Household sleep monitoring and stimulation system and method

Abstract

The invention relates to a home sleep monitoring and stimulating system and method, and the system comprises a first sleep monitor which is used for obtaining one or more pieces of physiological feature data of a user in a sleep state, determining a first sleep mode related to the user based on the one or more pieces of physiological feature data, applying / providing a waveform of which the frequency is close to that of the brain wave or a time-varying magnetic field which is pre-stored in a storage unit and is used for generating the corresponding brain wave to any actionable target spot at the body of the user; when a signal analysis unit of the first sleep monitor analyzes and determines that the sleep state or the sleep quality of the user is poor or needs to be adjusted based on one or more physiological feature data, obtained by an acquisition module, of the user in the sleep process, a time-varying magnetic field is provided for the body of the user through a magnetic field unit. According to the invention, receptors such as the median nerve, the radial nerve and / or the ulnar nerve of the testee can be stimulated by using the alternating current, so that the corresponding intracranial brain region can be adjusted through the nerve feeling, and the auxiliary treatment of insomnia can be realized.

Description

[0001] The original basis of the divisional application is patent application No. 202310271797.8, filed on March 20, 2023, with the title of "A system for assisting sleep and its application method". TECHNICAL FIELD

[0002] The present application relates to the technical field of sleep monitoring, in particular to a home sleep monitoring and stimulation system and method. BACKGROUND

[0003] Sleep apnea syndrome (SAS) is an example of sleep disorders, which is characterized by repeated occurrence of respiratory pause and / or low ventilation, sleep interruption and other manifestations in the sleep state. These symptoms can last for several seconds or even several minutes. When apnea occurs, carbon dioxide accumulates in the human body, and the high carbon dioxide level detected by the sensor in the blood stream sends a signal to the brain to wake up the person so that he can breathe, and then fall asleep again. This type of event can occur several times throughout the night, and significantly reduces sleep quality, which can also cause various risks and gradually become an important factor causing various health problems. People with sleep apnea syndrome (SAS) experience a full night's sleep, but they still feel that they have not had enough proper rest.

[0004] Many studies have shown that sleep problems are significantly associated with various serious health conditions, including depression, heart disease, obesity, and shorter life expectancy. Just one or a few hours of sleep loss on a night can have a significant negative impact on athletic performance, learning skills, and mood. On the other hand, long night sleepers who sleep more than 9 hours or more are also at risk of coronary heart disease and stroke.

[0005] In order to explore the complex interrelationship between sleep and post-waking conditions, researchers have been continuously studying various different physiological conditions during sleep. Sleep monitoring is valued for many reasons, one of the most important reasons is that sleep monitoring can provide actual data related to user sleep, such as sleep duration, depth, sleep time and sleep wake-up time. After mastering these data, patients with sleep disorders can have the basis for seeking to improve sleep quality.

[0006] CN104224132B discloses a sleep monitoring device, comprising a detection module, a processing module electrically connected with the detection module, and an output module electrically connected with the processing module. The detection module is configured to collect physiological characteristic signals representing a sleep state of a user, including one or more of a heart rate characteristic signal representing a heart rate characteristic of a subject and a respiration characteristic signal representing a respiration characteristic of the subject. The processing module is configured to process the physiological characteristic signals from the detection module to obtain a comprehensive sleep assessment result of the subject. The output module is configured to output the comprehensive sleep assessment result from the processing module.

[0007] There are several devices on the market for monitoring sleep efficiency or sleep quality, such as home portable sleep monitors and medical-grade sleep monitors. The medical-grade sleep monitor (such as polysomnography) is currently the gold standard for sleep research, and is mainly used to accurately assess the sleep state of a subject, such as diagnosing sleep disorders. Polysomnography includes 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 required to record the brain wave signals must have extremely high accuracy. Therefore, existing medical-grade sleep monitoring devices are usually set up in health service institutions such as hospitals and clinics, and need to be supervised by experts, which is not convenient for home use.

[0008] Portable sleep monitoring products are usually wearable and most are based on accelerometers. Such products mainly obtain motion data of a user during sleep through an accelerometer, and analyze and evaluate the sleep state of the user based on the data. However, the limb movement data generated by the accelerometer is not directly related to the sleep state of the user, so the final sleep state evaluation is often inaccurate: for example, the user has fallen asleep, but due to certain involuntary reflexes of the human body during sleep, the user produces body movements, at which time the sleep monitoring device may determine that the user has not fallen asleep due to the body movement data provided by the accelerometer. Therefore, these devices usually cannot accurately measure sleep quality and sleep efficiency.

[0009] Therefore, it is necessary to provide a sleep monitoring device / system with accurate measurement results, which can correctly guide or assist users in monitoring and evaluating sleep states at home and improving sleep quality.

[0010] In addition, on the one hand, there are differences in the understanding of those skilled in the art; on the other hand, due to the limited space, the applicant has not listed all the details and contents, but this does not mean that the present application does not have these prior art characteristics, on the contrary, the present application has all the characteristics of the prior art, and the applicant reserves the right to add relevant prior art in the background art. SUMMARY

[0011] In view of the deficiencies of the prior art, the present application 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.

[0012] To achieve the above-mentioned purpose, the present application provides a sleep assisting system, comprising a first sleep monitor and a second sleep monitor allowing interaction with one or more sleep state metric indicators associated with a subject, wherein, The first sleep monitor is configured to determine a first sleep pattern according to one or more physiological characteristic data associated with the sleep duration of the subject, and can provide a variable magnetic field / electric field associated with the sleep time or frequency of the subject to the actionable target of the subject; The second sleep monitor is configured to determine a second sleep pattern matched with the first sleep pattern according to one or more physiological characteristic data associated with the sleep duration of the subject; Wherein, in the second sleep pattern, the second sleep monitor can determine a third sleep pattern according to one or more bioelectric signal data associated with the sleep duration of the subject, and correct at least one sleep state metric indicator contained in the first sleep pattern according to the third sleep pattern.

[0013] Preferably, the sleep assisting system according to the present application further comprises: The second sleep monitor can provide one or more auxiliary treatment programs related to the sleep stage of the user to the first sleep monitor according to one or more sleep state metric indicators related to the first sleep pattern based on the third sleep pattern.

[0014] Preferably, the sleep assisting system according to the present application further comprises: The first sleep monitor can start at least one auxiliary treatment program associated with the sleep stage of the user determined according to one or more sleep state metric indicators related to the first sleep pattern based on the third sleep pattern in the determined one or more sleep stages.

[0015] Preferably, the step of determining the sleep pattern according to one or more physiological characteristic data associated with the sleep time or frequency of the subject comprises: processing the data waveform of one or more physiological characteristic data into a plurality of segmented waveforms; extracting one or more physiological characteristic data in each segmented waveform; classifying the sleep stage of the user with one or more physiological characteristic data in each segmented waveform; obtaining the sleep state sum of the user based on the classified sleep stage to determine the sleep pattern.

[0016] Preferably, the physiological characteristic data includes body temperature, motion, heart rate and / or respiratory rate.

[0017] Preferably, the bioelectric signal data comprises electroencephalogram, electrooculogram, electromyogram and / or electrocardiogram.

[0018] Preferably, the present application relates to a method for using the above-mentioned sleep-assisted system, comprising: S101: determining, by a first sleep monitor, a first sleep pattern corresponding to one or more physiological feature data associated with sleep time or frequency of a subject.

[0019] S102: determining, by a second sleep monitor, at least one second sleep pattern matching the first sleep pattern corresponding to one or more physiological feature data associated with sleep time or frequency of the subject.

[0020] S103: determining, by the second sleep monitor, a third sleep pattern corresponding to one or more bioelectric signal data associated with sleep time or frequency of the subject based on the second sleep pattern.

[0021] S104: correcting, by the second sleep monitor, one or more sleep state metric indicators included in the first sleep pattern determined by the first sleep monitor based on the third sleep pattern.

[0022] Preferably, the present application relates to a method for using the above-mentioned sleep-assisted system, further comprising: activating, by the first sleep monitor, at least one sleep stage-associated assistance treatment scheme determined based on the one or more sleep state metric indicators related to the first sleep pattern corrected based on the third sleep pattern, in one or more sleep stages determined.

[0023] Preferably, the present application further relates to an electronic device, comprising: one or more processors; a memory for storing one or more computer programs; when the one or more computer programs are executed by the one or more processors, the one or more processors implement the method for using the above-mentioned sleep-assisted system.

[0024] Preferably, the present application further relates to a storage medium containing computer executable instructions for executing the method for using the above-mentioned sleep-assisted system when executed by a computer processor. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 is a structural schematic diagram of a sleep-assisted system according to a preferred embodiment of the present application; Figure 2 is a flowchart of a sleep-assisted method according to a preferred embodiment of the present application.

[0026] List of reference signs 100: first sleep monitor; 200: second sleep monitor. DETAILED DESCRIPTION

[0027] The following detailed description is made in connection with the accompanying drawings.

[0028] Various embodiments and / or implementations herein relate to an auxiliary / monitoring system and method thereof that utilizes user data, such as heart rate, body temperature, respiratory waveform, etc., to monitor and quantify user sleep quality.

[0029] Embodiment 1 In particular, the present application provides an auxiliary sleep system, such as Figure 1 as shown, comprising: A first sleep monitor 100 operatively attached to a user for acquiring one or more physiological characteristic data of the user in a sleep state. Further, the first sleep monitor 100 can determine a first sleep pattern associated with the user based on the one or more physiological characteristic data.

[0030] A second sleep monitor 200 operatively attached to the user for acquiring one or more physiological characteristic data and / or bioelectric signal data of the user in the sleep state. Further, the second sleep monitor 200 can determine a second sleep pattern based on the one or more physiological characteristic data and / or a third sleep pattern based on the bioelectric signal data.

[0031] Further, the second sleep monitor 200 can determine at least one sleep cycle based on a matching relationship between the first sleep pattern and the second sleep pattern with respect to at least one physiological characteristic data. In particular, the at least one sleep cycle is at least one sleep pattern that fits the first sleep pattern. In particular, 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 under the determined sleep pattern.

[0032] In particular, the auxiliary sleep occurrence described in the present application can be promoting the user to fall asleep, promoting deep sleep and / or prolonging it, promoting the transition between the latent sleep and the deep sleep, etc.

[0033] According to a preferred embodiment, the physiological characteristic data can generally include data signals of body temperature, motion, heart rate, and respiratory rate, etc. In particular, the physiological characteristic data of body temperature, motion, heart rate, and respiratory rate, etc. are stored in relation to time or frequency.

[0034] According to a preferred embodiment, bioelectrical signal data typically includes electroencephalogram (EEG) signals, electrooculogram (EOG) signals, electromyogram (EMG) signals, and electrocardiogram (ECG) signals. Specifically, these bioelectrical signal data are stored in a time- or frequency-dependent manner.

[0035] Specifically, in this invention, the first sleep monitor 100 can be a wearable / worn sleep monitor. Specifically, the wearable / worn sleep monitor can take the form of, for example, a hand-held type, a wristwatch type, a neck wrap type, or a head-clamping type, etc. In particular, this invention does not limit the specific structure of the wearable / worn first sleep monitor 100.

[0036] According to a preferred embodiment, since there is a certain correlation between physiological changes and sleep state during sleep, 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 mentioned above. This includes determining the total sleep duration, sleep stages corresponding to each time point, the segment duration and total duration of a certain sleep stage, interruptions and transitions between sleep stages, and sleep efficiency, etc.

[0037] According to a preferred embodiment, a wearable sleep monitor typically includes at least a data acquisition module and a signal processing module. Specifically, the data acquisition module is used to acquire one or more physiological characteristic data characterizing the user's sleep state. The signal processing module is electrically connected to the data acquisition module. The signal processing module is used to analyze and determine the user's sleep state or sleep quality based on the one or more physiological characteristic data from the data acquisition module.

[0038] 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 real-time physiological characteristic data in the storage unit and analyze it to obtain evaluation results of the sleep state or sleep quality related to the subject.

[0039] According to a preferred embodiment, the wearable / worn sleep monitor typically also includes an output module. The output module can be used to output sleep state evaluation results from the signal processing module. Specifically, the output module can output the user's sleep state evaluation results using any means capable of conveying information. For example, through one or more of the following methods: display, vibration, sound / light, etc. Alternatively, the generated sleep state evaluation results can be provided via an interface, which can be a monitor, mobile device, laptop, desktop computer, wearable device, or home computing device, etc.

[0040] Specifically, sleep state or sleep quality may include sleep quality index, sleep cycles, total sleep time, sleep efficiency, sleep latency, sleep fragmentation, and / or other measures. Furthermore, the evaluation results of sleep state or sleep quality may be any one of the following methods, or a combination thereof: graphs, curves, and textual representations.

[0041] Specifically, 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 acquire user information via indirect contact (such as video, IR, motion detectors, or other types of sensors).

[0042] According to a preferred embodiment of the present invention, the acquisition module can 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. Further, the temperature sensor can be used to acquire the user's body temperature characteristic signal. The heart rate sensor can be used to acquire the user's heart rate characteristic signal. The respiration sensor can be used to acquire the user's respiratory rate characteristic signal. The motion sensor can be used to acquire the user's body movement characteristic signal.

[0043] 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. Further, the signal analysis unit can output the evaluation result of the user's sleep state or sleep quality to the user through an output module. Specifically, the heart rate sensor can be one or more of an electrocardiogram (ECG) sensor, a blood oxygen saturation sensor, an ultrasound sensor, an optical volume measurement sensor, and a radio frequency sensor.

[0044] According to a preferred embodiment, when the acquisition module is a temperature sensor, the signal extraction unit can extract the body temperature characteristic signal from the temperature sensor. The signal analysis unit can store the real-time body temperature characteristic signal in the storage unit and analyze it to obtain the 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 through the output module.

[0045] According to a preferred embodiment, when the acquisition module is a respiratory sensor, the signal extraction unit can extract the respiratory frequency characteristic signal from the respiratory sensor. The signal analysis unit can store the real-time respiratory frequency characteristic signal in a storage unit and analyze it to obtain an evaluation result of the user's sleep state or sleep quality. Further, the signal analysis unit can output the evaluation result of the user's sleep state or sleep quality to the user through an output module. Specifically, the respiratory sensor can be one or more of a displacement sensor, a strain gauge sensor, and an optical volume measurement sensor.

[0046] Specifically, in this invention, heart rate characteristic signals and respiratory rate characteristic signals can constitute the user's cardiopulmonary characteristic signals. In addition to the above, cardiopulmonary characteristic signals may also include respiratory variability characteristic signals and cardiopulmonary coupling characteristic signals, etc.

[0047] According to a preferred embodiment, when the acquisition module is a motion sensor, the signal extraction unit can extract body motion feature signals from the motion sensor. Specifically, the user's body motion feature signals typically include features such as turning over or twisting. Further, the signal analysis unit can store the real-time body motion feature signals in a storage unit and analyze them to obtain an evaluation result of the user's sleep state or sleep quality. Further, the signal analysis unit can output the evaluation result of the user's sleep state or sleep quality to the user through an output module. Specifically, the body motion sensor can be one or more of a linear accelerometer, angular accelerometer, or other sensors capable of detecting object movement.

[0048] 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 transmit them to an external electronic device, such as a computer or mobile phone, through the output interface for display or analysis. Alternatively, it can upload the results to a cloud database / server through the output interface so that the user can obtain more comprehensive analysis and sleep guidance.

[0049] 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 acquire the user's body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal, and body movement characteristic signal, either individually 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 units.

[0050] In one optional implementation, 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 the evaluation result of the user's sleep state or sleep quality based on the analysis and processing results of these physiological characteristic data signals.

[0051] Specifically, for example, a corresponding weighting coefficient can be assigned to each of the user's body temperature characteristic signal, heart rate characteristic signal, respiratory rate characteristic signal, and body movement characteristic signal, and / or a corresponding weighting coefficient can 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 movement characteristic signal change rate. Subsequently, a sleep quality index related to one or more of the above physiological characteristic data signals or characteristic data signal change rates is calculated based on a preset weighted average algorithm.

[0052] Furthermore, the calculated sleep quality index can be compared with a preset quality threshold. 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 a range of preset quality thresholds. For example, if the sleep quality index is less than the preset quality threshold, the user's sleep state or sleep quality is poor.

[0053] Alternatively, in one alternative implementation, the user's physiological characteristic data, such as body temperature, movement, heart rate, and respiratory rate, can specifically be waveforms, such as body temperature waveforms, movement waveforms, heart rate waveforms, and respiratory waveforms. These waveforms can be obtained by a wearable sleep monitor.

[0054] 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, pre-defined threshold programming, or self-set by medical personnel and / or other possible methods.

[0055] Specifically, the signal analysis unit can categorize a user's sleep state into one or more stages, including W, N1, N2, N3, and R stages. Furthermore, the signal analysis unit can 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 could be the sum of sleep quality indices for each sleep stage. Additionally, the evaluation result of sleep state or sleep quality can also be determined based on one or more of total sleep time, sleep efficiency, sleep latency, and sleep fragmentation.

[0056] According to a preferred embodiment of the present invention, a 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 latency, and sleep fragmentation.

[0057] According to a preferred embodiment, the wearable first sleep monitor 100 provided by the present invention may also have the function of applying / providing a waveform with a frequency close to that of brain waves, or a time-varying magnetic field pre-stored in a storage unit for generating corresponding brain waves, to any applicable target point on the user's body. In particular, the applicable target point for the user may be, for example, acupoints on the human body.

[0058] 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 adjustment based on one or more physiological characteristic data of the user during sleep acquired by the acquisition module, 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 relation to 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 desired 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 acting on the human body. In particular, the magnetic field unit is, for example, a magnetic coil.

[0059] Specifically, since the human body cannot store external magnetic field energy, the magnetic stimulation effect is not a direct effect of the magnetic field, but rather a result of the electric current. A time-varying magnetic field generates an electric field, and the magnitude of the induced electromotive force is proportional to the rate of change of magnetic flux over time. The current generated by this electric field, if of sufficient strength and continuous action, can effectively stimulate the nervous system, just like the current introduced into the human body through electrodes. In particular, the electric field subsequently generated by the changing magnetic field, acting on the human body, produces neurotransmitters related to deep sleep (such as inhibitory neurotransmitters), which can influence sleep, for example, by accelerating sleep, promoting deep sleep, or prolonging the duration of deep sleep.

[0060] According to a preferred embodiment, in this invention, the second sleep monitor 200 can be a polysomnography monitor used in hospitals or clinics. Specifically, the second sleep monitor 200 can determine the user's sleep pattern at least through electroencephalogram (EEG) signals. Alternatively, the second sleep monitor 200 can determine the user's sleep pattern through at least two of EEG signals, electrooculogram (EOG) signals, and electromyogram (EMG) signals. In other words, the second sleep monitor 200 can determine the user's sleep pattern through bioelectrical signals.

[0061] Specifically, the acquisition module (e.g., electrodes) of the second sleep monitor 200 is connected to the user's forehead pole to acquire one or more of the user's electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) signals. The acquisition module sends the user's EEG, EOG, and / or EMG signals to the signal processing module for processing, and then transmits them to the control unit. After receiving these signal data, the control unit can analyze and compare them with the sleep data models pre-stored in its internal database, thereby determining the user's sleep state or sleep quality.

[0062] On the other hand, the second sleep monitor 200, which has bioelectrical signal detection capabilities, also typically has the function of independently analyzing one or more physiological characteristic data of the user, such as 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 sleep quality index, sleep cycle, total sleep time, sleep efficiency, sleep latency, sleep fragmentation, and / or other measures as described above.

[0063] According to a preferred embodiment of the present invention, the second sleep monitor 200 can determine a second sleep mode based on one or more physiological characteristic data of the user. Furthermore, the second sleep monitor 200 can also determine a third sleep mode based on one or more bioelectrical signals of the user. Specifically, bioelectrical signals include electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG), and electrocardiogram (ECG), etc. Further, the second and / or third sleep modes may include one or more of the user's sleep quality index, total sleep time, sleep efficiency, sleep latency, sleep fragmentation, and / or other metrics.

[0064] According to a preferred embodiment, the second sleep monitor 200 may include a data acquisition module, a signal processing module, and an output module. Specifically, the data acquisition module can be used to acquire one or more physiological characteristic data and / or bioelectrical signal data characterizing the user's sleep state. The signal processing module can be used to analyze and determine the user's sleep pattern based on one or more physiological characteristic data and / or bioelectrical signal data from the data acquisition module, thereby determining the user's sleep state or sleep quality. The output module can be used to output the sleep state evaluation results from the processing module. Similarly, the second sleep monitor 200 may include the same or similar system architecture as the first sleep monitor 100, and the specific signal transmission and processing principles can be referred to those of the first sleep monitor 100, which will not be elaborated further here.

[0065] Similarly, in this invention, the second monitor may also be equipped to provide the subject with a variable, time-varying magnetic field / electric field.

[0066] Example 2 According to a preferred embodiment, in order to address the technical shortcomings of existing sleep monitoring systems / methods, particularly in situations where expensive medical-grade sleep monitoring equipment is unavailable, the present invention also provides an application method for an auxiliary sleep system, comprising: S101: The first sleep pattern is determined by the first sleep monitor 100, corresponding to at least one physiological characteristic data associated with the subject's sleep duration.

[0067] S102: Determine the second sleep pattern corresponding to at least one physiological characteristic data related to the subject's sleep duration using the second sleep monitor 200.

[0068] S103: In the second sleep mode, the second sleep monitor 200 determines the third sleep mode based on at least one bioelectrical signal data related to the subject's sleep duration.

[0069] S104: Modify at least one sleep state metric included in the first sleep mode based on the third sleep mode.

[0070] Specifically, the second sleep pattern is fitted to at least one sleep curve contained in the first sleep pattern determined by the first sleep monitor 100. Alternatively, the second sleep pattern includes at least one sleep cycle fitted to the first sleep pattern.

[0071] Typically, sleep monitoring devices such as the second sleep monitor 200 are high-precision monitoring instruments deployed in hospitals, high-end clinics, and other similar settings. One of the significant advantages of this type of sleep monitoring device is its high detection accuracy and precision, which is often used to accurately assess the sleep state of the subject. However, its drawback is that users need to go to designated locations from time to time for testing and sleep treatment, which is very cumbersome and inconvenient, especially for some users with mobility impairments. As a result, it not only consumes a lot of time and energy for users, but more importantly, the high cost of purchasing and using the in-hospital sleep monitoring and treatment equipment itself results in higher treatment expenses for users, increasing their burden.

[0072] To address this, numerous portable sleep monitors for home use (such as the First Sleep Monitor 100) are available on the market. These portable sleep monitors are lightweight, easy to wear, and can be flexibly applied to monitor sleep states in various sleep-friendly settings. In particular, the data detection capabilities of these sleep monitors, such as body temperature, heart rate, and respiratory rate, can basically support users' sleep quality monitoring at home. Furthermore, the sleep assistance functions provided by these sleep monitors (such as applying electric / magnetic field stimulation to generate sleep-promoting neurotransmitters or regulate related hormones) can also basically meet users' daily sleep therapy needs.

[0073] However, compared to medical-grade sleep monitors like the second monitor 200, portable sleep monitors have very limited detection accuracy and precision. One or more of the sleep cycles, sleep quality index, sleep efficiency, sleep latency, sleep fragmentation, and / or other metrics they determine related to the user's sleep process are likely to be inaccurate. Therefore, when a user is sleeping at home, these portable sleep monitors may provide significantly biased sleep state assessments. Based on these erroneous assessments, the sleep guidance and even the sleep aids / measures offered by these portable sleep monitors are often inadequate. In such cases, portable sleep monitors not only fail to provide accurate assessments but also fail to guide the user into the desired sleep state through reasonable and effective means. Furthermore, the implementation of incorrect sleep guidance or aids may worsen the user's poor sleep state, increase fatigue, disrupt circadian rhythms, and seriously affect and harm the user's physical and mental health.

[0074] Specifically, considering the inherent limitations of most portable sleep monitors when used at home, this invention utilizes a high-precision and accurate medical-grade sleep monitor to correct the sleep patterns determined by the portable sleep monitor itself. While using the portable sleep monitor to determine the user's sleep pattern, at least one sleep pattern that fits the sleep curve determined by the portable sleep monitor is determined through the independent physiological characteristic data monitoring device of the medical-grade sleep monitor. Furthermore, after determining a sleep pattern with a high degree of fit to the sleep curve obtained by the portable sleep monitor, the user's sleep pattern is further determined using bioelectrical signals (such as electroencephalogram signals) acquired by the medical-grade sleep monitor. Based on this sleep pattern determined by bioelectrical signals, the sleep pattern determined by the portable sleep monitor is corrected, such as by correcting one or more of the following metrics: sleep quality index, sleep efficiency, sleep latency, sleep fragmentation, and / or others, to provide the user with accurate and reliable sleep state assessment results.

[0075] Furthermore, by verifying the sleep patterns determined by portable sleep monitors using medical-grade sleep monitors, it is possible not only to accurately determine whether the sleep patterns determined by home portable sleep monitors are correct, but also to provide reasonable and effective sleep assistance measures based on the accurate determination of sleep patterns, such as providing time-varying magnetic or electric fields related to the user's sleep state.

[0076] Specifically, the subject is placed in an environment equipped with medical-grade sleep monitors, such as a hospital or high-end clinic. A portable sleep monitor (such as the first sleep monitor 100 mentioned above) and a medical-grade sleep monitor (such as the second sleep monitor 200 mentioned above) are worn to establish a sleep monitoring connection with the subject. Preferably, the portable sleep monitor and the medical-grade sleep monitor establish signal communication, enabling them to interact and share system data. Further, the subject's sleep patterns can be detected and determined using both the portable and medical-grade sleep monitors. 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. Specifically, the sleep pattern determined by the medical-grade sleep monitor that fits the portable sleep monitor can be based on the same physiological characteristic data, where the total sleep duration, the start and end points and corresponding durations of each independent sleep stage, and the values ​​or rates of change of one or more sleep state data points in each sleep stage are comparable.

[0077] Secondly, when the medical-grade sleep monitor identifies at least one sleep pattern that fits the sleep curve identified by the portable sleep monitor, the medical-grade sleep monitor can identify / acquire at least one other sleep pattern relevant to the subject based on the acquired bioelectrical signals. Specifically, given the superior detection accuracy of the medical-grade sleep monitor, the controller can correct at least one evaluation metric (such as sleep quality index, sleep efficiency, sleep latency, etc.) included in the sleep pattern identified by the portable sleep monitor based on at least one other sleep cycle identified by the medical-grade sleep monitor. Subsequently, when the subject uses the portable sleep monitor independently for sleep state monitoring in settings such as home, the portable sleep monitor will use the sleep state metrics under the same sleep cycle identified by the medical-grade sleep monitor as a baseline to correct the data under the current sleep pattern, thereby obtaining more accurate sleep state assessment results. In other words, all sleep state metrics in the sleep state assessment results acquired by the portable sleep monitor have been corrected by the medical-grade sleep monitor.

[0078] According to a preferred embodiment, a portable sleep monitor and a medical-grade sleep monitor are used to detect the sleep state of the subject to determine the corresponding sleep pattern. The sleep pattern determination results obtained by the medical-grade sleep monitor are used to correct one or more sleep state assessment indicators in the sleep pattern determined by the portable sleep monitor. This includes having the subject experience one or more complete sleep cycles. As a result, several sleep patterns that the subject may generate under different sleep environments (including different environments, physiological factors and external interference factors) and the differences in various sleep state measurement indicators in different sleep cycles can be determined.

[0079] Furthermore, based on the sleep patterns determined by the medical-grade sleep monitor, the sleep state metrics under various sleep patterns and / or sleep cycles determined by the portable sleep monitor can be corrected, and the correction results can be fed back and stored in the portable sleep monitor to improve its detection accuracy. In addition, accurate sleep state assessment results can help examine the relationship between sleep quality and the recovery of patients with sleep disorders and other diseases.

[0080] According to a preferred embodiment, based on the difference between at least one sleep mode determined by a medical-grade sleep monitor according to bioelectrical signals and at least one sleep mode determined by a portable sleep monitor, each corresponding to one or more sleep state metrics, the controller can correct the sleep state metrics related to the sleep mode determined by the portable sleep monitor based on the sleep state metrics in the sleep mode 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. Specifically, correcting the sleep state metrics related to the sleep mode determined by the portable sleep monitor based on the sleep state metrics in the sleep mode determined by the medical-grade sleep monitor can be based on a preset correction program / algorithm, machine learning, or settings by medical personnel.

[0081] According to a preferred embodiment, the application method provided by the present invention may further include a 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 metric related to the first sleep mode, which is modified based on a third sleep mode.

[0082] Specifically, with today's increasingly intelligent sleep monitoring devices and methods, whether portable or medical-grade, both typically develop sleep support programs based on one or more sleep state metrics within the determined sleep pattern when identifying the subject's sleep pattern or sleep state. Specifically, sleep support programs may involve applying magnetic or electric fields that can influence the subject's sleep state using a built-in magnetic field unit or electrical stimulation unit. In particular, based on accurate sleep state assessment reports, this data can be used to develop supportive treatment programs to improve the subject's poor sleep state. Furthermore, by initiating or implementing these supportive treatment programs at appropriate times, they can improve the subject's sleep quality. More importantly, in addition to improving sleep quality, these sleep support programs may also have a potentially positive impact on promoting the absorption of certain drugs during sleep.

[0083] Specifically, the sleep state monitoring results of a portable sleep monitor are corrected by the sleep state monitoring results of a medical-grade sleep monitor, and a corresponding sleep assistance plan is formed based on the corrected sleep state monitoring results and stored in the portable sleep monitor. This allows subjects to complete relatively accurate and effective sleep assistance treatment at home using a portable sleep monitor without having to go to hospitals or high-end clinics with expensive medical-grade sleep monitors.

[0084] According to a preferred embodiment, the application method of the present invention may further include initiating at least one auxiliary treatment program associated with the user's sleep stage, determined based on at least one sleep state metric related to the first sleep mode and modified according to a third sleep mode, during one or more sleep stages identified by the first sleep monitor 100. Specifically, these auxiliary treatment programs may be pre-activated by the subject before the patient falls asleep or activated at a set time. Alternatively, during real-time monitoring by a portable sleep monitor, these auxiliary treatment programs may be activated during one or more specific sleep stages identified by the portable sleep monitor.

[0085] According to a preferred embodiment, low-frequency electromagnetic stimulation and digital frequency-synthesized bio-inspired electrical waves can be used to act on the subject to achieve a sleep-aiding effect. Specifically, for example, when a portable sleep monitor determines that the subject has entered a light sleep stage, a first-frequency magnetic field and / or electric field can be applied to the subject's head or hands using a handheld or head-mounted portable sleep monitor to accelerate the subject's sleep onset process. Alternatively, when a portable sleep monitor determines that the subject has entered a deep sleep stage, a second-frequency magnetic field and / or electric field can be applied to the subject's head or hands using a handheld or head-mounted portable sleep monitor to prolong deep sleep time. Given 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.

[0086] According to a preferred embodiment, in a sleep aid program provided by a sleep monitor with sleep aid function, such as a first sleep monitor 100 (e.g., a portable sleep monitor) and / or a second sleep monitor 200 (e.g., a medical-grade sleep monitor), alternating current can be used to stimulate receptors such as the median nerve, radial nerve, and / or ulnar nerve of the subject to regulate the corresponding brain regions (such as the hypothalamus) through nerve sensation, thereby achieving insomnia aid treatment.

[0087] Example 3 According to a preferred embodiment, this embodiment provides an electronic device that can be used to implement the application method of the sleep-aid system provided by the present invention. Specifically, the electronic device may include: one or more processors, a memory, and at least a communication bus for connecting the processor and the memory.

[0088] According to a preferred embodiment, the memory is configured to store a computer system readable medium having the functions described in the embodiments of the present invention.

[0089] According to a preferred embodiment, the processor is configured to execute computer system readable media stored in memory to perform various functional applications and data processing, particularly the anti-fraud propaganda method in this embodiment.

[0090] According to a preferred embodiment, the processor includes, but is not limited to, CPU (Central Processing Unit), MPU (Micro Processor Unit), MCU (Micro Control Unit), and SOC (System on Chip).

[0091] According to a preferred embodiment, the memory includes, but is not limited to, volatile memory (e.g., DRAM or SRAM) and non-volatile memory (e.g., FLASH, optical disc, floppy disk, and hard disk drive).

[0092] According to a preferred embodiment, the communication bus includes, but is not limited to, industry standard architecture bus, microchannel architecture bus, enhanced ISA bus, video electronics standards association local bus, and peripheral component interconnect bus.

[0093] According to a preferred embodiment, the electronic device may further include at least one communication interface. Specifically, the electronic device can communicate with at least one external device via the communication interface. Furthermore, the electronic device can also communicate with at least one external network via a network adapter. The network adapter is communicatively connected to a communication bus.

[0094] Example 4 This embodiment provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the application method described in this invention.

[0095] According to a preferred embodiment, the computer storage medium of this embodiment can be 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. The computer-readable storage medium includes, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof.

[0096] According to a preferred embodiment, more specific examples of a computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0097] 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, wherein computer-readable program code is carried. This propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0098] According to a preferred embodiment, program code contained on a computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, or RF, or any suitable combination thereof.

[0099] According to a preferred embodiment, computer program code for performing the operations of embodiments of the present invention can be written in one or more programming languages ​​or a combination thereof. The programming languages ​​include object-oriented programming languages ​​such as Python, Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0100] It should be noted that the specific embodiments described above are exemplary. Those skilled in the art can devise various solutions inspired by the disclosure of this invention, and these solutions all fall within the scope of this invention and its protection. Those skilled in the art should understand that this specification and its accompanying drawings are illustrative and not intended to limit the scope of the claims. The scope of protection of this invention is defined by the claims and their equivalents. This specification contains multiple inventive concepts; terms such as "preferredly," "according to a preferred embodiment," or "optionally" indicate that the corresponding paragraph discloses an independent concept. The applicant reserves the right to file divisional applications based on each inventive concept.

Claims

1. A home sleep monitoring and stimulation system, characterized in that, The system includes a first sleep monitor (100). The first sleep monitor (100) is used to acquire one or more physiological characteristic data of the user in the sleep state, determine a first sleep mode related to the user based on one or more physiological characteristic data, and apply / provide a waveform with a frequency close to the brain wave to any target point on the user's body, or a time-varying magnetic field pre-stored in the storage unit for generating the corresponding brain wave. Among them, the signal analysis unit of the first sleep monitor (100) analyzes one or more physiological characteristic data of the user during sleep obtained by the acquisition module to determine the user's sleep state or sleep quality is poor or needs to be adjusted, and provides a time-varying magnetic field to the user's body through the magnetic field unit.

2. The system according to claim 1, characterized in that, The signal analysis unit provides a time-varying magnetic field through the magnetic field unit, which needs to be determined based on the difference between the user's sleep state or sleep quality and the ideal or expected sleep state.

3. The system according to claim 1 or 2, characterized in that, The signal analysis unit outputs a pulse signal with a variable frequency through the magnetic field unit, thereby adjusting the coupling time of the time-varying magnetic field acting on the human body.

4. The system according to any one of claims 1 to 3, characterized in that, The system also includes a second sleep monitor (200), which uses bioelectrical signals to determine the user's second sleep mode; Specifically, a second sleep pattern matching the first sleep pattern is determined by a second sleep monitor (200) corresponding to one or more physiological characteristic data associated with the subject's sleep time or frequency.

5. The system according to any one of claims 1 to 4, characterized in that, The second sleep monitor (200) determines a third sleep pattern associated with the subject's sleep time or frequency through bioelectrical signals; 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; The first sleep monitor (100) initiates at least one auxiliary treatment program associated with the user's sleep stage during one or more determined sleep stages, based on one or more sleep state metrics related to the first sleep mode and modified according to the third sleep mode.

6. The system according to any one of claims 1 to 5, characterized in that, The signal analysis unit in the first sleep monitor (100) calculates a sleep quality index related to one or more physiological characteristic data signals or the rate of change of characteristic data signals based on a preset weighted average algorithm; The calculated sleep quality index is compared with a preset quality threshold, and the user's sleep state or sleep quality is determined based on the difference between the sleep quality index and the preset quality threshold or the preset quality threshold range.

7. The system according to any one of claims 1 to 6, characterized in that, The second sleep pattern is fitted to at least one sleep curve contained in the first sleep pattern determined by the first sleep monitor (100); Alternatively, the second sleep pattern may include at least one sleep cycle that is fitted to the first sleep pattern.

8. The system according to any one of claims 1 to 7, characterized in that, The second sleep monitor (200) can provide one or more sleep state metrics 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 that are modified based on the third sleep mode.

9. A method for home sleep monitoring and stimulation, characterized in that, The method includes: Acquire one or more physiological characteristic data of the user in the sleep state, determine the first sleep mode related to the user based on one or more physiological characteristic data, and apply / provide a waveform with a frequency close to the brain wave to any target point on the user's body, or a time-varying magnetic field pre-stored in the storage unit for generating the corresponding brain wave. Among them, when the analysis of one or more physiological characteristic data of the user during sleep obtained by the acquisition module determines that the user's sleep state or sleep quality is poor or needs to be adjusted, a time-varying magnetic field is provided to the user's body through the magnetic field unit.

10. The method according to claim 9, characterized in that, The method further includes: The time-varying magnetic field provided by 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.

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