CN116269230A - Health sleep management system and method - Google Patents
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Abstract
The invention relates to a health sleep management system and a method, wherein the health sleep management system comprises: a first monitor operatively attached to the user for acquiring at least one item of sleep characteristic data of the user related to time and determining a first sleep mode based on the at least one item of sleep characteristic data; a second monitor operatively attached to the user for acquiring at least one item of sleep characteristic data and/or bioelectric signal data of the user in the first sleep mode, and determining at least one second sleep mode fitting the first sleep mode based on the at least one item of sleep characteristic data, and in the determined second sleep mode, determining a third sleep mode based on the bioelectric signal data, wherein the second monitor is capable of modifying at least one sleep state metric comprised by the first sleep mode based on the third sleep mode. The present invention is intended to accurately monitor or quantify a user's sleep without expensive sleep monitoring equipment.
Description
Technical Field
The invention relates to the technical field of sleep monitoring, in particular to a healthy sleep management system and method.
Background
Sleep can be generally characterized by two main sleep types: non-REM (rapid eye movement) sleep and REM (rapid eye movement) sleep, which is also known as dream sleep. non-REM sleep includes three sleep stages with different depths, starting with the shallowest stage of transition to sleep, to the second shallow sleep stage, and deepening to the third deep sleep stage where it is very difficult to wake up the sleeper. Sleep occurs in a series of recurrent sleep stages, where periods of non-REM (rapid eye movement) sleep and REM (rapid eye movement) sleep alternate, the sum of which may be referred to as the sleep cycle.
Sleep Apnea Syndrome (SAS) is an example of a sleep disorder characterized by recurrent manifestations of apnea and/or hypopnea, sleep interruption, etc. in a sleep state, which may last for seconds or even minutes. When apneas occur, carbon dioxide accumulates in the human body, and a signal is sent to the brain to wake up the person by detecting very high carbon dioxide levels through receptors in the blood stream, enabling it to breathe and then fall asleep again. This type of event may occur several times overnight and significantly reduce sleep quality, which may also cause various risks and gradually become an important factor in causing various health problems.
Hypopneas are another type of sleep disorder that includes too shallow breathing or abnormal breathing rate. Hypopneas are generally defined by a reduced amount of air moving into the lungs. Like Sleep Apnea Syndrome (SAS), hypopnea interferes with sleep in people, and even if people with hypopnea experience sleep overnight, they still feel that they do not get a sufficient rest.
Therefore, the quality of sleep of a user during a sleep cycle is critical to the daily activities of people. Although it is obvious that the human body needs to sleep to operate normally, the "quality" and "volume" of sleep required is still a complex problem. A great deal of research in recent years has focused on the discovery of sleep and its physiological and psychological effects. For example, some people feel tired and tired during daytime when they have severe hyposomnia, but some people also have similar lassitude after long-term sleep due to excessive sleep.
In order to ascertain the complex interrelationship between sleep and post-wake conditions, researchers are continually researching a variety of different physiological conditions during sleep. Among such studies, various sleep monitoring techniques have been proposed.
CN110882466B discloses a sleeping apparatus, which comprises a host and a magnetic coil electrically connected with the host, wherein the host comprises a main control device and a conversion circuit, the main control device is electrically connected with the magnetic coil, and the conversion circuit is electrically connected with the main control device; the main control device generates square wave signals and inputs the square wave signals into the conversion circuit, the square wave signals are converted into pulse signals through the conversion circuit, the pulse signals are input into the magnetic coil, so that the magnetic coil generates a time-varying magnetic field, the time-varying magnetic field is coupled to the brain sleep center of a patient with sleep disorder, the sleep process of the patient is conveniently regulated and induced, and the sleep promotion or awakening function is realized.
Portable sleep monitoring products are typically wearable/wearable (e.g., wrist-watch type intelligent sleep devices), most of which are accelerometer-based. The product mainly acquires motion data of a user in the sleeping process through an accelerometer, and evaluates the sleeping state of the user based on the analysis. However, the limb movement data generated by the accelerometer is not directly related to the sleep state of the user, so that the final sleep state assessment is inaccurate often: for example, the user has fallen asleep, but the user is producing body movements due to some involuntary reflex of the human body that occurs while sleeping, at which point the sleep monitoring device may assume that the user is not falling asleep due to the body movement data provided by the accelerometer.
Whereas sleep monitoring devices employed internally in hospitals typically evaluate sleep quality of a sleeper by measuring brain waves. Because brain waves are the golden rule defining sleep states, the existing medical brain wave detection device can be used for accurately evaluating the sleep states of a tested person. However, the brain wave signals are sometimes extremely weak, and the equipment for recording the brain wave signals needs to have extremely high accuracy, so that the existing medical sleep monitoring equipment is usually only set up in health service institutions such as hospitals and clinics, and is inconvenient to use at home.
Therefore, there is a need to provide a sleep monitoring device/system that can accurately guide or assist the user in monitoring, assessing and improving sleep quality in the home sleep state. Alternatively, there is a need for a method/system that accurately monitors or quantifies a user's sleep without expensive sleep monitoring equipment.
Furthermore, there are differences in one aspect due to understanding to those skilled in the art; on the other hand, since the applicant has studied a lot of documents and patents while making the present invention, the text is not limited to details and contents of all but it is by no means the present invention does not have these prior art features, but the present invention has all the prior art features, and the applicant remains in the background art to which the right of the related prior art is added.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a healthy sleep management system and a healthy sleep management method, which aim to solve at least one or more technical problems in the prior art.
To achieve the above object, the present invention provides a healthy sleep management system comprising:
a first monitor operatively attached to the user for acquiring at least one item of sleep characteristic data of the user related to time and determining a first sleep mode based on the at least one item of sleep characteristic data;
a second monitor operatively attached to the user for acquiring at least one item of sleep characteristic data and/or bioelectric signal data of the user in the first sleep mode and determining at least one second sleep mode fitting the first sleep mode based on the at least one item of sleep characteristic data, and in the determined second sleep mode, determining a third sleep mode based on the bioelectric signal data,
wherein the second monitor is capable of modifying at least one sleep state metric comprised by the first sleep mode based on the third sleep mode.
Preferably, the second monitor is capable of providing at least one auxiliary treatment regimen associated with the sleep stage of the user to the first monitor based on at least one sleep state metric associated with the first sleep mode modified according to the third sleep mode.
Preferably, the auxiliary treatment regimen is initiated either in advance or periodically before the user enters the sleep session or in one or more sleep stages as determined by the first monitor.
Preferably, determining at least one second sleep pattern that fits to the first sleep pattern based on the at least one sleep characteristic data, and in the determined second sleep pattern, determining a third sleep pattern based on the bioelectric signal data comprises subjecting the user to a plurality of sleep cycle periods.
Preferably, determining the sleep mode based on the at least one sleep characteristic data comprises:
processing a data waveform corresponding to at least one item of sleep characteristic data into a plurality of segmented waveforms;
extracting at least one sleep characteristic data in each segmented waveform;
dividing sleep stages of the user according to at least one sleep characteristic data in each segmented waveform;
and acquiring the sum of the sleep states of the users based on the classified sleep stages of the users to determine a sleep mode.
Preferably, in the present invention, the sleep state metric includes one or more of sleep quality index, sleep cycle, sleep efficiency, sleeping latency, and sleep segment.
Preferably, in the present invention, the at least one item of sleep characteristic data comprises one or more of body temperature, exercise, heart rhythm and respiratory rate.
Preferably, in the present invention, the first monitor and/or the second monitor may include:
the acquisition module is used for acquiring at least one sleep state characteristic data and/or bioelectric signal data representing the sleep state of the user;
a processing module capable of determining a sleep state assessment result associated with the user in response to the at least one item of sleep state characteristic data and/or bioelectrical signal data acquired from the acquisition module;
and the output module is used for outputting the sleep state evaluation result which is related to the user and comes from the processing module.
Preferably, the present invention also relates to a method of healthy sleep management, comprising:
providing a first monitor and a second monitor capable of bi-directional communication;
the first monitor determines a first sleep mode according to at least one sleep characteristic data related to a sleep duration of the user;
the second monitor determines at least one second sleep mode fitting the first sleep mode according to at least one sleep characteristic data related to the sleep time of the user;
in the determined second sleep mode, the second monitor determines a third sleep mode from at least one piece of bioelectrical signal data related to the sleep duration of the user and modifies at least one sleep state metric index contained in the first sleep mode based on the third sleep mode.
Preferably, the healthy sleep management method according to the present invention further includes:
at least one auxiliary treatment regimen associated with the sleep stage of the user is provided to the first monitor based on at least one sleep state metric associated with the first sleep mode modified according to the third sleep mode.
The invention checks the sleep mode determined by the portable sleep monitor through the medical grade sleep monitor, meets the requirement of accurately monitoring or quantifying the sleep of the user under the condition of no expensive sleep monitor equipment, can accurately judge whether the sleep state evaluation result determined by the household portable sleep monitor is correct or not, provides possible positive influence for checking the relation between the sleep quality and the recovery of patients with sleep disorder and other diseases, and simultaneously provides reasonable and effective sleep auxiliary measures for the patients with sleep disorder based on the accurate determination of the sleep mode, thereby obviously improving the sleep quality of the patients with sleep disorder.
Detailed Description
The present invention will be described in detail with reference to specific examples.
The american society of sleep medicine (AASM) divides the sleep cycle of adults into W-phase-awake (wake), N1-phase-non-rapid eye movement 1 (NREM 1), N2-phase-non-rapid eye movement 2 (NREM 2), N3-phase-non-rapid eye movement 3 (NREM 3), and R-phase-Rapid Eye Movement (REM), with sleep entering NREM sleep from W first, beginning with N1 phase, N1 lasting about 3-7 minutes, entering N2; the N2 phase lasts about 10 to 25 minutes; then, N3-N4 phase is entered, which varies from several minutes to one hour. After the deep sleep is finished, the sleep returns to the N1 phase or the N2 phase. Then, a first REM sleep period (first REM period lasting 5-10 minutes) is entered. The first sleep cycle is completed. Specifically, in one sleep cycle, the non-REM (rapid eye movement) sleep time is about 75% -80%, and the REM (rapid eye movement) sleep time is about 20% -25%.
In particular, an average adult has 4 to 6 sleep cycles per night. In the middle of sleep, deep non-rapid eye movement (NREM) sleep gradually decreases and REM sleep gradually extends. Specifically, the first half of the night has a high N3-phase ratio, and the second half of the night has a smaller N3-phase ratio, and REM (rapid eye movement) increases.
Further, during sleep, the brain typically generates a variety of brain wave signals, such as alpha, beta, theta, delta, and other non-characteristic waves, such as tip, spindle, and K complex waves. Specifically, the α wave: mainly seen in the quiet, awake and eye-closed state and in the R (rapid eye movement) phase, the frequency is 8-13 Hz. Beta wave: mainly seen in the eye opening state in the awake period, the low potential wave with the frequency of more than 13Hz (mostly 14-30 Hz). Theta wave: mainly seen in the later stage of N1, the frequency is 4-7 Hz. Delta wave: mainly seen in the deep sleep stage, the frequency is 1-3 Hz low frequency wave.
Various embodiments and/or implementations herein relate to a management system and method thereof that utilizes user data, such as heart rate, body temperature, respiration waveform, etc., to monitor and quantify the quality of sleep of a user.
Specifically, the present invention provides a healthy sleep management system, which may include:
A first monitor is operably attached to the user for acquiring one or more sleep characteristic data of the user in a sleep state. Further, the first monitor may determine a first sleep mode associated with the user based on the one or more sleep characteristic data.
A second monitor is operably attached to the user for acquiring one or more sleep characteristic data and/or bioelectrical signal data of the user in a sleep state. Further, the second monitor may determine a second sleep mode of the user and/or bioelectrical signal data based on the one or more sleep characteristic data.
Further, the second monitor can determine at least one sleep cycle based on a matching relationship of the first sleep mode and the second sleep mode with respect to the at least one item of sleep characteristic data. Specifically, the at least one sleep cycle is at least one sleep mode that fits to the first sleep mode. In particular, in the determined sleep mode, the second monitor is capable of modifying at least one sleep state metric associated with the first sleep mode determined by the first monitor based on the determined third sleep mode.
According to a preferred embodiment, the sleep characteristic data may generally comprise data signals such as body temperature (T), movement (S), heart rhythm (H), and respiratory rate (R). In particular, body temperature (T), movement (S), heart rhythm (H), respiratory rate (R), etc. are stored in relation to time or frequency.
According to a preferred embodiment, the bioelectric signal data may comprise brain wave signals, eye electrical signals, electromyographic signals, electrocardiographic signals, and the like. In particular, brain wave signals, eye electrical signals, muscle electrical signals, and cardiac electrical signals, etc. are stored in relation to time or frequency.
In particular, in the present invention, the first monitor may be a wearable/wearable sleep monitor. Specifically, the wearable/wearable sleep monitor may be in the form of a hand grip, wrist watch, neck wrap, head clamp, or the like, for example. In particular, in the present invention, the specific structure of the wearable/wearable first monitor is not limited.
According to a preferred embodiment, as a person is sleeping, there is a certain link between his physiological changes and his sleeping state. Therefore, the general sleep monitor can determine the sleep state of the human body according to the physiological signals of the human body, such as the body temperature, the heart rate, the respiratory rate and the like, including determining the total sleep time of the human body, the sleep stage corresponding to each time node, the segment time and the total duration of a certain sleep stage, the interrupt and link node between each sleep stage, the sleep efficiency and the like.
According to a preferred embodiment, the wearable/wearable sleep monitor may generally comprise at least an acquisition module and a processing module. In particular, the acquisition module may be used to acquire one or more sleep characteristic data characterizing a sleep state of the user. The processing module is electrically connected to the acquisition module. The processing module may be configured to determine a sleep state or sleep quality of the user based on the one or more sleep characteristic data analyses from the acquisition module.
According to a preferred embodiment, the processing module may comprise an extraction unit, an analysis unit and a storage unit. Specifically, the extraction unit may extract one or more sleep characteristic data from the acquisition module. The analysis unit may store the real-time sleep characteristic data in the storage unit and analyze it to obtain an evaluation result of sleep state or sleep quality.
According to a preferred embodiment, the wearable/wearable sleep monitor may also typically comprise an output module. The output module can be used for outputting the sleep state evaluation result from the processing module. In particular, the output module may output the sleep state assessment of the user using any means capable of communicating information. For example by one or more of display, vibration, sound/light, etc. Alternatively, the generated sleep state assessment results may be provided via an interface, which may be a monitor, mobile device, laptop, desktop, wearable or home computing device, or the like.
In particular, sleep states or sleep quality may include sleep quality index, sleep period, total sleep time, sleep efficiency, latency of sleep, sleep fragmentation, and/or other metrics. Further, the evaluation result of the sleep state or the sleep quality may be any one of a graph, a curve and a text manner or a combination thereof.
In particular, the acquisition module may be any device, wearable, sensor or other element configured or capable of obtaining data about a user. The acquisition module may communicate directly with the user or may obtain the user's information via indirect contact (video, IR, motion detector or other type of sensor).
According to a preferred embodiment, the acquisition module may be a sensor in the present invention. In particular, the acquisition module may include one or more of a temperature sensor, a heart rate sensor, a respiration sensor, and a motion sensor.
According to a preferred embodiment, the temperature sensor may be used to collect a characteristic signal of the body temperature of the user. The heart rate sensor may be used to collect heart rate characteristic signals of the user. The respiration sensor may be used to acquire a characteristic signal of the respiration rate of the user. The motion sensor may be used to collect body movement characteristic signals of the user.
According to a preferred embodiment, when the acquisition module is a heart rate sensor, the extraction unit may extract heart rate characteristic signals from the heart rate sensor. The analysis unit may store the real-time heart rate characteristic signal in the storage unit and analyze it to obtain an evaluation result of the sleep state or sleep quality of the user. Further, the analysis unit may output the evaluation result of the sleep state or sleep quality of the user to the user through the output module. In particular, the heart rate sensor may employ one or more of an electrocardiograph sensor, a blood oxygen saturation sensor, an ultrasound sensor, a light volume measurement sensor, and a radio frequency sensor.
According to a preferred embodiment, when the acquisition module is a temperature sensor, the extraction unit may extract the body temperature characteristic signal from the temperature sensor. The analysis unit may store the real-time body temperature characteristic signal in the storage unit and analyze it to obtain an evaluation result of the sleep state or sleep quality of the user. Further, the analysis unit may output the evaluation result of the sleep state or sleep quality of the user to the user through the output module.
According to a preferred embodiment, when the acquisition module is a respiration sensor, the extraction unit may extract a respiration frequency characteristic signal from the respiration sensor. The analysis unit may store the real-time respiratory rate characteristic signal in the storage unit and analyze it to obtain an evaluation result of the sleep state or sleep quality of the user. Further, the analysis unit may output the evaluation result of the sleep state or sleep quality of the user to the user through the output module. In particular, the respiration sensor may employ one or more of a displacement sensor, a strain gauge sensor, and a light volume measurement sensor.
In particular, in the present invention, the heart rate characteristic signal and the respiratory rate characteristic signal may constitute a cardiopulmonary characteristic signal of the user. In addition to the above, cardiopulmonary signature signals may include respiratory variability signature signals, cardiopulmonary coupling signature signals, and the like.
According to a preferred embodiment, when the acquisition module is a motion sensor, the extraction unit may extract a body movement characteristic signal from the motion sensor. In particular, the body movement characteristic signal of the user may generally include a characteristic signal such as turning over and twisting of the human body. Further, the analysis unit may store the real-time body movement characteristic signal in the storage unit and analyze it to obtain an evaluation result of the sleep state or sleep quality of the user. Further, the analysis unit may output the evaluation result of the sleep state or sleep quality of the user to the user through the output module. In particular, the body movement sensor may employ one or more of a linear accelerometer, an angular accelerometer, or other sensor that can detect movement of an object.
According to a preferred embodiment, after the processing module obtains the sleep state or sleep quality evaluation result of the user, the sleep state or sleep quality evaluation result can be transmitted to external electronic equipment, such as a computer, a mobile phone and the like, so as to be displayed or analyzed, and can also be uploaded to a cloud database/server through the output interface so that the user can obtain more comprehensive analysis and sleep guidance.
According to a preferred embodiment, the processing module may analytically determine the sleep state or sleep quality of the user based on the plurality of sleep characteristic data of the user. Specifically, the acquisition module may acquire the body temperature characteristic signal, the heart rate characteristic signal, the respiratory rate characteristic signal, the body movement characteristic signal, and the like of the user separately or simultaneously. The one or more extraction units of the processing module may extract and amplify the body temperature characteristic signal, the heart rate characteristic signal, the respiratory rate characteristic signal, and/or the body movement characteristic signal of the user. The analysis unit may calculate a sleep state or a sleep quality of the user based on the analysis of the body temperature characteristic signal, the heart rate characteristic signal, the respiratory rate characteristic signal, and/or the body movement characteristic signal from the extraction unit.
In an alternative embodiment, the analysis unit may process one or more of the body temperature characteristic signal, the heart rate characteristic signal, the respiratory frequency characteristic signal and the body movement characteristic signal of the user in a weighted operation manner, and obtain an evaluation result of the sleep state or the sleep quality of the user based on the analysis processing result of the sleep characteristic data signals.
In particular, for example, each of the body temperature characteristic signal, the heart rate characteristic signal, the respiratory rate characteristic signal and the body movement characteristic signal of the user may be given a respective weighting coefficient, and/or each of the body temperature characteristic signal change rate, the heart rate characteristic signal change rate, the respiratory rate characteristic signal change rate and the body movement characteristic signal change rate of the user may be given a respective weighting coefficient. Thereafter, a sleep quality index associated with the one or more sleep characteristic data signals or the characteristic data signal rate of change is determined based on a predetermined weighted average algorithm.
Further, the obtained sleep quality index may be compared with a preset quality threshold, and the sleep state or sleep quality of the user may be determined according to 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 smaller than the preset quality threshold, the sleep state or sleep quality of the user is poor.
Alternatively, in an alternative embodiment, the sleep characteristic data of the user, such as the data signals of body temperature (T), movement (S), heart rhythm (H), and respiratory rate (R), may specifically be waveforms, such as a body temperature waveform, a movement waveform, a heart rhythm waveform, and a respiratory waveform. These waveforms may be obtained from wearable sleep monitor measurements.
According to a preferred embodiment, after the extraction unit obtains the sleep characteristic data waveforms, the analysis unit may divide the characteristic data waveforms into a number of segmented waveforms. The analysis unit may extract characteristic data in the segmented oscillograms, such as body temperature data, heart rate data, or respiration data. Further, the analysis unit may divide the sleep state or stage of the user based on the feature data in the segmented waveform diagrams. In particular, the classification of the sleep state of the user by the analysis unit based on the characteristic data in the segmented waveform map may be by machine learning, predetermined threshold programming or self-setting by medical personnel and/or other possible ways.
Specifically, the analysis unit may divide the sleep state of the user into one or more phases of W phase, N1 phase, N2 phase, N3 phase, and R phase. Further, the analysis unit may analyze the sleep state or sleep quality results of the user for one or more categories of sleep stages. For example, the sleep state or sleep quality result of the user may be a sum of sleep quality indices for the individual sleep stages. Furthermore, 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, sleeping latency, and sleep fragmentation.
According to a preferred embodiment, the first monitor determines the first sleep mode based on one or more sleep characteristic data of the user. Further, the first sleep mode may include one or more of a sleep quality index, a total sleep time, a sleep efficiency, a sleeping latency, and sleep fragmentation of the user.
According to a preferred embodiment, the wearable/wearable first monitor provided by the present invention may further have a function of applying/providing a certain waveform with a frequency close to that of brain waves to an actionable target point at any one of the user's body, or a time-varying magnetic field pre-stored in a storage unit for generating corresponding brain waves. Specifically, the user may act on points such as points of the human body, e.g., baihui points, shenfeng points, zhihai points, or Yongquan points.
Specifically, the analysis unit of the first monitor can provide a time-varying magnetic field to the body of the user through the magnetic field unit when the analysis unit of the first monitor determines that the sleep state or sleep quality of the user is poor or needs to be adjusted based on one or more sleep characteristic data analysis of the user in the sleep process, which is acquired by the acquisition module. Further, the time-varying magnetic field provided by the analysis unit through the magnetic field unit is configured in association with a sleep state or a sleep quality of the user. In other words, the analysis unit provides a time-varying magnetic field through the magnetic field unit, which needs to be determined according to the sleep state or the difference of the sleep quality of the user from the ideal or desired sleep state. Alternatively, the analysis unit may 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.
In particular, since the human body cannot store external magnetic field energy, the magnetic excitation effect is not a direct effect of the magnetic field, but belongs to a current effect result. The time-varying magnetic field generates an electric field, and the magnitude of the induced electromotive force generated by the magnetic field is proportional to the rate of change of the magnetic flux with time. The current generated by the electric field has certain intensity and continuous action, and can effectively stimulate the nervous system as the current introduced into the human body through the electrode. In particular, neurotransmitters associated with deep sleep (e.g., inhibitory neurotransmitters) are generated when the electric field generated by the changing magnetic field is applied to the human body, and can affect the human sleep, such as to accelerate sleep, promote deep sleep, or extend the duration of deep sleep.
According to a preferred embodiment, the second monitor may be an electroencephalogram sleep monitor such as used in a hospital or medical clinic. In particular, the second monitor is, for example, a polysomnography. In particular, the second monitor may determine the sleep mode of the user at least by means of an electroencephalogram signal. Alternatively, the second monitor may determine the sleep mode of the user through at least two of an electroencephalogram signal, an electrooculogram signal, and an electromyogram signal. In other words, the second monitor may determine the sleep mode of the user through the bioelectrical signal.
Specifically, a signal acquisition unit (such as an electrode) of the second monitor is connected to the frontal pole of the user to acquire an electroencephalogram signal, an electrooculogram signal, an electromyogram signal, and the like of the user. The signal acquisition unit sends the brain electrical signals, the eye electrical signals and the electromyographic signals of the user to the processing module, and the brain electrical signals, the eye electrical signals and the electromyographic signals are transmitted to the control part after being processed. After receiving the signal data, the control part can analyze and compare the signal data with a sleep data model pre-stored in an internal database, so that the sleep state or sleep quality of the user can be determined.
On the other hand, the second monitor having the electroencephalogram detection function may also generally have a function of independently analyzing one or more sleep characteristic data of the body temperature (T), movement (S), heart rate (H), and respiratory rate (R) of the user to determine the sleep state or sleep quality of the user. In particular, the sleep state or sleep quality may include a sleep quality index, sleep cycle, total sleep time, sleep efficiency, latency to sleep, sleep fragmentation, and/or other metrics as previously described.
According to a preferred embodiment, the second monitor may determine the second sleep mode based on one or more sleep characteristic data of the user. In addition, the second monitor may also determine a third sleep mode based on one or more bioelectrical signals of the user. In particular, bioelectric signals include brain electrical signals, eye electrical signals, muscle electrical signals, and cardiac electrical signals, and the like. Further, the second sleep mode and/or the third sleep mode may include one or more of a sleep quality index, a total sleep time, a sleep efficiency, a latency of sleep, sleep fragmentation, and/or other metrics of the user.
According to a preferred embodiment, the second monitor may comprise an acquisition module, a processing module and an output module. In particular, the acquisition module may be used to acquire one or more sleep characteristic data and/or bioelectric signal data characterizing a sleep state of the user. The processing module may be configured to determine a sleep mode of the user based on the one or more sleep characteristic data and/or the bioelectrical signal data analysis from the acquisition module to determine a sleep state or sleep quality of the user. The output module can be used for outputting the sleep state evaluation result from the processing module. Similarly, the second monitor may include the same or similar system architecture as the first monitor, and specific signal transmission and processing principles may refer to the first monitor, which is not described herein in detail.
Generally, a sleep monitoring device such as a second monitor is often a device for sleep monitoring by using bioelectric signals (such as brain signals), and is often deployed in hospitals, advanced clinics and the like, and since determining the sleep state of a user based on brain waves is the gold rule commonly accepted by the scientific community, one of the significant advantages of a medical-grade sleep monitoring device is that it has higher detection precision and accuracy, and is often used for accurately evaluating the sleep state of a subject, however, it has the disadvantage that it requires the user to go to a designated place to receive detection and sleep treatment, which is very cumbersome and inconvenient, especially for users with some inconvenient actions, thereby not only extremely consuming time and effort of the user, but also giving the user higher treatment expenditure due to the high purchase and use costs of the apparatus of the in-hospital sleep monitoring and treatment device itself, which aggravates the burden of the user.
In contrast, a plurality of portable sleep monitors (such as the first monitor) capable of being used at home are already provided in the market, the portable sleep monitor is light in size and convenient to wear, and can be flexibly applied to sleep state monitoring in various sleeping occasions, particularly, the data detection of body temperature, heart rhythm, respiratory rate and the like of the sleep monitor can basically support the sleep quality monitoring in the home state of a user, and the sleep auxiliary functions (such as applying electric field/magnetic field stimulation, generating neurotransmitters related to promoting sleep or adjusting related hormones and the like) of the sleep monitor can basically meet the daily sleep treatment requirements of the user. However, such portable sleep monitors have very limited detection accuracy and precision compared to medical grade sleep monitors, through which one or more of the self-determined sleep cycle, sleep quality index, sleep efficiency, latency, sleep fragmentation, and/or other metrics related to the user's sleep process are likely to be inaccurate.
In view of this, when a user is in a sleep process in a home environment, such a portable sleep monitor may give a sleep state evaluation result with a larger deviation result, and based on the wrong sleep state evaluation result, the sleep guidance advice provided by such a portable sleep monitor is often not reasonable enough, and in this case, the portable sleep monitor cannot not only provide the correct evaluation result for the user correctly, but also guide the user to enter a desired sleep state correctly through a reasonably effective means, and even under the execution of the wrong sleep guidance advice or assistance measure, the bad sleep state of the user may be aggravated, the tiredness thereof is increased, the biorhythm is unbalanced, and physical and mental health of the user is seriously affected and endangered.
According to a preferred embodiment, in order to solve the technical drawbacks of the existing portable and medical sleep monitors, the present invention provides a method for managing healthy sleep, comprising:
the first monitor determines a first sleep mode based on at least one sleep characteristic data related to a sleep duration of the subject.
The second monitor determines at least one second sleep pattern that fits the first sleep pattern based on at least one sleep characteristic data associated with a sleep duration of the subject.
In the determined second sleep mode, the second monitor determines a third sleep mode according to at least one piece of bioelectrical signal data related to the sleep duration of the person under test, and corrects at least one sleep state metric index contained in the first sleep mode based on the third sleep mode.
In particular, in view of the inherent shortcomings of most portable sleep monitors when used in a home state, the present invention utilizes a high precision and accuracy medical grade sleep monitor to correct a sleep pattern determined by the portable sleep monitor itself, while determining a sleep pattern of a user with the portable sleep monitor, at least one sleep pattern fitting to a sleep curve determined by the portable sleep monitor is determined by a monitoring device independent of the medical grade sleep monitor, such as detecting one or more sleep characteristic data of body temperature, motion, heart rhythm, and respiratory rate. In addition, in a state where a sleep mode having a high degree of fit to a sleep curve acquired by the portable sleep monitor is determined, the sleep mode of the user is determined again by a bioelectric signal (e.g., an electroencephalogram signal) acquired by the medical-grade sleep monitor, and the sleep mode determined by the portable sleep monitor is corrected based on the sleep mode determined by the bioelectric signal, such as one or more of a sleep quality index, a sleep efficiency, a sleep latency, sleep fragmentation, and/or other metrics are corrected to provide an accurate and reliable sleep state evaluation result to the user.
Further, the sleep mode determined by the portable sleep monitor is checked by the medical-grade sleep monitor, so that whether the sleep mode determined by the portable sleep monitor for household is correct or not can be judged with high precision, and reasonable and effective sleep auxiliary measures, such as time-varying magnetic fields or electric fields related to the sleep state of a user, can be provided based on the accurate sleep mode determination.
Specifically, the subject is placed in an occasion having a medical grade sleep monitor, such as a hospital, an advanced clinic, or the like, and a portable sleep monitor (first monitor as described above) and a medical grade sleep monitor (second monitor as 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 are in signal communication so as to interact with each other to share system data. Further, the sleep mode of the subject may be detected and determined by the portable sleep monitor and the medical grade sleep monitor, respectively, wherein the medical grade sleep monitor is to be used to determine at least one sleep mode fitting the sleep curve determined by the portable sleep monitor. In particular, the sleep pattern determined by the medical grade sleep monitor that fits the portable sleep monitor may be based on one or more of the same sleep characteristic data, the total sleep time determined by both, the start-stop node and corresponding time of each individual sleep stage, and the value or rate of change of one or more sleep state data in each sleep stage.
Second, while 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 is able to determine/acquire at least another sleep pattern associated with the subject based on the acquired bioelectric signals (e.g., brain electrical signals). In particular, in view of the excellent detection accuracy of the medical grade sleep monitor, the controller may modify at least one evaluation index (e.g., sleep quality index, sleep efficiency, sleep latency, etc.) included in the sleep mode 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 performs sleep state monitoring on a home-use occasion, for example, only by using the portable sleep monitor, the portable sleep monitor corrects the data in the current sleep mode with the sleep state measurement index in the same sleep period determined by the medical-level sleep monitor as a reference value to obtain a more accurate sleep state evaluation result. In other words, each sleep state measurement index in the sleep state evaluation result obtained by the portable sleep monitor is corrected by the medical-grade sleep monitor.
According to a preferred embodiment, the sleep states of the testee are detected by the portable sleep monitor and the medical grade sleep monitor to determine corresponding sleep modes, and the sleep mode determination result obtained by the medical grade sleep monitor is used for correcting one or more sleep state evaluation indexes in the sleep modes determined by the portable sleep monitor, so that the testee can undergo one or more complete sleep cycle periods, and therefore, a plurality of sleep modes possibly generated by the testee under different sleep environments (including different situations, physiological factors and external interference factors) and differentiation of various sleep state measurement indexes in different sleep cycle periods can be determined.
Further, according to the sleep mode determined by the medical grade sleep monitor, various sleep modes and/or sleep state measurement indexes under the sleep cycle period determined by the portable sleep monitor can be respectively corrected, and correction results can be fed back and stored in the portable sleep monitor so as to improve the detection accuracy of the portable sleep monitor. In addition, accurate sleep state assessment results also help to verify the relationship between sleep quality and recovery of patients with sleep disorders and other diseases.
According to a preferred embodiment, based on the degree of difference between the at least one other sleep mode determined by the medical-grade sleep monitor according to the bioelectrical signal and the at least one sleep mode determined by the portable sleep monitor, the controller is capable of correcting the sleep-state metric index related to the sleep mode determined by the portable sleep monitor based on the sleep-state metric index in the sleep mode determined by the medical-grade sleep monitor, and transmitting the corrected sleep-state evaluation result related to each sleep-state metric index to the portable sleep monitor for storage. In particular, modifying the relevant sleep state metrics in the sleep mode determined by the portable sleep monitor in accordance with the sleep state metrics in the sleep mode determined by the medical grade sleep monitor may be based on a preset modification program/algorithm, machine learning, or healthcare worker setting.
On the other hand, with today's increasingly intelligent sleep monitoring devices and methods, whether portable or medical grade sleep monitors, generally when determining a sleep mode or sleep state of a subject, both may form a sleep aid regimen associated with the determined sleep mode based on one or more sleep state metrics contained in the sleep mode. Specifically, the sleep assisting scheme is to apply a magnetic field or an electric field capable of affecting the sleep state of the subject by means of a magnetic field unit or an electric stimulation unit built in the instrument, for example. In particular, based on accurate sleep state assessment reports, these data can be used to form an adjuvant therapy regime for improving the poor sleep state of the subject. Further, these adjuvant therapy regimens can be used to improve the sleep quality of the subject by initiating or executing them at the appropriate times. More importantly, in addition to improving sleep quality, these sleep aid regimens may have potentially positive effects in promoting the absorption of certain drugs during sleep stages.
According to a preferred embodiment, the sleep state monitoring result of the portable sleep monitor is corrected according to the sleep state monitoring result of the medical grade sleep monitor, and a corresponding sleep assistance scheme is formed according to the corrected sleep state monitoring result and stored in the portable sleep monitor, so that a person to be tested can complete more accurate and effective sleep assistance treatment at home through the portable sleep monitor without entering a state of a hospital, a high-grade clinic or the like with an expensive medical grade sleep monitor. In particular, these adjuvant therapy regimens may be initiated in advance by the subject or timed before the patient falls asleep. Alternatively, during real-time monitoring of the portable sleep monitor, these auxiliary treatment protocols may be initiated in one or more specific sleep stages as determined by the portable sleep monitor.
According to a preferred embodiment, the simulated bioelectricity wave can be synthesized by using low-frequency electromagnetic stimulation and digital frequency to act on the tested person so as to achieve the effect of assisting sleep. Specifically, for example, when the portable sleep monitor determines that the subject enters a light sleep stage, a magnetic field and/or an electric field of a first frequency may be applied to the head or hand of the subject by the handheld or head-mounted portable sleep monitor for accelerating the sleep-inducing process of the subject. Alternatively, when the portable sleep monitor determines that the subject enters a deep sleep stage, a second frequency magnetic field and/or electric field may be applied to the subject's head or hand by the hand-held or head-mounted portable sleep monitor for extending the deep sleep time. In view of the different manifestations of brain waves and other physiological indicators in different sleep states, the corresponding auxiliary treatment schemes of each sleep stage have different configuration parameters, such as current/magnetic field intensity, frequency, duration and the like.
According to a preferred embodiment, in a sleep-aiding scheme for aiding a subject to sleep using a sleep monitor having a sleep-aiding function such as a first monitor (e.g., a portable sleep monitor) and/or a second monitor (e.g., a medical-grade sleep monitor), receptors such as the median nerve, radial nerve, and/or ulnar nerve of the subject may be stimulated with alternating current to modulate corresponding brain regions (e.g., hypothalamus) in the cranium by nerve sensation, thereby achieving insomnia-aiding treatment.
It should be noted that the above-described embodiments are exemplary, and that a person skilled in the art, in light of the present disclosure, may devise various solutions that fall within the scope of the present disclosure and fall within the scope of the present disclosure. It should be understood by those skilled in the art that the present description is illustrative and not limiting to the claims. The scope of the invention is defined by the claims and their equivalents. The description of the invention encompasses multiple inventive concepts, such as "preferably," "according to a preferred embodiment," or "optionally," all means that the corresponding paragraph discloses a separate concept, and that the applicant reserves the right to filed a divisional application according to each inventive concept.
Claims (10)
1. A healthy sleep management system, comprising:
a first monitor operatively attached to the user for acquiring at least one item of sleep characteristic data of the user related to time and determining a first sleep mode based on the at least one item of sleep characteristic data;
a second monitor operatively attached to the user for acquiring at least one item of sleep characteristic data and/or bioelectric signal data of the user in said first sleep mode and determining at least one second sleep mode fitted to said first sleep mode based on said at least one item of sleep characteristic data, and in said determined second sleep mode, determining a third sleep mode based on said bioelectric signal data,
wherein the second monitor is capable of modifying at least one sleep state metric comprised by the first sleep mode based on the third sleep mode.
2. The healthy sleep management system according to claim 1, wherein the second monitor is capable of providing at least one adjuvant therapy regime associated with a sleep stage of a user to the first monitor based on at least one sleep state metric associated with a first sleep mode modified according to the third sleep mode.
3. A healthy sleep management system according to claim 1 or 2, wherein the adjuvant therapy regime is initiated in advance or at regular times before the user enters a sleep session, or in one or more sleep stages as determined by the first monitor.
4. A healthy sleep management system according to any one of claims 1-3, characterized in that, the determining at least one second sleep mode fitted to the first sleep mode based on the at least one sleep characteristic data, and in the determined second sleep mode, determining a third sleep mode based on the bioelectric signal data comprises subjecting the user to a plurality of sleep cycle periods.
5. The healthy sleep management system according to any one of claims 1-4, wherein determining a sleep mode based on the at least one sleep characteristic data comprises:
processing the data waveform corresponding to the at least one sleep characteristic data into a plurality of segmented waveforms;
extracting at least one sleep characteristic data in each segmented waveform;
dividing sleep stages of the user according to at least one sleep characteristic data in each segmented waveform;
and acquiring the sum of the sleep states of the users based on the classified sleep stages of the users to determine a sleep mode.
6. The healthy sleep management system according to any one of claims 1-5, wherein the sleep state metric comprises one or more of a sleep quality index, a sleep cycle, a sleep efficiency, a sleep latency, and a sleep segment.
7. The healthy sleep management system according to any one of claims 1-6, wherein the at least one sleep characteristic data comprises one or more of body temperature, exercise, heart rhythm, and respiratory rate.
8. The healthy sleep management system according to any one of claims 1 to 7, wherein the first monitor and/or second monitor comprises:
the acquisition module is used for acquiring at least one sleep state characteristic data and/or bioelectric signal data representing the sleep state of the user;
a processing module capable of determining a sleep state assessment result associated with the user in response to at least one item of sleep state characteristic data and/or bioelectric signal data acquired from the acquisition module;
and the output module is used for outputting the sleep state evaluation result which is related to the user and comes from the processing module.
9. A method of healthy sleep management, comprising:
Providing a first monitor and a second monitor capable of bi-directional communication;
the first monitor determines a first sleep mode according to at least one sleep characteristic data related to a sleep duration of the user;
a second monitor determines at least one second sleep mode fitting the first sleep mode according to at least one sleep characteristic data related to the sleep time of the user;
in the determined second sleep mode, the second monitor determines a third sleep mode from at least one piece of bioelectrical signal data related to the sleep duration of the user and modifies at least one sleep state metric index contained in the first sleep mode based on the third sleep mode.
10. The method of healthy sleep management according to claim 9, further comprising:
providing at least one auxiliary treatment regimen associated with a sleep stage of the user to the first monitor based on at least one sleep state metric associated with the first sleep mode modified according to the third sleep mode.
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