sleep monitor collects at least one first sleep characteristic data related to the user's time and determines a first sleep pattern while the user is in a sleep state. The second sleep monitor collects at least one second sleep characteristic data related to the user's time and determines a second sleep pattern while the user is in a sleep state. The system compares the difference between the first sleep pattern and the second sleep pattern and generates updated information about the sleep state metric of the first sleep monitor. The system then enables the first sleep monitor to correct its monitoring results for the first sleep pattern based on the updated information about the sleep state metric. The present invention enables high-precision monitoring of sleep monitoring results of portable wearable devices.

Description

Technical Field

[0001] The present invention relates to the technical field of sleep monitoring, and in particular to a healthy sleep management system and method. Background Art

[0002] Sleep can generally be characterized by two main types: non-REM (rapid eye movement) sleep and REM (rapid eye movement) sleep, also known as dream sleep. Non-REM sleep consists of three stages of sleep with varying depths, starting with a transition to the shallowest stage of sleep, through a second shallow stage, and deepening to a third deep sleep stage from which the sleeper is very difficult to awaken. Sleep occurs in a series of recurring sleep stages, in which periods of non-REM (rapid eye movement) sleep and REM (rapid eye movement) sleep alternate, the sum of which can be called a sleep cycle.

[0003] Users with sleep apnea syndrome (SAS) are prone to experiencing breathing pauses and / or hypopneas, disrupting sleep, and other symptoms. If breathing pauses last for several seconds or minutes, the body can wake up due to lack of oxygen. Frequent breathing pauses can significantly reduce sleep quality and pose health risks.

[0004] Hypopnea manifests as shallow breathing or an abnormal breathing rate. Hypopnea is generally defined by a decrease in the amount of air moving into the lungs. Like sleep apnea syndrome (SAS), hypopnea disrupts a person's sleep, and even though people with hypopnea experience a full night of sleep, they still feel they are not getting enough rest.

[0005] Therefore, sleep quality is crucial to daily activities. While it's clear that the human body requires sleep to function properly, determining the quality and quantity of sleep remains a complex issue. In recent years, extensive research has focused on understanding sleep and its physiological and psychological effects. For example, some people experience daytime fatigue and tiredness when they're severely sleep deprived, while others experience a similar sense of languor after excessive sleep.

[0006] Currently, in order to improve users' sleep quality, more sleep-aiding devices are being developed and produced. For example, CN110882466A discloses a sleep instrument comprising a main unit and a magnetic coil electrically connected to the main unit. The main unit comprises a main control device and a conversion circuit, the main control device being electrically connected to the magnetic coil, and the conversion circuit being electrically connected to the main control device. The main control device generates a square wave signal and inputs it into the conversion circuit. The conversion circuit converts the square wave signal into a pulse signal, which is input into the magnetic coil to cause the magnetic coil to generate a time-varying magnetic field. The time-varying magnetic field is coupled to the sleep center of the brain of a patient with sleep disorders, thereby regulating and inducing the patient's sleep process and achieving the function of promoting sleep or awakening.

[0007] Portable sleep monitoring products are usually wearable / wornable (such as wristwatch-style smart sleep monitors). Some of them judge the sleep state and sleep quality based on the user's tossing frequency collected by the accelerometer, and some of them judge the sleep state and sleep quality based on the user's body temperature, heartbeat and other data collected by various sensors. The common defects of these two types of sleep monitoring products include: the preset sleep state measurement indicators are popular rather than personalized; when there are individual sleep differences among users, the preset sleep state measurement indicators cannot match the sleep conditions of each individual, which leads to errors in the sleep monitor's judgment of the user's sleep state. As the use time of the sleep monitor increases, the error in the sleep monitor's judgment of the sleep state will become larger and larger. This is also the reason why current medical practitioners or doctors cannot use the monitoring data of portable sleep monitors as reference data for sleep treatment.

[0008] Sleep monitoring equipment used in hospitals typically assesses a user's sleep quality by measuring brainwaves. Because brainwaves are the golden rule for defining sleep states, existing medical EEG detection devices can accurately assess a subject's sleep state. However, EEG signals can be extremely weak, and the highly accurate equipment used to record them is expensive and bulky. Therefore, existing medical-grade sleep monitoring equipment is typically only available in healthcare facilities such as hospitals and clinics, making it inconvenient for home use.

[0009] Therefore, how to combine the advantages of portable sleep monitors' portable monitoring capabilities with the advantages of medical-grade sleep monitoring equipment's precise judgment capabilities is a problem that currently available products cannot solve.

[0010] In addition, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making the present invention, but due to space limitations, not all details and contents are listed in detail. However, this does not mean that the present invention does not have the characteristics of these prior arts. On the contrary, the present invention already has all the characteristics of the prior art, and the applicant reserves the right to add relevant prior art to the background technology. Summary of the Invention

[0011] Existing portable devices do not accurately monitor a user's sleep patterns. Regularly calibrating sleep status metrics on portable devices to accurately assess sleep patterns remains a currently unresolved technical issue.

[0012] To achieve the above-mentioned objectives, the healthy sleep management system of the present invention includes a first sleep monitor and a second sleep monitor. The first sleep monitor collects at least one first sleep characteristic data related to time of the user in the sleep state and determines the first sleep mode; the second sleep monitor collects at least one second sleep characteristic data related to time of the user in the sleep state and determines the second sleep mode, compares the difference between the first sleep mode and the second sleep mode, and generates updated information of the sleep state measurement index of the first sleep monitor, so that the first sleep monitor can correct the monitoring result of the first sleep mode based on the updated information of the sleep state measurement index. The present invention updates the sleep state measurement index of the first sleep monitor by using the second sleep monitor that can accurately judge the sleep mode, so that the first sleep monitor can accurately judge the user's sleep state.

[0013] According to a preferred embodiment, the first sleep monitor and the second sleep monitor are each connected to a terminal via wired and / or wireless communication. The terminal retrieves a corresponding auxiliary treatment plan from a database based on the received second sleep pattern. By incorporating the terminal, the present invention enables the terminal to analyze, display, and retrieve data, helping users further understand their sleep process and auxiliary treatment methods through the terminal.

[0014] According to a preferred embodiment, the first sleep monitor updates the sleep state metric based on the received sleep state metric update information to improve the accuracy of the first sleep mode monitoring results. Because the first sleep monitor is a portable wearable device, long-term monitoring may be inaccurate. The present invention updates the sleep state metric of the first sleep monitor to make the first sleep monitor's monitoring results of the user's sleep state more accurate.

[0015] According to a preferred embodiment, upon receiving a first sleep pattern transmitted by a first sleep monitor, the terminal generates sleep intervention data based on the auxiliary treatment plan and the first sleep pattern, enabling a sleep intervention device connected to the terminal to implement sleep intervention actions on the user based on the sleep intervention data. The present invention utilizes the terminal and the sleep intervention device to implement sleep intervention on the user, enabling the sleep intervention device to effectively intervene in the user's actions, thereby improving the user's sleep quality.

[0016] According to a preferred embodiment, a first sleep monitor collects first sleep characteristic data of the user in a wearable manner, while a second sleep monitor collects second sleep characteristic data of the user by collecting brainwave data. Because the results of analyzing sleep patterns using brainwave data are relatively accurate, using the second sleep monitor to calibrate the sleep state measurement indicators of the first sleep monitor can improve the accuracy of the first sleep monitor's sleep monitoring results.

[0017] According to a preferred embodiment, a second sleep monitor determines a first sleep pattern and a second sleep pattern within the same sleep cycle based on time and compares the difference between the first and second sleep patterns. The second sleep monitor receives the sleep state metric from the first sleep monitor and adjusts the updated information of the first sleep monitor's sleep state metric based on the second sleep pattern as the monitoring result that the first sleep monitor should determine. Correcting the sleep state metric based on the same sleep cycle accurately determines the difference between the two sleep patterns and prevents incorrect calibration of the sleep state metric.

[0018] According to a preferred embodiment, the sleep state metric indicator update information of the first sleep monitor includes one of sleep state metric indicator replacement information and sleep state metric indicator adjustment difference information. Both types of sleep state metric indicator update information can calibrate or correct the sleep state metric indicator of the first sleep monitor, ensuring that the sleep pattern determined by the first sleep monitor is accurate.

[0019] According to a preferred embodiment, a first sleep monitor includes: a first acquisition module, a first processing module, and a first output module. The first acquisition module is configured to acquire at least one first sleep characteristic data item representing a user's sleep state; the first processing module is configured to determine a first sleep pattern associated with the user in response to the at least one first sleep characteristic data item acquired by the first acquisition module; and the first output module is configured to output information related to the first sleep pattern from the first processing module. The first sleep monitor of the present invention can directly determine and output the first sleep pattern based on a preset monitoring program.

[0020] According to a preferred embodiment, the second sleep monitor includes a second acquisition module, a second processing module, and a second output module. The second acquisition module is used to obtain at least one second sleep characteristic data representing the user's sleep state; the second sleep characteristic data is different from the first sleep characteristic data; the second processing module is capable of determining a second sleep pattern associated with the user in response to the at least one second sleep characteristic data obtained from the second acquisition module; the difference between the first sleep pattern and the second sleep pattern is compared and updated information of the sleep state metric of the first sleep monitor is generated; and the second output module is used to output the second sleep pattern and updated information of the sleep state metric of the first sleep monitor. The second sleep monitor has a high accuracy in determining sleep patterns and can therefore be used for calibration and generation of updated information of sleep state metric.

[0021] The present invention provides a healthy sleep management method from a second aspect, the method comprising: a first sleep monitor collecting at least one first sleep characteristic data related to time of the user while in a sleep state and determining a first sleep pattern; a second sleep monitor collecting at least one second sleep characteristic data related to time of the user while in a sleep state and determining a second sleep pattern, comparing the difference between the first sleep pattern and the second sleep pattern and outputting updated information of the sleep state measurement index of the first sleep monitor, so that the first sleep monitor can correct the monitoring result of the first sleep pattern based on the updated information of the sleep state measurement index. The healthy sleep management method of the present invention is simple in calibrating the first sleep monitor and does not significantly increase the user's cost. At the same time, it allows the monitoring results of the first sleep monitor to be calibrated regularly, providing a good sleep monitoring basis for sleep-assisted treatment.

[0022] According to a preferred embodiment, the method further includes: when the second sleep monitor is connected to the terminal via a wired and / or wireless connection, the terminal retrieves a corresponding auxiliary treatment plan from a database based on the received second sleep pattern. The method of the present invention can provide a corresponding auxiliary treatment plan based on an accurate sleep pattern, thereby ensuring high-quality sleep intervention for the user.

[0023] According to a preferred embodiment, the method further includes: the first sleep monitor updating the sleep state metric based on the received update information of the sleep state metric to improve the accuracy of the monitoring result of the first sleep mode.

[0024] From a third aspect, the present invention also provides a sleep monitoring system, including a first sleep monitor and a second sleep monitor that communicate with each other, the first sleep monitor and the second sleep monitor respectively collecting at least one first sleep characteristic data and second sleep characteristic data of the user related to time in the sleep state; the first sleep characteristic data is different from the second sleep characteristic data; the first sleep monitor determines the user's first sleep pattern based on the first sleep characteristic data, and sends the first sleep pattern to the second sleep monitor; the second sleep monitor determines the user's second sleep pattern based on the second sleep characteristic data, compares the difference between the first sleep pattern and the second sleep pattern and generates updated information of the sleep state measurement index of the first sleep monitor, the first sleep monitor receives and corrects the monitoring result of the first sleep pattern based on the updated information of the sleep state measurement index.

[0025] The sleep monitoring system of the present invention can realize monitoring calibration of the first sleep monitor by using only two devices in an interactive manner, requires a small number of devices, and has good monitoring results for the first sleep mode.

[0026] According to a preferred embodiment, the second sleep monitor retrieves from a database a supplementary treatment plan that matches and is applicable to the first sleep monitor based on the second sleep pattern. When the first sleep monitor is in communication with a sleep intervention device, the first sleep monitor sends corresponding instruction information to the sleep intervention device based on the user's first sleep pattern and the supplementary treatment plan while the user is asleep, causing the sleep intervention device to implement a sleep intervention operation based on the received instruction information. The sleep monitoring system of the present invention utilizes the matching supplementary treatment plan to implement the sleep intervention operation, thereby intervening in the user's sleep and improving their sleep quality.

[0027] According to a fourth aspect, the present invention provides a sleep-assisted therapy terminal. When a user is in a sleeping state, the terminal is communicatively connected to a first sleep monitor and a second sleep monitor respectively. The terminal is configured to: receive update information of a sleep state metric indicator of the first sleep monitor sent by the second sleep monitor; regularly calibrate the sleep state metric indicator of the first sleep monitor based on the update information of the sleep state metric indicator of the first sleep monitor; receive a first sleep pattern sent by the first sleep monitor and retrieve a corresponding auxiliary therapy plan from a database.

[0028] The advantage of the sleep-assisted therapy terminal of the present invention is that it can use the data of the second sleep monitor with higher monitoring accuracy and its sleep pattern information to calibrate the sleep state measurement index of the first sleep monitor with lower monitoring accuracy, and can determine the corresponding auxiliary therapy plan based on the accurate first sleep pattern, so that the user's sleep can be scientifically intervened to improve sleep quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a structural diagram of a healthy sleep management system according to a preferred embodiment of the present invention;

[0030] Figure 2 This is a working logic diagram of the healthy sleep management system provided by the present invention;

[0031] Figure 3 This is a working logic diagram of the terminal of the healthy sleep management system provided by the present invention;

[0032] Figure 4 It is a flow chart of a healthy sleep management method according to a preferred embodiment of the present invention.

[0033] Reference Signs List

[0034] 100: First sleep monitor; 200: Second sleep monitor; 310: First acquisition module; 320: Second acquisition module; 410: First processing module; 420: Second processing module; 510: First output module; 520: Second output module; 600: Terminal; 700: Database; 810: Extraction unit; 820: Analysis unit; 830: Storage unit. DETAILED DESCRIPTION

[0035] The following is a detailed description with reference to the accompanying drawings.

[0036] Example 1

[0037] The American Academy of Sleep Medicine (AASM) divides the adult sleep cycle into stages W (wakefulness), N1 (non-rapid eye movement 1 (NREM1), N2 (non-rapid eye movement 2 (NREM2), N3 (non-rapid eye movement 3 (NREM3), and R (rapid eye movement (REM)). Sleep begins in stage W by first entering NREM sleep, starting with stage N1, which lasts approximately 3 to 7 minutes, and then transitioning to stage N2; stage N2 lasts approximately 10 to 25 minutes. This is followed by stages N3-N4, which can last from a few minutes to an hour. After deep sleep ends, sleep returns to stage N1 or N2. Then, it transitions to the first REM sleep period (the first REM period lasts 5 to 10 minutes), completing the first sleep cycle. Specifically, during a sleep cycle, non-REM (rapid eye movement) sleep accounts for approximately 75% to 80%, while REM (rapid eye movement) sleep accounts for approximately 20% to 25%.

[0038] In particular, the average adult has four to six sleep cycles per night. In the second half of the night, deep non-rapid eye movement (NREM) sleep gradually decreases, while REM (rapid eye movement) sleep gradually increases. Specifically, N3 sleep accounts for a higher proportion in the first half of the night, while N3 sleep decreases and REM sleep increases in the second half of the night.

[0039] Furthermore, during sleep, the brain usually produces a variety of brain wave signals, such as alpha waves, beta waves, theta waves, delta waves, and other non-characteristic waves, such as top waves, spindle waves, and K complex waves. Specifically, alpha waves: mainly seen in the quiet, awake, closed-eye state and R (rapid eye movement) period, with a frequency of 8 to 13 Hz. Beta waves: mainly seen in the awake, open-eye state, low-potential waves with a frequency >13 Hz (mostly 14 to 30 Hz). Theta waves: mainly seen in the late N1 stage, with a frequency of 4 to 7 Hz. Delta waves: mainly seen in deep sleep, low-frequency waves with a frequency of 1 to 3 Hz. Therefore, brain wave signals can be used to determine the user's different sleep patterns and complete sleep cycles.

[0040] Although portable sleep monitors currently on the market have the advantages of being small and easy to wear, their sleep patterns determined based on data such as body temperature, heart rate, and respiratory rate can only provide users with a reference for sleep information, and cannot provide medical-level judgment results on users' sleep patterns.

[0041] Compared with medical-grade sleep monitors, the detection accuracy and precision of such portable sleep monitors are very limited, and one or more of the sleep cycles, sleep quality index, sleep efficiency, sleep onset latency, sleep fragmentation and / or other metrics related to the user's sleep process determined by them are likely to be inaccurate.

[0042] Therefore, the portable sleep monitor may give erroneous monitoring results on the sleep state, resulting in unreasonable sleep assistance treatment plans provided to users.

[0043] In order to address the problem that portable wearable devices have large errors in monitoring the user's sleep pattern, resulting in the inability to provide the user with accurate auxiliary treatment plans, or even the inability to implement accurate sleep intervention operations on the user's sleep through sleep intervention equipment, the present invention uses a sleep monitor with high accuracy in judging sleep patterns to calibrate or update the sleep state measurement indicators of the wearable device, so that the portable wearable device can accurately judge or evaluate the user's sleep pattern.

[0044] Various embodiments and / or implementations herein relate to a management system and method thereof that utilizes user data (such as heart rate, body temperature, respiratory waveform, etc.) to monitor and quantify the user's sleep quality.

[0045] The present invention provides a healthy sleep management system, such as Figure 1 As shown, a first sleep monitor 100 and a second sleep monitor 200 are included.

[0046] Specifically, the first sleep monitor 100 can be a wearable sleep monitor. The first sleep monitor 100 collects the user's first sleep characteristic data in a wearable manner. Wearable sleep monitors can be, for example, hand-held, wristwatch-style, neck-wrap-around, head-clip-on, and so on. In particular, the present invention does not limit the specific structure of the wearable first sleep monitor 100.

[0047] Since physiological changes during sleep are closely linked to a person's sleep state, existing sleep monitors can determine a person's sleep state based on physiological signals such as body temperature, heart rate, and respiratory rate, as mentioned above. This includes determining the person's total sleep duration, the sleep stages corresponding to each time point, the segmented and total duration of a sleep stage, the interruptions and transitions between sleep stages, and sleep efficiency.

[0048] The first sleep characteristic data may generally include data signals such as body temperature (T), motion (S), heart rate (H), and respiratory rate (R). In particular, the data signals such as body temperature (T), motion (S), heart rate (H), and respiratory rate (R) are stored in a time- or frequency-dependent manner.

[0049] The first sleep monitor 100 collects at least one first sleep characteristic data related to time of the user in a sleeping state and determines a first sleep pattern.

[0050] like Figure 2 As shown, the first sleep monitor 100 includes a first acquisition module 310, a first processing module 410 and a first output module 510. The first acquisition module 310, the first processing module 410 and the first output module 510 are connected to each other in a wired and / or wireless manner.

[0051] The first acquisition module 310 is used to obtain at least one first sleep characteristic data representing the user's sleep state. The first acquisition module 310 can be a wearable device, sensor, or other element configured to or capable of obtaining data about the user. The first acquisition module 310 can also communicate directly with the user's wearable device, or can obtain the user's first sleep characteristic data via indirect contact (video, IR, motion detector, or other type of sensor).

[0052] In the present invention, the first acquisition module 310 may be a sensor. Specifically, the first acquisition module 310 may include one or more of a temperature sensor, a heart rate sensor, a respiration sensor, and a motion sensor. The temperature sensor may be used to collect a user's body temperature characteristic signal. The heart rate sensor may be used to collect a user's heart rate characteristic signal. The respiration sensor may be used to collect a user's respiratory rate characteristic signal. The motion sensor may be used to collect a user's body movement characteristic signal.

[0053] The first processing module 410 can determine a first sleep pattern related to the user in response to at least one first sleep characteristic data acquired from the first acquisition module 310 .

[0054] The first processing module 410 has information analysis and processing functions. The first processing module 410 can be a dedicated integrated circuit, a CPU, or a processor capable of running a coding program for determining the first sleep pattern. The first processing module 410 can include an extraction unit 810, an analysis unit 820, and a storage unit 830. Specifically, the extraction unit 810 can extract one or more sleep characteristic data from the first acquisition module 310. The analysis unit 820 can store the real-time sleep characteristic data in the storage unit 830 and analyze the first sleep characteristic data based on preset sleep state metrics to derive a sleep pattern or sleep quality evaluation result.

[0055] Preferably, the first processing module 410 may not be provided in the hardware body of the first sleep monitor 100, and the terminal 600, which is in communication with the first processing module 410, may execute the operating program for determining the first sleep mode. In other words, the first processing module 410 is replaced by the terminal 600. The terminal 600 feeds back the first sleep mode and related information to the first sleep monitor 100.

[0056] The first output module 510 is used to output information related to the first sleep mode from the first processing module 410. The first output module 510 can output information such as the sleep mode, the time of the sleep mode, the time period, the sleep cycle, and the change of the sleep mode.

[0057] Specifically, the first output module 510 can output the user's sleep pattern and its evaluation information using any method capable of conveying information. For example, one or more of display, vibration, sound / light, etc. Alternatively, the generated first sleep pattern and its evaluation results can be provided via an interface, such as a monitor, mobile device, laptop, desktop computer, wearable device, or home computing device.

[0058] In particular, the data related to sleep patterns may include sleep quality index, sleep cycles, total sleep time, sleep efficiency, sleep onset latency, sleep fragmentation, and / or other metrics. Furthermore, the sleep pattern evaluation results may be in the form of a chart, a curve, or text, or any combination thereof.

[0059] When the first acquisition module 310 is a heart rate sensor, the extraction unit 810 can extract the heart rate characteristic signal from the heart rate sensor. The analysis unit 820 can store the real-time heart rate characteristic signal in the storage unit 830 and analyze it to obtain an evaluation result of the user's sleep state or sleep quality. Furthermore, the analysis unit 820 can output the evaluation result of the user's sleep pattern or sleep quality to the user's terminal 600 via the first output module 510 or display it via the first output module 510. In particular, the heart rate sensor can be one or more of an electrocardiogram sensor, a blood oxygen saturation sensor, an ultrasonic sensor, a photoplethysmography sensor, and a radio frequency sensor.

[0060] According to a preferred embodiment, when the first acquisition module 310 is a temperature sensor, the extraction unit 810 can extract a characteristic body temperature signal from the temperature sensor. The analysis unit 820 can store the real-time characteristic body temperature signal in the storage unit 830 and analyze it to derive an evaluation result of the user's sleep pattern or sleep quality. Furthermore, the analysis unit 820 can output the evaluation result of the user's sleep state or sleep quality to the user's terminal 600 via the first output module 510 or display it via the first output module 510.

[0061] According to a preferred embodiment, when the first acquisition module 310 is a respiratory sensor, the extraction unit 810 can extract a respiratory frequency characteristic signal from the respiratory sensor. The analysis unit 820 can store the real-time respiratory frequency characteristic signal in the storage unit 830 and analyze it to obtain an evaluation result of the user's sleep state or sleep quality. Furthermore, the analysis unit 820 can output the evaluation result of the user's sleep pattern or sleep quality to the user's terminal 600 via the first output module 510 or display it via the first output module 510. In particular, the respiratory sensor can be one or more of a displacement sensor, a strain gauge sensor, and a photoplethysmography sensor.

[0062] In particular, in the present invention, the heart rate characteristic signal and the respiratory frequency characteristic signal can constitute the user's cardiopulmonary characteristic signal. In addition to the above, the cardiopulmonary characteristic signal can also include a respiratory variability characteristic signal and a cardiopulmonary coupling characteristic signal.

[0063] According to a preferred embodiment, when the first acquisition module 310 is a motion sensor, the extraction unit 810 can extract the body motion characteristic signal from the motion sensor. In particular, the user's body motion characteristic signal may generally include characteristic signals such as turning over and twisting of the human body. Further, the analysis unit 820 can store the real-time body motion characteristic signal in the storage unit 830 and analyze it to obtain the evaluation result of the user's sleep state or sleep quality. Further, the analysis unit 820 can output the evaluation result of the user's sleep pattern or sleep quality to the user through the first output module 510. In particular, the body motion sensor can adopt one or more of a linear accelerometer, an angular accelerometer or other sensors that can detect the movement of an object.

[0064] According to a preferred embodiment, after the first processing module 410 obtains the evaluation results of the user's sleep pattern or sleep quality, it can be transmitted to an external electronic device, such as a computer, mobile phone, etc., through an output interface for display or analysis, or uploaded to a cloud database 700 / server through the output interface so that the user can obtain more comprehensive analysis and sleep guidance.

[0065] According to a preferred embodiment, the first processing module 410 can analyze and determine the user's sleep pattern or sleep quality based on multiple sleep characteristic data of the user. Specifically, the first acquisition module 310 can collect the user's body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal, and body motion characteristic signal, etc. separately or simultaneously. One or more extraction units 810 of the first processing module 410 can extract and amplify the user's body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal and / or body motion characteristic signal. The analysis unit 820 can analyze the user's sleep state or sleep quality based on the analysis of the body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal and / or body motion characteristic signal from the extraction unit 810.

[0066] In an optional embodiment, the analysis unit 820 may use a weighted operation to process one or more of the user's body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal and body movement characteristic signal, and obtain an evaluation result of the user's sleep state or sleep quality based on the analysis and processing results of these sleep characteristic data signals.

[0067] Specifically, for example, a corresponding weighting coefficient may be assigned to each of the user's body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal, and body motion characteristic signal, and / or a corresponding weighting coefficient may be assigned to each of the user's body temperature characteristic signal change rate, heart rate characteristic signal change rate, respiratory rate characteristic signal change rate, and body motion characteristic signal change rate. Subsequently, a sleep quality index associated with the one or more sleep characteristic data signals or characteristic data signal change rates is calculated based on a preset weighted average algorithm.

[0068] Furthermore, the calculated sleep quality index can be compared with a preset quality threshold, and the user's sleep pattern or sleep quality can be determined based on the difference between the sleep quality index and the preset quality threshold or the preset quality threshold interval. For example, if the sleep quality index is less than the preset quality threshold, the user's sleep quality is poor.

[0069] Alternatively, in an optional embodiment, the user's sleep characteristic data, such as body temperature (T), motion (S), heart rate (H), and respiratory rate (R), can be specifically waveforms, such as body temperature waveforms, motion waveforms, heart rate waveforms, and respiratory waveforms. These waveforms can be measured and obtained by a wearable sleep monitor.

[0070] According to a preferred embodiment, after the extraction unit 810 obtains these sleep characteristic data waveforms, the analysis unit 820 can divide these characteristic data waveforms into several segmented waveforms. The analysis unit 820 can extract characteristic data from these segmented waveforms. The characteristic data is, for example, body temperature data, heart rate data, or respiratory data. Furthermore, the analysis unit 820 can classify the user's sleep state or stage based on the characteristic data in these segmented waveforms. In particular, the data model used by the analysis unit 820 to classify the user's sleep pattern based on the characteristic data in the segmented waveforms can be obtained through machine learning, predetermined threshold programming, self-setting by medical personnel, and / or other possible methods.

[0071] Specifically, the analysis unit 820 can classify the user's sleep pattern into one or more stages of W, N1, N2, N3, and R. Furthermore, the analysis unit 820 can analyze the user's sleep pattern or sleep quality results for one or more categories of sleep stages. For example, the user's sleep pattern or sleep quality results can be the sum of the sleep quality indexes of each sleep stage. In addition, the evaluation results of the sleep pattern or sleep quality can also be determined based on one or more of the total sleep time, sleep efficiency, sleep onset latency, and sleep fragmentation.

[0072] According to a preferred embodiment, the wearable sleep monitor 100 provided by the present invention may also be capable of applying or providing a waveform with a frequency close to that of brain waves, or a time-varying magnetic field pre-stored in the storage unit 830 for generating corresponding brain waves, to any target point on the user's body. Specifically, the target point on the user may be an acupuncture point on the human body, such as the Baihui, Shenfeng, Zhaohai, or Yongquan points.

[0073] Specifically, for example, if the analysis unit 820 of the first sleep monitor 100 determines that the user's sleep state or sleep quality is poor or requires adjustment based on one or more sleep characteristic data acquired by the first acquisition module 310 during the user's sleep, the sleep intervention device can be used to intervene in the user's physical sensations and change the user's sleep pattern. For example, when the sleep intervention device is a magnetic field device, the magnetic field device provides a time-varying magnetic field to the user's body. Furthermore, the time-varying magnetic field provided by the magnetic field device by the analysis unit 820 is configured in association with the user's sleep pattern or sleep quality.

[0074] While the user is sleeping, the second sleep monitor 200 collects at least one second sleep characteristic data item related to time and determines a second sleep pattern. The second sleep monitor 200 collects the second sleep characteristic data by collecting the user's brainwave data. The second sleep monitor 200 compares the first sleep pattern with the second sleep pattern and generates updated sleep state metric information for the first sleep monitor 100. This allows the first sleep monitor 100 to modify its monitoring results for the first sleep pattern based on the updated sleep state metric information.

[0075] The second sleep characteristic data is different from the first sleep characteristic data. The second sleep characteristic data is bioelectrical signal data. Bioelectrical signal data may include brain wave signals, electrooculogram signals, electromyographic signals, and electrocardiogram signals. In particular, brain wave signals, electrooculogram signals, electromyographic signals, and electrocardiogram signals are stored in a time- or frequency-dependent manner. In the present invention, the second sleep characteristic data is described using the electroencephalogram (EGG) signal as an example.

[0076] In the present invention, the second sleep monitor 200 can be an EEG sleep monitor, such as that used in hospitals or medical clinics. Specifically, the second sleep monitor 200 can be, for example, a polyencephalogram (PEO) sleep monitor. In particular, the second sleep monitor 200 can determine the user's sleep pattern at least based on EEG signals. Alternatively, the second sleep monitor 200 can determine the user's sleep pattern based on at least two of EEG signals, electrooculogram (EOG) signals, and electromyography (EMG) signals. In other words, the second sleep monitor 200 can determine the user's sleep pattern based on bioelectrical signals.

[0077] According to a preferred embodiment, the second sleep monitor 200 includes a second acquisition module 320, a second processing module 420, and a second output module 520. The second acquisition module 320 is configured to acquire at least one second sleep characteristic data item representing the user's sleep state. The second processing module 420 is configured to determine a second sleep pattern associated with the user in response to the at least one second sleep characteristic data item acquired from the second acquisition module 320; compare the difference between the first sleep pattern and the second sleep pattern; and generate updated information about the sleep state metric of the first sleep monitor 100. The second output module 520 is configured to output the second sleep pattern and the updated information about the sleep state metric of the first sleep monitor 100.

[0078] The first output module 510 and the second output module 520 of the present invention can both be display components, wired or wireless communication ports, etc.

[0079] Specifically, the second acquisition module 320 (e.g., an electrode) of the second sleep monitor 200 is connected to the user's forehead to collect the user's EEG signals, EOG signals, and EMG signals. The second acquisition module 320 sends the user's EEG signals, EOG signals, and EMG signals to the second processing module 420. The second processing module 420 analyzes and compares the pre-processed EEG data with the sleep data model pre-stored in the connected database 700 to determine the user's sleep pattern or sleep quality. The second output module 520 outputs the sleep pattern or sleep quality to the user's terminal 600 or displays it through the second output module 520.

[0080] Generally speaking, sleep monitoring devices such as the second sleep monitor 200 are mostly devices that use bioelectric signals (such as EEG signals) for sleep monitoring, and are mostly deployed in hospitals, high-end clinics, and other places. Since determining the user's sleep state based on brain waves is a golden rule generally recognized by the scientific community, one of the significant advantages of medical-grade sleep monitoring devices is that they have high detection accuracy and precision, and are often used to accurately assess the sleep state of the subject. However, their disadvantage is that they require users to go to designated locations from time to time to receive testing and sleep treatment, which is very cumbersome and inconvenient, especially for some users with limited mobility. This not only consumes a lot of users' time and energy, but more importantly, the high cost of purchasing and using the in-hospital sleep monitoring and treatment equipment itself imposes high treatment expenses on users, increasing the burden on users. Therefore, how to make portable wearable devices replace non-portable high-precision sleep monitoring devices to monitor sleep and obtain uniform and accurate monitoring results is a problem that needs to be solved.

[0081] According to a preferred embodiment, the second sleep monitor 200 determines, based on time, a first sleep pattern and a second sleep pattern that are in the same sleep cycle. If the first sleep pattern and the second sleep pattern are determined to be in the same sleep cycle, the difference between the first sleep pattern and the second sleep pattern is compared. When there is direct or indirect interaction between the second sleep monitor 200 and the first sleep monitor 100, the second sleep monitor 200 receives the sleep state metric from the first sleep monitor 100. The second sleep monitor 200 adjusts the update information of the sleep state metric of the first sleep monitor 100 based on the second sleep pattern as the monitoring result that the first sleep monitor 100 should first determine.

[0082] Specifically, when the user is asleep, the first sleep monitor 100 and the second sleep monitor 200 are activated simultaneously and monitor the user's sleep pattern. After the user's sleep pattern is monitored, the first sleep monitor 100 and the second sleep monitor 200 respectively confirm the first sleep pattern and the second sleep pattern. In the case of direct interaction between the two, the first sleep monitor 100 sends the sleep pattern and its sleep state metric to the second sleep monitor 200. The second sleep monitor 200 compares the first sleep pattern and the second sleep pattern and their changes within the same sleep cycle to identify the differences between the two. The second sleep monitor 200 adjusts the sleep state metric of the first sleep monitor 100 based on the second sleep pattern as the correct monitoring result, so that the first sleep monitor 100 analyzes the first sleep characteristic data based on the new sleep state metric and obtains the same monitoring results as the second sleep monitor 200.

[0083] In order to improve the accuracy of the sleep state metric, the second sleep monitor 200 selects the difference between the first sleep pattern and the second sleep pattern of multiple sleep cycles to generate updated information for the sleep state metric of the first sleep monitor 100. According to a preferred embodiment, the updated information for the sleep state metric of the first sleep monitor 100 includes one of replacement information for the sleep state metric and an adjusted difference for the sleep state metric. The replacement information for the sleep state metric refers to a new sleep state metric that can replace the old sleep state metric, and belongs to the updated sleep state metric. The adjusted difference for the sleep state metric refers to the difference by which each sleep state metric should be adjusted. After the old sleep state metric is adjusted according to the adjusted difference, the new sleep state metric is formed to monitor and evaluate the first sleep characteristic data, and confirm that the first sleep pattern and the second sleep pattern are the same or close to the same.

[0084] Preferably, the first sleep monitor 100 and the second sleep monitor 200 simultaneously monitor a complete sleep cycle of the user or multiple sleep cycles. Monitoring multiple sleep cycles can reduce the difference between the first sleep pattern and the second sleep pattern caused by errors, and more objectively obtain data on the difference between the first sleep pattern and the second sleep pattern, thereby making the calibrated sleep state measurement indicator more accurate, and ensuring that the first sleep pattern determined by the first sleep monitor 100 is accurate each time.

[0085] The second sleep monitor 200 sends the updated information of the sleep state metric directly to the first sleep monitor 100, or indirectly to the first sleep monitor 100 through the terminal 600. The first sleep monitor 100 updates the sleep state metric based on the received updated information of the sleep state metric to improve the accuracy of the monitoring result of the first sleep mode.

[0086] Preferably, the encoding program for generating updated information of the sleep state metric can be set based on a preset algorithm or machine learning model, or can be set by medical staff through the terminal 600.

[0087] As described above, the present invention achieves the goal of improving the precision of sleep monitoring results from portable wearable devices, enabling them to accurately identify sleep patterns for users at home. Users only need to regularly or irregularly bring their first sleep monitor 100 to a hospital for calibration or correction of sleep state metrics with their second sleep monitor 200, enabling the first sleep monitor 100 to accurately identify their first sleep pattern. However, simply improving the accuracy of sleep pattern monitoring by portable wearable devices is not sufficient to provide users with effective supplemental sleep treatment options.

[0088] In order to enable users to obtain auxiliary treatment plans and implement them to improve sleep quality or avoid dangerous situations when their sleep patterns are accurately confirmed, such as Figure 1As shown, the system of the present invention also requires a terminal 600 and a sleep intervention device. The terminal 600 can also provide data analysis functions for the first sleep monitor 100 and the second sleep monitor 200, thereby replacing the first processing module 410 and the second processing module 420. For example, when the terminal 600 pre-stores and runs a coding program for confirming the first sleep mode, a coding program for the second sleep mode, and a coding program for analyzing the updated information of the sleep state measurement index, the first sleep monitor 100 and the second sleep monitor 200 only need to send the collected first sleep characteristic data and the second sleep characteristic data to the terminal 600 respectively to perform the sleep mode confirmation step. The first sleep monitor 100 receives the updated information of the sleep state measurement index fed back by the terminal 600 to update the sleep state measurement index. This not only simplifies the data processing volume of the first sleep monitor 100 and the second sleep monitor 200, but also reduces the hardware requirements of the first sleep monitor 100 and the second sleep monitor 200, thereby being applicable to the modification of sleep state measurement indicators of portable wearable devices of more types, specifications, and produced by different manufacturers, thereby reducing the amount of money users spend on purchasing the first sleep monitor 100 for sleep monitoring.

[0089] According to a preferred embodiment, Figure 3 As shown, the first sleep monitor 100 and the second sleep monitor 200 are connected to the terminal 600 in a wired and / or wireless manner. The wired manner is connected via a data cable, and the wireless manner is connected via a communication port such as a Bluetooth communication component, an infrared communication component, or a WiFi communication component. When the terminal 600 is connected to the first sleep monitor 100 for independent communication, the terminal 600 retrieves the corresponding auxiliary treatment plan from the database 700 based on the received first sleep pattern, such as Figure 3 When the terminal 600 is in communication with the second sleep monitor 200 , the terminal 600 retrieves the corresponding auxiliary treatment plan from the database 700 based on the received second sleep pattern.

[0090] According to a preferred embodiment, upon receiving the first sleep pattern sent by the first sleep monitor 100, the terminal 600 generates sleep intervention data based on the auxiliary treatment plan and the first sleep pattern, so that the sleep intervention device connected to the terminal 600 can perform sleep intervention actions on the user based on the sleep intervention data.

[0091] When the first sleep monitor 100 is communicatively connected to the sleep intervention device, the first sleep monitor 100 sends corresponding instruction information to the sleep intervention device based on the user's first sleep pattern and auxiliary treatment plan while the user is in a sleeping state, so that the sleep intervention device implements a sleep intervention operation based on the received instruction information.

[0092] According to a preferred embodiment, low-frequency electromagnetic stimulation and digital frequency synthesis of bio-waves can be used to act on the subject to achieve the effect of sleep intervention. Specifically, for example, when the portable first sleep monitor 100 determines that the subject has entered a light sleep stage, a handheld or head-mounted portable sleep intervention device can be used to apply a first frequency magnetic field and / or electric field to the subject's head or hand to accelerate the subject's sleep process. Alternatively, when the portable first sleep monitor 100 determines that the subject has entered a deep sleep stage, a handheld or head-mounted portable sleep intervention device can be used to apply a second frequency magnetic field and / or electric field to the subject's head or hand to prolong the deep sleep time. In view of the different manifestations of brain waves and other physiological indicators in different sleep states, the auxiliary treatment plans corresponding to each sleep stage have different configuration parameters, such as current / magnetic field strength, frequency and duration, etc.

[0093] As described above, the present invention takes into account the inherent defects of most portable first sleep monitors when used at home, and utilizes a medical-grade second sleep monitor with high precision and accuracy to calibrate the sleep pattern determined by the first sleep monitor 100. For example, one or more of the sleep quality index, sleep efficiency, sleep latency, sleep fragmentation, and / or other metrics in the sleep state data are corrected to provide the user with an accurate and reliable sleep pattern and evaluation results. The present invention utilizes a medical-grade second sleep monitor 200 to accurately calibrate the sleep state measurement indicators of the portable first sleep monitor 100, which is conducive to obtaining an accurate sleep pattern, so that the user's therapist can be provided with an appropriate auxiliary treatment plan. An auxiliary treatment plan is, for example, to provide an appropriate time-varying magnetic field or electric field.

[0094] Preferably, if the first sleep monitor 100 and the second sleep monitor 200 can communicate directly and the data information received from each other can be directly read, the first sleep monitor 100 directly sends information including its own sleep state metric and the first sleep pattern to the second sleep monitor 200. If a program for calibrating the sleep state metric is stored and can be executed, the second sleep monitor 200 can directly calibrate or correct the sleep state metric of the first sleep monitor 100 based on its own second sleep pattern and first sleep pattern.

[0095] The present invention updates the sleep state measurement index of the first sleep monitor 100 by correction or calibration, so that the portable first sleep monitor 100 can be calibrated regularly or irregularly by the second sleep monitor 200 or the terminal 600 to accurately obtain the user's first sleep pattern. Furthermore, the user can obtain accurate sleep pattern information without having to purchase a medical-grade second sleep monitor, saving the cost of equipment required for sleep monitoring and reducing the need for users to frequently travel to and from hospitals and medical institutions. The user can use the calibrated first sleep monitor 100 to obtain an accurate first sleep pattern at home, providing good basic information for the accurate operation of sleep intervention equipment.

[0096] Example 2

[0097] This embodiment is a further improvement of embodiment 1, and repeated contents will not be repeated here.

[0098] The present invention provides a healthy sleep management method from a second aspect, such as Figure 4 As shown, the method includes:

[0099] S101: The first sleep monitor 100 collects at least one first sleep characteristic data related to time of the user in a sleeping state and determines a first sleep pattern;

[0100] S102: The second sleep monitor 200 collects at least one second sleep characteristic data related to time of the user in the sleep state and determines a second sleep pattern.

[0101] S103: Compare the difference between the first sleep mode and the second sleep mode and output updated information of the sleep state metric of the first sleep monitor 100,

[0102] S104: The first sleep monitor 100 can modify the monitoring result of the first sleep mode according to the updated information of the sleep state metric.

[0103] S105 : When the second sleep monitor 200 or the first sleep monitor 100 is connected to the terminal 600 in a wired and / or wireless manner, the terminal 600 retrieves a corresponding auxiliary treatment plan from the database 700 based on the received second sleep pattern.

[0104] According to a preferred embodiment, the method further includes: the first sleep monitor 100 updating the sleep state metric based on the received update information of the sleep state metric to improve the accuracy of the monitoring result of the first sleep mode.

[0105] Example 3

[0106] This embodiment is a further improvement of embodiment 1, and repeated contents will not be repeated here.

[0107] This embodiment provides a sleep assistance system and an application method thereof, aiming to solve at least one or more technical problems existing in the prior art.

[0108] To achieve the above object, the present invention provides a system for assisting sleep, such as Figure 1 As shown, a first sleep monitor 100 and a second sleep monitor 200 are included, which allow interaction with one or more sleep state metrics associated with the subject. In particular, the sleep assistance mode of the present invention can be to help the user fall asleep, promote deep sleep and / or prolong it, and promote the transition between light sleep and deep sleep.

[0109] The first sleep monitor 100 is configured to determine a first sleep pattern based on one or more physiological characteristic data associated with the subject's sleep duration, and can provide a variable magnetic field / electric field associated with the subject's sleep time or frequency to an actionable target point of the subject.

[0110] The second sleep monitor 200 is configured to determine a second sleep pattern that matches the first sleep pattern based on one or more physiological characteristic data associated with the sleep duration of the subject.

[0111] In the second sleep mode, the second sleep monitor 200 can determine a third sleep mode based on one or more bioelectric signal data associated with the subject's sleep duration, and modify at least one sleep state metric included in the first sleep mode based on the third sleep mode.

[0112] The second sleep monitor 200 can provide one or more auxiliary treatment plans related to the user's sleep stage to the first sleep monitor 100 according to one or more sleep state metrics related to the first sleep pattern corrected based on the third sleep pattern.

[0113] The first sleep monitor 100 can initiate at least one auxiliary treatment plan associated with the user's sleep stage determined according to one or more sleep state metrics related to the first sleep pattern corrected based on the third sleep pattern during the determined one or more sleep stages.

[0114] Preferably, the step of determining the sleep pattern based on one or more physiological characteristic data associated with the subject's sleep time or frequency includes:

[0115] Processing a data waveform of one or more physiological characteristic data into a plurality of segmented waveforms;

[0116] Extracting one or more physiological characteristic data from each segmented waveform;

[0117] Classifying the user's sleep stage based on one or more physiological characteristic data in each segmented waveform;

[0118] The sleep state sum of the user is obtained based on the classified sleep stages to determine the sleep pattern.

[0119] Preferably, the physiological characteristic data includes body temperature, movement, heart rhythm and / or respiratory rate.

[0120] Preferably, the bioelectric signal data includes electroencephalogram (EEG) signals, electrooculogram (EOG) signals, electromyography (EMG) signals and / or electrocardiogram (ECG) signals.

[0121] Preferably, the present invention further provides an application method based on the above-mentioned sleep assistance system, comprising:

[0122] S201 : Determine, by a first sleep monitor 100 , a first sleep pattern corresponding to one or more physiological characteristic data associated with a subject's sleep time or frequency.

[0123] S202 : Determine, by the second sleep monitor 200 , at least one second sleep pattern that matches the first sleep pattern and corresponds to one or more physiological characteristic data associated with the subject's sleep time or frequency.

[0124] S203 : Based on the second sleep pattern, the second sleep monitor 200 determines a third sleep pattern corresponding to one or more bioelectric signal data associated with the subject's sleep time or frequency.

[0125] S204 : The second sleep monitor 200 corrects one or more sleep state metrics included in the first sleep pattern determined by the first sleep monitor 100 based on the third sleep pattern.

[0126] Preferably, the application method of the sleep assistance system according to the present invention further includes:

[0127] The first sleep monitor 100 initiates at least one auxiliary therapy program associated with the user's sleep stage determined according to one or more sleep state metrics related to the first sleep pattern corrected based on the third sleep pattern during the determined one or more sleep stages.

[0128] Example 4

[0129] This embodiment is a further improvement of embodiment 1, and repeated contents will not be repeated here.

[0130] This embodiment provides a sleep-assisted therapy terminal. When a user is in a sleeping state, the terminal 600 is in communication connection with the first sleep monitor 100 and the second sleep monitor 200 .

[0131] Terminal 600 is configured as follows:

[0132] S301: receiving update information of the sleep state metric of the first sleep monitor 100 sent by the second sleep monitor 200;

[0133] S302: regularly calibrating the sleep state metric of the first sleep monitor 100 based on the update information of the sleep state metric of the first sleep monitor 100;

[0134] S303 : Receive the first sleep pattern sent by the first sleep monitor 100 and retrieve the corresponding auxiliary treatment plan from the database 700 .

[0135] The terminal 600 includes: one or more processors, a memory, and a communication bus at least for connecting the processors and the memory.

[0136] The memory is used to store one or more computer programs. When the one or more computer programs are executed by one or more processors, the one or more processors implement the application method of the sleep assistance system of the present invention.

[0137] According to a preferred embodiment, the processor includes but is not limited to a CPU (Central Processing Unit), an MPU (Micro Processor Unit), an MCU (Micro Control Unit), and a SOC (System on Chip).

[0138] According to a preferred embodiment, the memory includes but is not limited to volatile memory (such as DRAM or SRAM) and non-volatile memory (such as FLASH, optical disk, floppy disk and mechanical hard disk, etc.).

[0139] According to a preferred embodiment, the communication bus includes but is not limited to an Industry Standard Architecture bus, a Micro Channel Architecture bus, an Enhanced ISA bus, a Video Electronics Standards Association local bus, and a Peripheral Component Interconnect bus.

[0140] This embodiment further provides a storage medium containing computer-executable instructions. When the computer-executable instructions are executed by a computer processor, they are used to execute the execution steps of the sleep-assisted therapy terminal involved in the present invention.

[0141] According to a preferred embodiment, the computer storage medium of this embodiment can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. Computer-readable storage media include, but are not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination thereof.

[0142] According to a preferred embodiment, more specific examples of computer-readable storage media include: an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0143] According to a preferred embodiment, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0144] According to a preferred embodiment, the program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable or RF, etc., or any suitable combination of the above.

[0145] According to a preferred embodiment, the computer program code for performing the operation of the embodiment of the present invention can be written in one or more programming languages ​​or a combination thereof, and the programming language includes an object-oriented programming language, such as python, Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0146] It should be noted that the above-mentioned specific embodiments are exemplary, and those skilled in the art can come up with various solutions inspired by the disclosure of the present invention, and these solutions also fall within the scope of the disclosure of the present invention and fall within the scope of protection of the present invention. Those skilled in the art should understand that the present invention specification and its drawings are illustrative and do not constitute a limitation on the claims. The scope of protection of the present invention is defined by the claims and their equivalents. The present invention specification contains multiple inventive concepts, such as "preferably", "according to a preferred embodiment" or "optionally", which means that the corresponding paragraph discloses an independent concept, and the applicant reserves the right to file a divisional application based on each inventive concept.

Claims

1. A healthy sleep management system, characterized in that: include: A portable wearable first sleep monitor that is brought to the hospital regularly or irregularly collects at least one physiological characteristic data of the user related to time during sleep as first sleep characteristic data and determines a first sleep pattern; A second sleep monitor deployed in the hospital is activated simultaneously with the first sleep monitor during sleep and simultaneously monitors the sleep pattern of the user. The second sleep monitor collects at least one time-related bioelectrical signal data of the user that is different from the first sleep characteristic data as second sleep characteristic data and determines a second sleep pattern. The second sleep pattern is compared with the first sleep pattern within the same sleep cycle and the sleep state metric of the first sleep monitor is adjusted based on the second sleep pattern as the correct monitoring result. Updated information of the sleep state metric of the first sleep monitor is generated, so that the first sleep monitor can correct the monitoring result of the first sleep pattern based on the updated information of the sleep state metric. The update information of the sleep state metric indicator of the first sleep monitor includes one of replacement information of the sleep state metric indicator and an adjustment difference value of the sleep state metric indicator; When the analysis unit of the first sleep monitor determines that the user's sleep state or sleep quality is poor or needs to be adjusted based on one or more sleep characteristic data of the user acquired by the first acquisition module during sleep, the analysis unit provides a time-varying magnetic field to the user's body through the magnetic field device to change the user's sleep pattern. The time-varying magnetic field provided by the magnetic field device by the analysis unit is configured in association with the user's sleep pattern or sleep quality. When the first sleep monitor and the second sleep monitor communicate directly and the data information received from each other is directly read, the first sleep monitor directly sends information including its own sleep state measurement index and the first sleep pattern to the second sleep monitor. When a program for calibrating the sleep state measurement index is stored and can be executed, the second sleep monitor directly calibrates or corrects the sleep state measurement index of the first sleep monitor based on its own second sleep pattern and the first sleep pattern.

2. The healthy sleep management system according to claim 1, characterized in that: The first sleep monitor (100) and the second sleep monitor (200) are respectively connected to the terminal (600) in a wired and / or wireless manner. The terminal (600) retrieves a corresponding auxiliary treatment plan from a database (700) based on the received second sleep pattern.

3. The healthy sleep management system according to claim 2, characterized in that: The first sleep monitor (100) updates the sleep state metric based on the received update information of the sleep state metric to improve the accuracy of the monitoring result of the first sleep mode.

4. The healthy sleep management system according to any one of claims 1 to 3, characterized in that: Upon receiving the first sleep pattern transmitted by the first sleep monitor (100), the terminal (600) generates sleep intervention data based on the auxiliary treatment plan and the first sleep pattern, so that a sleep intervention device connected to the terminal (600) can perform sleep intervention actions on the user based on the sleep intervention data.

5. The healthy sleep management system according to claim 4, characterized in that: The first sleep monitor (100) collects the first sleep characteristic data of the user in a wearable manner, The second sleep monitor (200) collects the second sleep characteristic data of the user in a manner of collecting the user's brain wave data.

6. The healthy sleep management system according to claim 4, characterized in that: The second sleep monitor (200) determines the first sleep pattern and the second sleep pattern in the same sleep cycle based on time and compares the difference between the first sleep pattern and the second sleep pattern, The second sleep monitor (200) receives the sleep state metric of the first sleep monitor (100), The second sleep monitor (200) adjusts update information of the sleep state metric of the first sleep monitor (100) based on the second sleep mode as a monitoring result that the first sleep monitor (100) should determine.

7. A healthy sleep management method, characterized in that: include: A portable wearable first sleep monitor brought to the hospital regularly or irregularly collects at least one physiological characteristic data of the user related to time during sleep as first sleep characteristic data and determines a first sleep pattern; A second sleep monitor deployed in the hospital is activated simultaneously with the first sleep monitor during sleep and simultaneously monitors the sleep pattern of the user. The second sleep monitor collects at least one time-related bioelectrical signal data of the user that is different from the first sleep characteristic data as second sleep characteristic data and determines a second sleep pattern. The second sleep pattern and the second sleep pattern within the same sleep cycle are compared and the sleep state metric of the first sleep monitor is adjusted based on the second sleep pattern as the correct monitoring result. Updated information of the sleep state metric of the first sleep monitor is output, so that the first sleep monitor can correct the monitoring result of the first sleep pattern based on the updated information of the sleep state metric. The update information of the sleep state metric indicator of the first sleep monitor includes one of replacement information of the sleep state metric indicator and an adjustment difference value of the sleep state metric indicator; When the analysis unit of the first sleep monitor determines that the user's sleep state or sleep quality is poor or needs to be adjusted based on one or more sleep characteristic data of the user acquired by the first acquisition module during sleep, the analysis unit provides a time-varying magnetic field to the user's body through the magnetic field device to change the user's sleep pattern. The time-varying magnetic field provided by the magnetic field device by the analysis unit is configured in association with the user's sleep pattern or sleep quality. When the first sleep monitor and the second sleep monitor communicate directly and the data information received from each other is directly read, the first sleep monitor directly sends information including its own sleep state measurement index and the first sleep pattern to the second sleep monitor. When a program for calibrating the sleep state measurement index is stored and can be executed, the second sleep monitor directly calibrates or corrects the sleep state measurement index of the first sleep monitor based on its own second sleep pattern and the first sleep pattern.

8. The healthy sleep management method according to claim 7, characterized in that: The method further includes: when the second sleep monitor (200) is connected to the terminal (600) in a wired and / or wireless manner, the terminal (600) retrieves a corresponding auxiliary treatment plan from a database (700) based on the received second sleep pattern.

9. A sleep-aiding treatment terminal, characterized in that: When the user is in a sleeping state, the terminal is connected to a first portable wearable sleep monitor brought to the hospital regularly or irregularly and a second sleep monitor deployed in the hospital; the terminal is configured to: receiving update information of the sleep state metric of the first sleep monitor sent by the second sleep monitor; the update information of the sleep state metric of the first sleep monitor includes one of replacement information of the sleep state metric and an adjustment difference value of the sleep state metric; regularly calibrating the sleep state metric of the first sleep monitor based on updated information of the sleep state metric of the first sleep monitor; receiving a first sleep pattern sent by a first sleep monitor and retrieving a corresponding auxiliary treatment plan from a database; wherein, The first sleep monitor collects at least one physiological characteristic data of the user related to time in a sleeping state as first sleep characteristic data and determines a first sleep pattern; The second sleep monitor is activated simultaneously with the first sleep monitor in the sleep state and monitors the sleep pattern respectively, collects at least one time-related bioelectric signal data of the user that is different from the first sleep characteristic data as the second sleep characteristic data, determines the second sleep pattern, compares the difference between the first sleep pattern and the second sleep pattern within the same sleep cycle, and adjusts the sleep state metric of the first sleep monitor based on the second sleep pattern as the correct monitoring result, thereby generating updated information on the sleep state metric of the first sleep monitor; When the analysis unit of the first sleep monitor determines that the user's sleep state or sleep quality is poor or needs to be adjusted based on one or more sleep characteristic data of the user acquired by the first acquisition module during sleep, the analysis unit provides a time-varying magnetic field to the user's body through the magnetic field device to change the user's sleep pattern. The time-varying magnetic field provided by the magnetic field device by the analysis unit is configured in association with the user's sleep pattern or sleep quality. When the first sleep monitor and the second sleep monitor communicate directly and the data information received from each other is directly read, the first sleep monitor directly sends information including its own sleep state measurement index and the first sleep pattern to the second sleep monitor. When a program for calibrating the sleep state measurement index is stored and can be executed, the second sleep monitor directly calibrates or corrects the sleep state measurement index of the first sleep monitor based on its own second sleep pattern and the first sleep pattern.

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