A sleep assisting system and its application method

Abstract

The present invention relates to a system for assisting sleep and an application method thereof, wherein the system includes a first sleep monitor and a second sleep monitor that allow interaction with one or more sleep state measurement indicators associated with a subject, wherein the first sleep monitor 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 of the subject; the second sleep monitor is configured to determine a second sleep pattern matching the first sleep pattern based on one or more physiological characteristic data associated with the subject's sleep duration; wherein, in the second sleep mode, the second sleep monitor can determine a third sleep pattern based on one or more bioelectric signal data associated with the subject's sleep duration, and correct at least one sleep state measurement indicator contained in the first sleep pattern based on the third sleep pattern.

Description

Technical Field

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

[0002] Sleep apnea syndrome (SAS) is an example of a sleep disorder characterized by repeated pauses in breathing and / or hypopnea, interrupted sleep, and other symptoms that may last for seconds or even minutes. When breathing stops, carbon dioxide accumulates in the body, and receptors in the bloodstream detect very high levels of carbon dioxide, sending a signal to the brain to wake the person up so that they can breathe and then fall asleep again. This type of event may occur several times throughout the night and significantly reduce sleep quality, which may also cause various risks and gradually become a major factor in causing various health problems. People with sleep apnea syndrome (SAS) experience a full night's sleep, but they still feel that they have not received enough and proper rest.

[0003] Numerous studies have shown a significant link between sleep problems and a variety of serious health conditions, including depression, heart disease, obesity, and a shorter life expectancy. Missing just one or a few hours of sleep a night can have a significant negative impact on athletic performance, learning skills, and mood. On the other hand, long sleepers, who sleep for nine hours or more, are also at increased risk for coronary heart disease and stroke.

[0004] To understand the complex interplay between sleep and waking, researchers are continuously studying various physiological conditions during sleep. Sleep monitoring is gaining attention for many reasons, not the least of which is its ability to provide actual data related to a user's sleep, such as sleep duration, depth, time to sleep onset, and wakefulness. With this data, patients with sleep disorders have a basis for seeking to improve their sleep quality.

[0005] CN104224132B discloses a sleep monitoring device, including a detection module, a processing module electrically connected to the detection module, and an output module electrically connected to the processing module, wherein the detection module is used to collect physiological characteristic signals representing the user's sleep state, and the physiological characteristic signals include one or more of a heart rate characteristic signal for representing the heart rate characteristics of the subject and a breathing characteristic signal for representing the breathing characteristics of the subject; the processing module is used to process the physiological characteristic signals from the detection module to obtain a comprehensive sleep assessment result of the subject; and the output module is used to output the comprehensive sleep assessment result from the processing module.

[0006] There are several devices on the market for monitoring sleep efficiency or sleep quality, such as portable home sleep monitors and medical-grade sleep monitors. Medical-grade sleep monitors (such as polysomnography) are currently the gold standard for sleep research and are often used to accurately assess the subject's sleep state, such as diagnosing sleep disorders. Polysomnography involves monitoring many different physiological signals, such as heart rate variability (HRV), respiration, EEG, EMG, and EOG. However, biological signals such as brain waves are sometimes extremely weak, and the equipment that records brain wave signals must be extremely accurate. Therefore, existing medical-grade sleep monitoring equipment is usually set up in health service institutions such as hospitals and clinics, and must be used under the supervision of experts, making it inconvenient for home use.

[0007] Portable sleep monitoring products are usually wearable, and most are based on accelerometers. These products mainly use accelerometers to obtain the user's movement data during sleep, and analyze and evaluate the user's sleep state based on this data. However, the limb movement data generated by the accelerometer is not directly related to the user's sleep state, which often leads to inaccurate final sleep state assessments: for example, the user has fallen asleep, but due to certain involuntary reflexes of the human body during sleep, the user has body movements. At this time, the sleep monitoring device may determine that the user has not fallen asleep based on the body movement data provided by the accelerometer. Therefore, these devices are usually unable to accurately measure sleep quality and sleep efficiency.

[0008] Therefore, it is necessary to provide a sleep monitoring device / system that has accurate measurement results and can correctly guide or assist users in monitoring and evaluating their sleep status at home and improving their sleep quality.

[0009] 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

[0010] In view of the deficiencies of the prior art, the present invention provides a sleep assisting system and an application method thereof, aiming to solve at least one or more technical problems existing in the prior art.

[0011] To achieve the above object, the present invention provides a system for assisting sleep, comprising a first sleep monitor and a second sleep monitor that allow interaction with one or more sleep state metrics associated with a subject, wherein:

[0012] a first sleep monitor configured to determine a first sleep pattern based on one or more physiological characteristic data associated with the subject's sleep duration, and capable of providing a variable magnetic / electric field associated with the subject's sleep time or frequency to an actionable target site on the subject;

[0013] a second sleep monitor configured to determine a second sleep pattern that matches the first sleep pattern based on one or more physiological characteristic data associated with the subject's sleep duration;

[0014] Among them, in the second sleep mode, the second sleep monitor can determine the third sleep mode based on one or more bioelectric signal data associated with the subject's sleep duration, and correct at least one sleep state measurement indicator included in the first sleep mode based on the third sleep mode.

[0015] Preferably, the sleep assisting system of the present invention further comprises:

[0016] The second sleep monitor can provide one or more auxiliary treatment plans related to the user's sleep stage to the first sleep monitor according to the one or more sleep state metrics related to the first sleep pattern corrected based on the third sleep pattern.

[0017] Preferably, the sleep assisting system of the present invention further comprises:

[0018] The first sleep monitor can initiate at least one auxiliary therapy program associated with the user's sleep stage determined according to one or more sleep state metrics associated with the first sleep pattern modified based on the third sleep pattern during the determined one or more sleep stages.

[0019] 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:

[0020] Processing a data waveform of one or more physiological characteristic data into a plurality of segmented waveforms;

[0021] Extracting one or more physiological characteristic data from each segmented waveform;

[0022] Classifying the user's sleep stage based on one or more physiological characteristic data in each segmented waveform;

[0023] The sleep state sum of the user is obtained based on the classified sleep stages to determine the sleep pattern.

[0024] Preferably, the physiological characteristic data includes body temperature, movement, heart rhythm and / or respiratory rate.

[0025] Preferably, the bioelectric signal data includes electroencephalogram (EEG) signals, electrooculogram (EOG) signals, electromyography (EMG) signals and / or electrocardiogram (ECG) signals.

[0026] Preferably, the present invention relates to an application method based on the above-mentioned sleep assistance system, comprising:

[0027] S101: Determine, by a first sleep monitor, a first sleep pattern corresponding to one or more physiological characteristic data associated with a subject's sleep time or frequency.

[0028] S102: Determine, by a second sleep monitor, 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.

[0029] S103: Based on the second sleep pattern, the second sleep monitor determines a third sleep pattern corresponding to one or more bioelectric signal data associated with the subject's sleep time or frequency.

[0030] S104: The second sleep monitor corrects one or more sleep state metrics included in the first sleep pattern determined by the first sleep monitor based on the third sleep pattern.

[0031] Preferably, the application method of the sleep assistance system according to the present invention further includes:

[0032] The first sleep monitor initiates at least one auxiliary therapy program associated with the user's sleep stage determined according to one or more sleep state metrics associated with the first sleep pattern modified based on the third sleep pattern during the determined one or more sleep stages.

[0033] Preferably, the present invention further relates to an electronic device, comprising:

[0034] one or more processors;

[0035] a memory for storing one or more computer programs;

[0036] When 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.

[0037] Preferably, the present invention further relates to a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to execute the application method of the sleep assistance system of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 1 is a schematic structural diagram of a sleep assistance system according to a preferred embodiment of the present invention;

[0039] Figure 2 The figure is a flow chart of a sleep assisting method according to a preferred embodiment of the present invention.

[0040] Reference Signs List

[0041] 100: first sleep monitor; 200: second sleep monitor. DETAILED DESCRIPTION

[0042] The following is a detailed description with reference to the accompanying drawings.

[0043] Various embodiments and / or implementations herein relate to assistance / monitoring systems and methods thereof that utilize user data, such as heart rate, body temperature, respiratory waveform, etc., to monitor and quantify the user's sleep quality.

[0044] Example 1

[0045] Specifically, the present invention provides a system for assisting sleep, such as Figure 1 Shown, including:

[0046] The first sleep monitor 100 is operably attached to a user and configured to obtain one or more physiological characteristic data of the user in a sleeping state. Further, the first sleep monitor 100 may determine a first sleep pattern associated with the user based on the one or more physiological characteristic data.

[0047] The second sleep monitor 200 is operably attached to the user and is configured to obtain one or more physiological characteristic data and / or bioelectrical signal data of the user while the user is asleep. Furthermore, the second sleep monitor 200 may determine a second sleep mode of the user based on the one or more physiological characteristic data and / or a third sleep mode of the user based on the bioelectrical signal data.

[0048] Furthermore, the second sleep monitor 200 can determine at least one sleep cycle based on the matching relationship between the first sleep pattern and the second sleep pattern with respect to at least one physiological characteristic data item. Specifically, the at least one sleep cycle is at least one sleep pattern that matches the first sleep pattern. In particular, within the determined sleep pattern, the second sleep monitor 200 can correct at least one sleep state metric associated with the first sleep pattern determined by the first sleep monitor 100 based on the determined third sleep pattern.

[0049] In particular, the sleep assistance described in the present invention may be to help the user fall asleep, help the user fall asleep in the deep sleep and / or prolong the deep sleep, and help the user transition between latent sleep and deep sleep.

[0050] According to a preferred embodiment, the physiological characteristic data may generally include data signals such as body temperature, movement, heart rhythm and respiratory rate, etc. In particular, the physiological characteristic data such as body temperature, movement, heart rhythm and respiratory rate are stored in a time- or frequency-dependent manner.

[0051] According to a preferred embodiment, the bioelectric signal data may generally include brain wave signals, electrooculogram signals, electromyogram signals, and electrocardiogram signals, etc. In particular, the bioelectric signal data such as brain wave signals, electrooculogram signals, electromyogram signals, and electrocardiogram signals are stored in relation to time or frequency.

[0052] Specifically, in the present invention, the first sleep monitor 100 can be a wearable sleep monitor. Specifically, the wearable sleep monitor can be in the form of a hand-held device, a wristwatch, a neck-wrap device, a head-clip device, and the like. In particular, in the present invention, the specific structure of the wearable sleep monitor 100 is not limited.

[0053] According to a preferred embodiment, since physiological changes during sleep are related to a person's sleep state, a typical sleep monitor can determine a person's sleep state based on physiological signals, such as body temperature, heart rate, and respiratory rate, as described 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 interruption and connection points between sleep stages, and sleep efficiency, among other factors.

[0054] According to a preferred embodiment, a wearable sleep monitor generally includes at least a data acquisition module and a signal processing module. Specifically, the data acquisition module is configured to collect one or more physiological characteristic data representing the user's sleep state. The signal processing module is electrically connected to the data acquisition module. The signal processing module is configured to analyze the one or more physiological characteristic data from the data acquisition module to determine the user's sleep state or sleep quality.

[0055] According to a preferred embodiment, the signal processing module may include a signal extraction unit, a signal analysis unit, and a storage unit. Specifically, the signal extraction unit may extract one or more physiological characteristic data from the acquisition module. The signal analysis unit may store the real-time physiological characteristic data in the storage unit and analyze the data to derive an evaluation result related to the subject's sleep state or sleep quality.

[0056] According to a preferred embodiment, a wearable / wornable sleep monitor may also include an output module. The output module may be used to output the sleep state assessment results from the signal processing module. Specifically, the output module may output the user's sleep state assessment results using any method capable of conveying information. For example, this may be through one or more of a display, vibration, sound / light, etc. Alternatively, the generated sleep state assessment results may be provided via an interface, such as a monitor, mobile device, laptop, desktop computer, wearable device, or home computing device.

[0057] In particular, the sleep state or sleep quality may include a sleep quality index, sleep cycles, total sleep time, sleep efficiency, sleep onset latency, sleep fragmentation, and / or other metrics. Furthermore, the sleep state or sleep quality evaluation results may be in the form of a chart, a curve, or text, or any combination thereof.

[0058] In particular, the acquisition module can be any device, wearable, sensor or other element configured to or capable of acquiring data about the user. The acquisition module can communicate directly with the user, or can acquire the user's information via indirect contact (such as video, IR, motion detector or other type of sensor).

[0059] According to a preferred embodiment, in the present invention, the acquisition module may be a sensor. Specifically, the acquisition module may include one or more of a temperature sensor, a heart rate sensor, a respiration sensor, and a motion sensor. Furthermore, the temperature sensor may be used to acquire a user's body temperature characteristic signal. The heart rate sensor may be used to acquire a user's heart rate characteristic signal. The respiration sensor may be used to acquire a user's respiratory rate characteristic signal. The motion sensor may be used to acquire a user's body movement characteristic signal.

[0060] According to a preferred embodiment, when the acquisition module is a heart rate sensor, the signal extraction unit can extract the heart rate characteristic signal from the heart rate sensor. The signal analysis unit can store the real-time heart rate characteristic signal in a storage unit and analyze it to obtain an evaluation result of the user's sleep state or sleep quality. Furthermore, the signal analysis unit can output the evaluation result of the user's sleep state or sleep quality to the user via an output module. 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.

[0061] According to a preferred embodiment, when the acquisition module is a temperature sensor, the signal extraction unit can extract a characteristic body temperature signal from the temperature sensor. The signal analysis unit can store the real-time characteristic body temperature signal in a storage unit and analyze it to obtain an evaluation result of the user's sleep state or sleep quality. Furthermore, the analysis unit can output the evaluation result of the user's sleep state or sleep quality to the user via an output module.

[0062] According to a preferred embodiment, when the acquisition module is a respiratory sensor, the signal extraction unit can extract a characteristic respiratory frequency signal from the respiratory sensor. The signal analysis unit can store the real-time characteristic respiratory frequency signal in a storage unit and analyze it to derive an evaluation result of the user's sleep state or sleep quality. Furthermore, the signal analysis unit can output the evaluation result of the user's sleep state or sleep quality to the user via an output module. In particular, the respiratory sensor can be one or more of a displacement sensor, a strain gauge sensor, and a photoplethysmography sensor.

[0063] 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.

[0064] According to a preferred embodiment, when the acquisition module is a motion sensor, the signal extraction unit 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. Furthermore, the signal analysis unit can store the real-time body motion characteristic signal in a storage unit and analyze it to obtain the evaluation result of the user's sleep state or sleep quality. Furthermore, the signal analysis unit can output the evaluation result of the user's sleep state or sleep quality to the user through the output module. 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.

[0065] According to a preferred embodiment, after the signal processing module obtains the evaluation results of the user's sleep state 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 / server through the output interface so that the user can obtain more comprehensive analysis and sleep guidance.

[0066] According to a preferred embodiment, the signal processing module can analyze and determine the user's sleep state or sleep quality based on multiple physiological characteristic data of the user. Specifically, the acquisition module can collect the user's body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal, and body movement characteristic signal, etc. separately or simultaneously. One or more extraction units of the signal processing module can extract and amplify the user's body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal and / or body movement characteristic signal. The signal analysis unit can calculate 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 movement characteristic signal from the extraction unit.

[0067] In an optional embodiment, the signal analysis unit 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 physiological characteristic data signals.

[0068] 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. Thereafter, a sleep quality index associated with the one or more physiological characteristic data signals or characteristic data signal change rates is calculated based on a preset weighted average algorithm.

[0069] Furthermore, the calculated sleep quality index can be compared with a preset quality threshold, and the user's sleep state 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 state or sleep quality is poor.

[0070] Alternatively, in an alternative embodiment, the user's physiological characteristic data, such as body temperature, movement, heart rate, and respiratory rate, can be specifically waveforms, such as body temperature waveforms, movement waveforms, heart rate waveforms, and respiratory waveforms. These waveforms can be measured and obtained by a wearable sleep monitor.

[0071] According to a preferred embodiment, after the signal extraction unit obtains these physiological characteristic data waveforms, the signal analysis unit can divide these characteristic data waveforms into several segmented waveforms. The signal analysis unit can extract characteristic data from these segmented waveforms, such as body temperature data, heart rate data, or respiratory data. Furthermore, the signal analysis unit can classify the user's sleep state or stage based on the characteristic data in these segmented waveforms. In particular, the signal analysis unit can classify the user's sleep state based on the characteristic data in the segmented waveforms through machine learning, predetermined threshold programming, or self-setting by medical personnel and / or other possible methods.

[0072] Specifically, the signal analysis unit may classify the user's sleep state into one or more stages of W, N1, N2, N3, and R. Furthermore, the signal analysis unit may analyze one or more categories of sleep stages to obtain the user's sleep state or sleep quality results. For example, the user's sleep state or sleep quality result may be the sum of the sleep quality indexes of each sleep stage. In addition, the evaluation result of the sleep state or sleep quality may also be determined based on one or more of the total sleep time, sleep efficiency, sleep onset latency, and sleep fragmentation.

[0073] According to a preferred embodiment of the present invention, the first sleep monitor 100 determines a first sleep pattern based on one or more physiological characteristic data of the user. Further, the first sleep pattern may include one or more of the user's sleep quality index, total sleep time, sleep efficiency, sleep onset latency, and sleep fragmentation.

[0074] According to a preferred embodiment, the wearable first 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 brainwaves, or a time-varying magnetic field pre-stored in a storage unit for generating corresponding brainwaves, to any applicable target point on the user's body. Specifically, the applicable target point on the user may be, for example, an acupuncture point on the human body.

[0075] Specifically, for example, when the signal analysis unit of the first sleep monitor 100 determines that the user's sleep state or sleep quality is poor or needs to be adjusted based on one or more physiological characteristic data of the user obtained by the acquisition module during the sleep process, it can provide a time-varying magnetic field to the user's body through the magnetic field unit. Furthermore, the time-varying magnetic field provided by the signal analysis unit through the magnetic field unit is configured in association with the user's sleep state or sleep quality. In other words, the time-varying magnetic field provided by the signal analysis unit through the magnetic field unit needs to be determined based on the difference between the user's sleep state or sleep quality and the ideal or expected sleep state. Alternatively, the signal analysis unit can output a pulse signal with a variable frequency through the magnetic field unit, thereby adjusting the coupling time of the time-varying magnetic field to the human body. In particular, the magnetic field unit is, for example, a magnetic coil.

[0076] In particular, since the human body cannot store external magnetic field energy, the magnetic stimulation effect is not a direct effect of the magnetic field, but a result of the action of electric current. The time-varying magnetic field will generate an electric field, and the magnitude of the induced electromotive force generated by it is proportional to the rate of change of the magnetic flux over time. The current generated by the electric field has a certain intensity and continuous action, which can effectively stimulate the nervous system in the same way as the current introduced into the human body through electrodes. In particular, after the electric field generated by the changing magnetic field acts on the human body, it will produce neurotransmitters related to deep sleep (such as inhibitory neurotransmitters), which can affect human sleep, such as accelerating sleep, promoting deep sleep or prolonging the duration of deep sleep.

[0077] According to a preferred embodiment of the present invention, the second sleep monitor 200 can be a polysomnogram used in hospitals or clinics. Specifically, the second sleep monitor 200 can determine the user's sleep pattern at least based on electroencephalogram (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.

[0078] Specifically, the acquisition module (e.g., electrode) of the second sleep monitor 200 is connected to the user's forehead to collect one or more of the user's EEG, EOG, and EMG signals. The acquisition module transmits the user's EEG, EOG, and / or EMG signals to the signal processing module, which then processes and transmits them to the control unit. Upon receiving these signal data, the control unit analyzes and compares them with the sleep data model pre-stored in the internal database to determine the user's sleep state or sleep quality.

[0079] On the other hand, the second sleep monitor 200 with bioelectrical signal detection capabilities typically also has the capability to independently analyze one or more physiological characteristic data of the user, including body temperature, movement, heart rate, and respiratory rate, to determine the user's sleep state or sleep quality. In particular, sleep state or sleep quality may include the sleep quality index, sleep cycles, total sleep time, sleep efficiency, sleep onset latency, sleep fragmentation, and / or other metrics as described above.

[0080] According to a preferred embodiment, in the present invention, the second sleep monitor 200 may determine the second sleep mode based on one or more physiological characteristic data of the user. Furthermore, the second sleep monitor 200 may also determine the third sleep mode based on one or more bioelectric signals of the user. Specifically, bioelectric signals include electroencephalogram (EEG) signals, electrooculogram (EOG) signals, electromyogram (EMG) signals, and electrocardiogram (ECG) signals. Furthermore, the second sleep mode and / or third sleep mode may include one or more of the user's sleep quality index, total sleep time, sleep efficiency, sleep onset latency, sleep fragmentation, and / or other metrics.

[0081] According to a preferred embodiment, the second sleep monitor 200 may include an acquisition module, a signal processing module, and an output module. Specifically, the acquisition module can be used to collect one or more physiological characteristic data and / or bioelectric signal data that characterize the user's sleep state. The signal processing module can be used to determine the user's sleep pattern based on the analysis of one or more physiological characteristic data and / or bioelectric signal data from the acquisition module to determine the user's sleep state or sleep quality. The output module can be used to output the sleep state evaluation result from the processing module. Similarly, the second sleep monitor 200 can include a system architecture that is the same or similar to the first sleep monitor 100, and the specific signal transmission and processing principles can refer to the first sleep monitor 100, and will not be elaborated on here.

[0082] Likewise, in the present invention, the second monitor may also be capable of providing a variable time-varying magnetic field / electric field to the subject.

[0083] Example 2

[0084] According to a preferred embodiment, in order to address the technical deficiencies of existing sleep monitoring systems / methods, especially portable sleep monitoring devices in situations where expensive medical-grade sleep monitoring equipment is unavailable, the present invention also provides an application method of a sleep assistance system, comprising:

[0085] S101 : Determine, by a first sleep monitor 100 , a first sleep pattern corresponding to at least one physiological characteristic data associated with a sleep duration of a subject.

[0086] S102: Determine, by the second sleep monitor 200 , a second sleep pattern corresponding to at least one physiological characteristic data related to the sleep duration of the subject.

[0087] S103 : In the second sleep mode, the second sleep monitor 200 determines a third sleep mode according to at least one bioelectric signal data item related to the sleep duration of the subject.

[0088] S104: Modify at least one sleep state measurement indicator included in the first sleep mode based on the third sleep mode.

[0089] Specifically, the second sleep pattern is fitted with at least one sleep curve included in the first sleep pattern determined by the first sleep monitor 100. Alternatively, the second sleep pattern includes at least one sleep cycle fitted with the first sleep pattern.

[0090] Typically, sleep monitoring devices such as the second sleep monitor 200 are high-precision monitoring instruments deployed in hospitals, high-end clinics, and other places. One of the significant advantages of this type of sleep monitoring equipment is its high detection precision and accuracy, and is often used to accurately assess the sleep state of the subject. However, its disadvantage is that it requires 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. As a result, it not only consumes the user's time and energy, but more importantly, the high equipment purchase and use costs of the in-hospital sleep monitoring and treatment equipment themselves give users higher treatment expenses, increasing the burden on users.

[0091] To this end, the market provides a large number of portable sleep monitors that can be used at home (such as the first sleep monitor 100). Such portable sleep monitors are lightweight and easy to wear, and can be flexibly used for sleep status monitoring in various sleeping situations. In particular, the data detection of body temperature, heart rate and respiratory rate, etc., provided by such sleep monitors can basically support the user's sleep quality monitoring at home, and the sleep assistance functions provided by such sleep monitors (such as applying electric field / magnetic field stimulation, generating sleep-related neurotransmitters or regulating related hormones, etc.) can also basically meet the user's daily sleep treatment needs.

[0092] However, compared to medical-grade sleep monitors such as the second monitor 200, portable sleep monitors have very limited detection precision and accuracy. One or more of the sleep cycles, sleep quality index, sleep efficiency, sleep onset latency, sleep fragmentation, and / or other metrics determined by these portable sleep monitors in relation to a user's sleep progress are likely to be inaccurate. Consequently, when a user is in a home sleep environment, these portable sleep monitors may provide sleep state assessment results with significant deviations. Furthermore, based on these erroneous sleep state assessment results, the sleep guidance suggestions and even the sleep assistance functions / measures provided by these portable sleep monitors are often inadequate. In such cases, the portable sleep monitors not only fail to provide the user with accurate assessment results, but also fail to guide the user into a desired sleep state through reasonable and effective means. Furthermore, the implementation of erroneous sleep guidance suggestions or assistance measures may worsen the user's poor sleep state, increase fatigue, and cause imbalances in their biorhythms, seriously impacting and endangering the user's physical and mental health.

[0093] In particular, considering the inherent defects of most portable sleep monitors when used at home, the present invention utilizes a high-precision and accurate medical-grade sleep monitor to correct the sleep pattern determined by the portable sleep monitor. While the portable sleep monitor is used to determine the user's sleep pattern, the medical-grade sleep monitor's independent physiological characteristic data monitoring device is used to determine at least one sleep pattern that fits the sleep curve determined by the portable sleep monitor. In addition, after determining a sleep pattern that has a high degree of fit with the sleep curve obtained by the portable sleep monitor, the user's sleep pattern is again determined using bioelectric signals (such as EEG signals) obtained by the medical-grade sleep monitor. Based on the sleep pattern determined by the bioelectric signals, the sleep pattern determined by the portable sleep monitor is corrected, such as correcting one or more of the sleep quality index, sleep efficiency, sleep onset latency, sleep fragmentation, and / or other metrics, to provide the user with accurate and reliable sleep state assessment results.

[0094] Furthermore, by verifying the sleep pattern determined by the portable sleep monitor with a medical-grade sleep monitor, it is possible not only to accurately determine whether the sleep pattern determined by the portable sleep monitor for home use is correct, but also to provide reasonable and effective sleep assistance measures based on the accurate determination of the sleep pattern, such as providing a time-varying magnetic field or electric field related to the user's sleep state.

[0095] Specifically, the subject is placed in a setting such as a hospital or a high-end clinic equipped with a medical-grade sleep monitor, and a portable sleep monitor (such as the first sleep monitor 100 described above) and a medical-grade sleep monitor (such as the second sleep monitor 200 described above) are respectively worn in place to establish a sleep monitoring connection with the subject. Preferably, the portable sleep monitor and the medical-grade sleep monitor establish signal communication so that they interact with each other to share system data. Furthermore, the subject's sleep pattern can be detected and determined by the portable sleep monitor and the medical-grade sleep monitor, respectively, wherein the medical-grade sleep monitor is used to determine at least one sleep pattern that fits the sleep curve determined by the portable sleep monitor. In particular, the sleep pattern determined by the medical-grade sleep monitor and the portable sleep monitor can be based on the same physiological characteristic data, and the total sleep duration, the start and end nodes and corresponding duration of each independent sleep stage, and the value or change rate of one or more sleep state data in each sleep stage determined by the two can be comparable.

[0096] Secondly, when the medical-grade sleep monitor determines at least one sleep pattern that fits the sleep curve determined by the portable sleep monitor, the medical-grade sleep monitor can determine / obtain at least one other sleep pattern related to the subject based on the acquired bioelectrical signals. In particular, given the excellent detection accuracy of the medical-grade sleep monitor, the controller can correct at least one evaluation indicator (such as sleep quality index, sleep efficiency, sleep onset latency, etc.) included in the sleep pattern determined by the portable sleep monitor based on at least one other sleep cycle determined by the medical-grade sleep monitor. Thereafter, when the subject uses the portable sleep monitor independently to monitor their sleep state in settings such as at home, the portable sleep monitor will use the sleep state measurement indicators determined by the medical-grade sleep monitor under the same sleep cycle as the baseline value to correct the data under the current sleep pattern to obtain a more accurate sleep state assessment result. In other words, each sleep state measurement indicator in the sleep state assessment result obtained by the portable sleep monitor has been corrected by the medical-grade sleep monitor.

[0097] According to a preferred embodiment, a portable sleep monitor and a medical-grade sleep monitor are used to detect the sleep state of a subject to determine a corresponding sleep pattern, and the sleep pattern determination result obtained by the medical-grade sleep monitor is used to correct one or more sleep state evaluation indicators in the sleep pattern determined by the portable sleep monitor, including making the subject experience one or more complete sleep cycles. Thus, several sleep patterns that may be produced by the subject in different sleep environments (including different field conditions, physiological factors and external interference factors) and the differentiation of various sleep state measurement indicators in different sleep cycles can be determined.

[0098] Furthermore, based on the sleep patterns determined by the medical-grade sleep monitor, the sleep state metrics for various sleep patterns and / or sleep cycles determined by the portable sleep monitor can be individually corrected. The correction results can be fed back to and stored in the portable sleep monitor to improve the detection accuracy of the portable sleep monitor. In addition, accurate sleep state assessment results can also help to examine the relationship between sleep quality and recovery for patients with sleep disorders and other diseases.

[0099] According to a preferred embodiment, based on the difference between at least one other sleep pattern determined by the medical-grade sleep monitor based on bioelectric signals and at least one sleep pattern determined by the portable sleep monitor, each of which corresponds to one or more sleep state metrics, the controller can correct the sleep state metrics related to the sleep pattern determined by the portable sleep monitor based on the sleep state metrics in the sleep pattern determined by the medical-grade sleep monitor, and transmit the corrected sleep state assessment results related to each sleep state metric to the portable sleep monitor for storage. In particular, correcting the sleep state metrics related to the sleep pattern determined by the portable sleep monitor based on the sleep state metrics in the sleep pattern determined by the medical-grade sleep monitor can be based on a preset correction program / algorithm, machine learning, or settings set by medical staff.

[0100] According to a preferred embodiment, the application method provided by the present invention may further include the second sleep monitor 200 providing at least one auxiliary treatment plan related to the user's sleep stage to the first sleep monitor 100 based on at least one sleep state measurement indicator related to the first sleep mode corrected based on the third sleep mode.

[0101] In particular, for today's increasingly intelligent sleep monitoring equipment and methods, whether it is a portable sleep monitor or a medical-grade sleep monitor, when determining the subject's sleep pattern or sleep state, both can form a sleep assistance program related to the sleep pattern based on one or more sleep state metrics contained in the determined sleep pattern. Specifically, the sleep assistance program is, for example, to apply a magnetic field or electric field that can affect the subject's sleep state by relying on the instrument's built-in magnetic field unit or electrical stimulation unit. In particular, based on accurate sleep state assessment reports, these data can be used to form an auxiliary treatment program for improving the subject's poor sleep state. Furthermore, by starting or executing these auxiliary treatment programs at the appropriate time, they can be used to improve the subject's sleep quality. More importantly, in addition to improving sleep quality, these sleep assistance programs may also have a potential positive effect on promoting the absorption of certain drugs during the sleep stage.

[0102] Specifically, the sleep status monitoring results of the portable sleep monitor are corrected by the sleep status monitoring results of the medical-grade sleep monitor, and a corresponding sleep assistance plan is formed based on the corrected sleep status monitoring results and stored in the portable sleep monitor, so that the subjects can complete more accurate and effective sleep assistance treatment at home through the portable sleep monitor without having to go to hospitals, high-end clinics, etc. with expensive medical-grade sleep monitors.

[0103] According to a preferred embodiment, the application method of the present invention may further include initiating at least one auxiliary treatment plan associated with the user's sleep stage, determined based on at least one sleep state metric associated with the first sleep pattern that is corrected based on the third sleep pattern, during one or more sleep stages determined by the first sleep monitor 100. Specifically, these auxiliary treatment plans can be pre-activated or timed by the subject before the patient falls asleep. Alternatively, during real-time monitoring by the portable sleep monitor, these auxiliary treatment plans can be activated during one or more specific sleep stages determined by the portable sleep monitor.

[0104] 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 assisting sleep. Specifically, for example, when the portable sleep monitor determines that the subject has entered the light sleep stage, a handheld or head-mounted portable sleep monitor can be used to apply a first frequency magnetic field and / or electric field to the subject's head or hands to accelerate the subject's sleep process. Alternatively, when the portable sleep monitor determines that the subject has entered the deep sleep stage, a handheld or head-mounted portable sleep monitor can be used to apply a second frequency magnetic field and / or electric field to the subject's head or hands 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.

[0105] According to a preferred embodiment, in a sleep assistance program for assisting a subject to fall asleep using a sleep monitor with a sleep assistance function such as a first sleep monitor 100 (such as a portable sleep monitor) and / or a second sleep monitor 200 (such as a medical-grade sleep monitor), alternating current can be used to stimulate receptors such as the subject's median nerve, radial nerve and / or ulnar nerve to regulate corresponding brain areas (such as the hypothalamus) in the skull through neural sensation, thereby achieving auxiliary treatment for insomnia.

[0106] Example 3

[0107] According to a preferred embodiment, this embodiment provides an electronic device that can be used to implement the application method of the sleep assistance system provided by the present invention. Specifically, the electronic device may include: one or more processors, a memory, and a communication bus for connecting at least the processor and the memory.

[0108] According to a preferred embodiment, the memory is configured to store a computer system readable medium, and the computer system readable medium has various functions in the embodiments of the present invention.

[0109] According to a preferred embodiment, the processor is configured to execute computer system readable media stored in the memory to implement various functional applications and data processing, especially the anti-fraud publicity method in this embodiment.

[0110] 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).

[0111] 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.).

[0112] 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.

[0113] According to a preferred embodiment, the electronic device may further include at least one communication interface. Specifically, the electronic device may be communicatively connected to at least one external device via the communication interface. In addition, the electronic device may also be communicatively connected to at least one external network via a network adapter. The network adapter is communicatively connected to a communication bus.

[0114] Example 4

[0115] This embodiment provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to execute the application method of the present invention.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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).

[0121] 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 sleep assisting system, characterized in that: A first sleep monitor (100) and a second sleep monitor (200) capable of signal communication to share system data and allow interaction with one or more sleep state metrics associated with a subject, wherein: A first wearable sleep monitor (100) for home use, configured to determine a first sleep pattern based on one or more physiological characteristic data associated with a subject's sleep duration, and capable of providing a variable magnetic field / electric field associated with the subject's sleep duration or frequency to an actionable target of the subject; A second sleep monitor (200) deployed in a hospital or advanced clinic, configured to determine a second sleep pattern matching the first sleep pattern based on one or more physiological characteristic data associated with the subject's sleep duration; The second sleep mode is fitted with at least one sleep curve included in the first sleep mode determined by the first sleep monitor (100), or the second sleep mode includes at least one sleep cycle fitted with the first sleep mode. In the second sleep mode, the second sleep monitor (200) is capable of determining a third sleep mode based on one or more bioelectric signal data associated with the subject's sleep duration, and correcting at least one sleep state measurement indicator included in the first sleep mode based on the third sleep mode.

2. The system according to claim 1, wherein: Also includes: The second sleep monitor (200) is capable of providing one or more auxiliary treatment plans related to the user's sleep stage to the first sleep monitor (100) based on one or more sleep state metrics related to the first sleep mode corrected based on the third sleep mode.

3. The system according to claim 2, characterized in that Also includes: The first sleep monitor (100) is capable of initiating 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 mode corrected based on the third sleep mode during the determined one or more sleep stages.

4. The system according to claim 1, wherein: Determining a sleep pattern based on one or more physiological characteristic data associated with a subject's sleep duration or frequency includes: Processing the data waveform of the one or more physiological characteristic data into a plurality of segmented waveforms; Extracting one or more physiological characteristic data from each segmented waveform; classifying the user's sleep stage based on one or more physiological characteristic data in each segmented waveform; The sleep state sum of the user is obtained based on the classified sleep stages to determine the sleep pattern.

5. The system according to claim 1, wherein: The physiological characteristic data includes body temperature, movement, heart rate and / or respiratory rate.

6. The system according to claim 1, wherein: The bioelectric signal data includes electroencephalogram (EEG) signals, electrooculogram (EOG) signals, electromyography (EMG) signals and / or electrocardiogram (ECG) signals.

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