CN106073714A - The recognition methods of a kind of sleep quality and system - Google Patents
The recognition methods of a kind of sleep quality and system Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4815—Sleep quality
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02405—Determining heart rate variability
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4809—Sleep detection, i.e. determining whether a subject is asleep or not
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4812—Detecting sleep stages or cycles
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/681—Wristwatch-type devices
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7271—Specific aspects of physiological measurement analysis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/7455—Details of notification to user or communication with user or patient ; user input means characterised by tactile indication, e.g. vibration or electrical stimulation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
Abstract
The invention provides recognition methods and the system of a kind of sleep quality, including terminal, described terminal includes: high-precision sensor module, is used for experiencing pulse and action, and changes into the signal of telecommunication；Recorder Modules, for receiving the signal of telecommunication of described high-precision sensor module, and stores record；Acquisition module, mode manually inputs the subjective index of user self；Processor module, for the data of Recorder Modules are processed, and/or, the data of acquisition module are processed.Present invention have the advantage that large-scale instrument and professional that the method avoids objective analysis method to need, also avoid the subjective randomness using merely subjective analysis method to cause simultaneously, the feature that the degree that is affected by human factors is high, the most subjective and objective combination is evaluated, make this evaluation more science with comprehensive, the method is reasonable in design, and it is simple, convenient to use, the most practical.
Description
Technical field
The present invention relates to recognition methods and the system of a kind of sleep quality, belong to Domestic health-care instrument and equipment technical field.
Background technology
Along with modern life rhythm accelerate, competitive pressure increases day by day, increasing people sleep be affected, sleep with
The live and work of people is closely related, and therefore the research of sleep quality monitoring and evaluation increasingly comes into one's own.The most urgent
Need New Research Method and new technique with assessment sleep quality quality, be aided with and scientifically instruct, so to improving sleep quality meeting
It is very helpful.
What objective evaluation sleep quality application at present was more is to utilize polysomnogram machine to monitor electroencephalogram, electrocardiogram, flesh
The various physiological parameter such as electrograph, blood oxygen saturation is that index is evaluated.The data acquisition of this evaluation is the most comfortable
Time when monitoring late 11 at environment such as room temperature 25 DEG C to morning 7, without the full dormant data of the lower 8h of illumination.Every example gathers 12 segment datas,
Every section of 40min.By sleep stage standard in the world, intercept the different electroencephalogram of sleep period, electrocardiogram, electromyogram, blood oxygen saturation
The each 20s of data such as degree carry out complexity calculations.This evaluation methodology needs large-scale instrument and equipment and the medical worker of specialty,
Therefore these evaluation meanses must go to hospital and could realize.It is unfavorable for people's self evaluation the quickest, simple.City now
On field, the house Sleep Evaluation product of exploitation mainly includes Lunar intelligent sleep recorder and fragrant citrus Intelligent pillow button, can carry out
Sleep cycle detects；Easily sleep intelligent sleep management and can detect heart rate, breathing rate, the length of one's sleep and quality；Protect sleep precious and
Reston intelligent sleep monitor can breathing in monitoring sleep in real time, heart beating, stand up, from the change of bed.The most external
Sense sensor can also detect the humidity in bedroom, light, sound, temperature and air particles situation except detection sleep quality.
The most subjective evaluation methodology is to be slept by Sleep Quality Index scale detection such as the most representational Pittsburgh
Dormancy performance figure, it needs to add up experimenter's sleep quality of 1 month.Assessment variable includes sleep quality, from awakening to sleep
Transition time, sleep duration, Sleep efficiency, sleep disordered situation, medicining condition, next day physical function obstacle totally 7 factors,
From 0 (without difficulty), to 3 (exceptional hardships), the value span finally given is 0 to 21 to weights, is worth the biggest explanation sleep quality more
Difference.This evaluation methodology subjectivity is the strongest, it is impossible to objective comprehensive evaluation sleep quality.
The present invention sets up the assessment system of sleep quality, this system combination evaluation methodology of subjective and objective combination.Whole
The method for objectively evaluating of the subjectivity stated and the residential use of closing, utilizes the physiological parameter collected and user to fill in sleep matter
Amount questionnaire survey combines the sleep quality to individual and is made that the assessment of a science.
Summary of the invention
It is an object of the invention to provide a kind of integrated evaluating method of conveniently, simply sleeping, the method avoids objective analysis
The large-scale instrument of method needs and professional, also avoid the subjective randomness using merely subjective analysis method to cause, by people simultaneously
For the feature that factor influence degree is high, the sleep quality assessment for health care and treatment insomnia crowd provides foundation.
For reaching above-mentioned purpose, the present invention implements by the following technical programs:
A kind of identification system of sleep quality, including terminal, described terminal includes:
High-precision sensor module, is used for experiencing pulse and action, and changes into the signal of telecommunication；
Recorder Modules, for receiving the signal of telecommunication of described high-precision sensor module, and stores record；
Acquisition module, mode manually inputs the subjective index of user self；
Processor module, for the data of Recorder Modules are processed, and/or, the data of acquisition module are carried out
Process.
Further, described terminal also includes:
Battery, for powering to monitoring system；
Vibrator module, is used for providing vibration to remind user.
Described action include heart rate, stand up, breathing rate, from bed etc..
The described signal of telecommunication includes analogue signal and digital signal, and the signal of telecommunication that wherein pulse is corresponding is digital signal, action
Corresponding signal is analogue signal.
The information of described acquisition module collection includes age, sleep peace, sleep complexity, journey of bestirring oneself of waking up
Degree, sleep satisfaction, evening are waken up frequency.
The recognition methods of a kind of sleep quality, uses the above sleep quality monitoring system, by described terminal band in inspection
In the wrist of survey person, the high-precision sensor in terminal is followed by the pulse of examined person and operating frequency change is believed as sensor
Number output to logging modle, after the data in one cycle of record, is sent to processing module；Processing module processes data and analysis is slept
Dormancy quality is to objective indicator assignment.
Preferably, also including, user inputs subjective index to acquisition module, processor carry out after index being carried out assignment
Calculating processes.
Preferably, assignment table is also included:
1) sleep peace according to the frequency stood up in sleep judge 0 time as the tranquilest, comparison is the tranquilest for 1-2 time, one
As be 3-4 time, somewhat uncalm for 5-8 time, do not have a rest completely good for more than 8 times；
2) complexity fallen asleep judges that basis is easily sleep and is less than 5 minutes, is easier as more than or equal to 5 points
Clock, less than 10 minutes, be difficult to not embarrass more than or equal to 10 minutes, less than 20 minutes, compare and embarrass more than or equal to 20 minutes, be less than
30 minutes, embarrass very much more than or equal to 30 minutes；
3) satisfaction of sleeping judges that judging that quite satisfaction refers to sleep the total time according to sleep is more than 7 hours total time,
Satisfied is more than 6 hours, less than or equal to 7 hours, typically greater than 5 hours, less than or equal to 6 hours, and less satisfaction is big
In 4 hours, less than or equal to 5 hours, it is discontented with very much and means less than or equal to 4 hours；
4) frequency that sleep is waken up is rarely 1 time, is 2 times once in a while, frequently larger than 2 times, is continuously and can not fall asleep always.
Investigation on sleep quality
Sleep quality data analysis
Subjective-objective Combination of the present invention evaluates the integrated evaluating method of sleep quality compared with prior art, has the most excellent
Point: the method avoids large-scale instrument and the professional that objective analysis method needs, and also avoids using merely subjective analysis method simultaneously
That causes is subjective random, and the feature that the degree that is affected by human factors is high, the most subjective and objective combination is evaluated, and makes this evaluation more
The science that adds is with comprehensively, and the method is reasonable in design, and it is simple, convenient to use, the most practical.Can be for health care and treatment insomnia crowd
Sleep quality assessment provide foundation.
Accompanying drawing explanation
Below according to drawings and Examples, the present invention is described in further detail.
Fig. 1 is the sleep quality regression analysis of 20 ± 3.0 years old group.
Fig. 2 is that 20 ± 3.0 years old group δ wave band accounts for the percentage ratio of total wave band of sleeping.
Fig. 3 is the sleep quality regression analysis of 30 ± 3.0 years old group.
Fig. 4 is that 30 ± 3.0 years old group δ wave band accounts for the percentage ratio of total wave band of sleeping.
Fig. 5 is the sleep quality regression analysis of 40 ± 3.0 years old group.
Fig. 6 is that 40 ± 3.0 years old group δ wave band accounts for the percentage ratio of total wave band of sleeping.
Fig. 7 is the sleep quality regression analysis of 50 ± 3.0 years old group.
Fig. 8 is that 50 ± 3.0 years old group δ wave band accounts for the percentage ratio of total wave band of sleeping.
Fig. 9 is the sleep quality regression analysis of 60 ± 3.0 years old group.
Figure 10 is that 60 ± 3.0 years old group δ wave band accounts for the percentage ratio of total wave band of sleeping.
Detailed description of the invention
Embodiment that of the present invention Subjective-objective Combination evaluate the integrated evaluating method of sleep quality is given below.
1, sleep quality comprehensive evaluation index is chosen
Actual carry out sleep quality assessment time, owing to the object evaluated is different, to the superior and inferior evaluating of sleep quality be also
Different.Comprehensive evaluation index the most how is selected to be by the important step of sleep quality assessment.Generally should follow following
Principle:
1) comprehensive, the most comprehensive during index for selection.
2) the easy property answered, the index chosen should be prone to user and understand and answer accurately.
3) dependency, between the index chosen, dependency is the least.
First subjective guideline is selected to include age, sleep peace, sleep complexity, wake up according to above principle
Bestir oneself degree, sleep satisfaction, evening is waken up frequency 5 indexs totally.
Medical research finds that heart rate variability is regulated and controled by autonomic nerve, is that the sensitivity of reflection Autonomic nerve block change refers to
Mark.Stable sleep state is often with higher heart rate variability, and the sleep state of instability is often with the higher heart
Rate variability.Heart rate variability high band intensity and sleep quality positive correlation, heart rate variability low-frequency range intensity and sleep quality
Inverse correlation.As long as and monitor heart rate is worn suitable terminal and is achieved that monitoring at home in sleep.In addition terminal is detected
Breathing rate can also be realized in addition to heart rate, stand up, from the detection of bed.Therefore we select heart rate, breathing rate, stand up, from bed work
For evaluating the foundation of the objective indicator assignment of sleep quality.
2, the subjective index of the sleep quality overall merit chosen is carried out assignment；
Based on the subjective evaluation index above established, simultaneously in order to meet the questionnaire survey of reality, questionnaire content includes 5
Index is shown in Table 1.
Table 1 Investigation on sleep quality
3, use heart rate, breathing rate, stand up, from bed monitoring, the objective indicator of sleep quality carried out assignment；
First, collect sleep action data, heart rate and breathing rate data by the terminal of intelligent sleep glasses, and record number
According to.Speed order awakening rapid eye movement phase ＞, ＞ phase according to whole sleep cycle heart rate is shallow sleeps sound sleep phase phase ＞ and each phase exhales
The change of suction rate and sleep action by the data that recorded by stages, counts the overall duration of each Sleep stages, sound sleep
The ratio in sleep cycle of dormancy, fall asleep need time, wake up persistent period totally 4 indexs carry out scoring and be shown in Table every time
2。。
Table 2 sleep quality data analysis
4, the comprehensive evaluation value of sleep quality is calculated with Logistic regression analysis.
Based on logistic regression model, set up sleep quality risk evaluation model: logit (P)=Ln (P/1-P)
=alpha+beta1χ1+β2χ2+...+βiχi+....+βnχn, wherein P is sleep quality assessment value, and α is constant, X1、X2...Xi... .Xn divides
Do not represent the 1st .i....n the risk factor in 2 ..., βiFor the regression coefficient of risk factor with LnORiEstimate.Use SAS statistics
Software carries out data process, carries out logistic regression analysis α=0.1.
5, embodiment checking
The present invention is to evaluate the integrated evaluating method of sleep quality, as the integrated evaluating method of sleep quality, and be with doctor
The electroencephalogram Comparison between detecting methods that institute is conventional, medical research shows that sleep cycle can be divided into the fourth phase according to EEG Characteristics, the
One phase, brain wave, based on θ ripple, is by the transition stage regained consciousness completely between sleep；The second phase belongs to rapid eye movement sleep, δ ripple
Less than 20%；The third phase is middle deep sleep, and δ ripple accounts for 20%-50%；The third phase is deep sleep, and δ ripple accounts for more than 50%.
Visible in preferably sleep δ wave band to account for the energy of brain wave the highest, therefore the δ wave band in brain wave can be slept as evaluation
The standard slept.The accuracy of method of proof is carried out with this evaluation example.
5.1 object choice
We select the crowd of different age group as study subject, and object of study derives from community or hospital.Tested right
As being divided into five groups according to the age, respectively 20 ± 3.0 years old group, 30 ± 3.0 years old group, 40 ± 3.0 years old group, 50 ± 3.0 years old group, 60 ±
3.0 years old groups.Often group male 5 people, women 5 people.Participate in experiment voluntarily.Every experimenter's advance notice experimentation, at letter of consent
Upper signature.Experimenter is not allow for hypertension, asthma, diabetes and other serious disease medical histories, electrocardiographic abnormality, indulges in excessive drinking, inhales
Bad habits such as cigarette and have somnambulism experiencer.
5.2 experimentation
Experiment is carried out within the hospital, and experimenter wears cotton cotta jams, covers thin blanket.Indoor temperature is 24 ± 2 DEG C,
Humidity is 55 ± 5%.Experimenter arrives hospital, is 1 group No. 1-10 by volume, 2 groups No. 1-10,3 groups No. 1-10,4 groups No. 1-10,5
Organize No. 1-10, after peace and quiet are had a rest 30 minutes, experiment implementer paste physiological parameter probe and the end with good intelligent sleep glasses
End, 23:00 starts sleep, and next day, morning, 7:00 experimenter woke up, and filled in sleep quality questionnaire survey.Often group experimenter joins continuously
Add 3 experiments and take average.
5.3 interpretation of result
5.3.1 20 ± 3.0 years old group interpretation of result
1) subjective index assigned result
2) objective indicator assigned result
3) logistic analysis of regression model
The subjective and objective index of logistic regression model totally 9 factors, synthesis pertinence (merge OR value) is respectively as follows: 1.11,
1.67、2.02、1.09、3.97、2.82、5.27、3.10、2.40.Final model is Logit (P)=0.1+1.11X1+
1.67X2+2.02X3+1.09X4+3.97X5+2.82X6+5.27X7+3.10X8+2.40X9.By questionnaire survey and intelligent sleep eye
The data that the terminal of mirror is collected are brought regression model into and are obtained such as Fig. 1 result.Numerical value is the highest, and sleep quality is the best.
The percentage ratio of No. 4 and No. 9 δ ripples of 20 years old group is higher as can be seen from Fig. 2, and No. 8 relatively low.This returns with Logistic with us
The result returning the comprehensive evaluation value of analytical calculation is consistent.
5.3.2 30 ± 3.0 years old group interpretation of result
1) subjective index assigned result
2) objective indicator assigned result
3) logistic analysis of regression model
The subjective and objective index of logistic regression model totally 9 factors, synthesis pertinence (merge OR value) is respectively as follows: 1.11,
1.67、2.02、1.09、3.97、2.82、5.27、3.10、2.40.Final model is Logit (P)=0.1+1.11X1+
1.67X2+2.02X3+1.09X4+3.97X5+2.82X6+5.27X7+3.10X8+2.40X9.By questionnaire survey and intelligent sleep eye
The data that the terminal of mirror is collected are brought regression model into and are obtained such as Fig. 3 result.Numerical value is the highest, and sleep quality is the best.
From lower Fig. 4, the percentage ratio of No. 6 δ ripples of visible 30 years old group is higher, and No. 5 relatively low.This returns with Logistic with us
The result of the comprehensive evaluation value of analytical calculation is consistent.
5.3.3 40 ± 3.0 years old group interpretation of result
1) subjective index assigned result
2) objective indicator assigned result
3) logistic analysis of regression model
The subjective and objective index of logistic regression model totally 9 factors, synthesis pertinence (merge OR value) is respectively as follows: 1.11,
1.67、2.02、1.09、3.97、2.82、5.27、3.10、2.40.Final model is Logit (P)=0.1+1.11X1+
1.67X2+2.02X3+1.09X4+3.97X5+2.82X6+5.27X7+3.10X8+2.40X9.By questionnaire survey and intelligent sleep eye
The data that the terminal of mirror is collected are brought regression model into and are obtained such as Fig. 5 result.Numerical value is the highest, and sleep quality is the best.
From lower Fig. 6, the percentage ratio of No. 1 and No. 8 δ ripple of visible 40 years old group is higher, and 9, No. 10 relatively low.This uses with us
The result of the comprehensive evaluation value that Logistic regression analysis calculates is consistent.
5.3.4 50 ± 3.0 years old group interpretation of result
1) subjective index assigned result
2) objective indicator assigned result
3) logistic analysis of regression model
The subjective and objective index of logistic regression model totally 9 factors, synthesis pertinence (merge OR value) is respectively as follows: 1.11,
1.67、2.02、1.09、3.97、2.82、5.27、3.10、2.40.Final model is Logit (P)=0.1+1.11X1+
1.67X2+2.02X3+1.09X4+3.97X5+2.82X6+5.27X7+3.10X8+2.40X9.By questionnaire survey and intelligent sleep eye
The data that the terminal of mirror is collected are brought regression model into and are obtained such as Fig. 7 result.Numerical value is the highest, and sleep quality is the best.
From lower Fig. 8, the percentage ratio of No. 6 and No. 7 δ ripples of visible 50 years old group is higher, and 4 and No. 8 relatively low.This uses with us
The result of the comprehensive evaluation value that Logistic regression analysis calculates is consistent.
5.3.5 60 ± 3.0 years old group interpretation of result
1) subjective index assigned result
2) objective indicator assigned result
3) logistic analysis of regression model
The subjective and objective index of logistic regression model totally 9 factors, synthesis pertinence (merge OR value) is respectively as follows: 1.11,
1.67、2.02、1.09、3.97、2.82、5.27、3.10、2.40.Final model is Logit (P)=0.1+1.11X1+
1.67X2+2.02X3+1.09X4+3.97X5+2.82X6+5.27X7+3.10X8+2.40X9.By questionnaire survey and intelligent sleep eye
The data that the terminal of mirror is collected are brought regression model into and are obtained such as Fig. 9 result.Numerical value is the highest, and sleep quality is the best.
The percentage ratio of No. 4 and No. 7 δ ripples of 60 years old group is higher as can be seen from Fig. 10, and No. 6 relatively low.This uses Logistic with us
The result of the comprehensive evaluation value that regression analysis calculates is consistent.
By utilizing Logistic regression analysis to calculate sleep quality seen from the confirmatory experiment of five set different age group
It is a kind of convenience, the method for evaluation sleep quality convenient, reliable.
Last it is noted that the foregoing is only the preferred embodiment of invention, it is not limited to invention, although
Being described in detail invention with reference to previous embodiment, for a person skilled in the art, it still can be to front
State the technical scheme described in each embodiment to modify, or wherein portion of techniques feature is carried out equivalent.All send out
Within bright spirit and principle, any modification, equivalent substitution and improvement etc. made, should be included in invention protection domain it
In.
Claims (8)
1. an identification system for sleep quality, including terminal, it is characterised in that described terminal includes:
High-precision sensor module, is used for experiencing pulse and action, and changes into the signal of telecommunication；
Recorder Modules, for receiving the signal of telecommunication of described high-precision sensor module, and stores record；
Acquisition module, mode manually inputs the subjective index of user self；
Processor module, for the data of Recorder Modules are processed, and/or, the data of acquisition module are processed.
2. the system as claimed in claim 1, it is characterised in that described terminal also includes:
Battery, for powering to monitoring system；
Vibrator module, is used for providing vibration to remind user.
3. the system as claimed in claim 1, it is characterised in that described action include heart rate, stand up, breathing rate, from bed etc..
4. the system as described in one of claim 1-3, it is characterised in that the described signal of telecommunication includes analogue signal and numeral letter
Number, the signal of telecommunication that wherein pulse is corresponding is digital signal, and signal corresponding to action is analogue signal.
5. the system as described in one of claim 1-4, it is characterised in that the information of described acquisition module collection include the age,
Sleep peace, sleep complexity, bestir oneself degree, the sleep of waking up satisfaction, evening are waken up frequency.
6. a recognition methods for sleep quality, uses the above sleep quality monitoring system, by described terminal band in detection
In the wrist of person, the high-precision sensor in terminal is followed by the pulse of examined person and operating frequency changes as sensor signal
Output, to logging modle, after the data in one cycle of record, is sent to processing module；Processing module processes data and analyzes sleep
Quality is to objective indicator assignment.
7. method as claimed in claim 6, it is characterised in that also including, user inputs subjective index to acquisition module, by
Reason device carries out calculating process after index is carried out assignment.
8. method as claimed in claim 6, it is characterised in that also include assignment table:
1) sleep peace according to the frequency stood up in sleep judge 0 time as the tranquilest, comparison is the tranquilest for 1-2 time, is generally
3-4 time, somewhat uncalm for 5-8 time, do not have a rest completely good for more than 8 times；
2) complexity fallen asleep judges according to being easily sleep less than 5 minutes, be easier into more than or equal to 5 minutes, little
In 10 minutes, it is difficult to not embarrass more than or equal to 10 minutes, less than 20 minutes, compares and embarrass more than or equal to 20 minutes, less than 30 points
Clock, embarrassed more than or equal to 30 minutes very much；
3) sleep satisfaction judges to judge that quite satisfied finger more than 7 hours, is compared sleep total time the total time according to sleep
Satisfied for more than 6 hours, less than or equal to 7 hours, typically greater than 5 hours, less than or equal to 6 hours, less satisfied for little more than 4
Time, less than or equal to 5 hours, very discontented mean less than or equal to 4 hours；
4) frequency that sleep is waken up is rarely 1 time, is 2 times once in a while, frequently larger than 2 times, is continuously and can not fall asleep always.
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| CN107910054A (en) * | 2017-11-10 | 2018-04-13 | 泰康保险集团股份有限公司 | Sleep state determines method and device, storage medium and electronic equipment |
| CN108042108A (en) * | 2017-12-06 | 2018-05-18 | 中国科学院苏州生物医学工程技术研究所 | A kind of sleep quality monitoring method and system based on body shake signal |
| CN109199336A (en) * | 2018-09-30 | 2019-01-15 | 深圳个人数据管理服务有限公司 | A kind of sleep quality quantization method, device and equipment based on machine learning |
| CN109199350A (en) * | 2018-09-30 | 2019-01-15 | 浙江凡聚科技有限公司 | Sleep disturbance based on virtual reality situation is comprehensive to survey method for training and system |
| CN109222935A (en) * | 2018-11-01 | 2019-01-18 | 广东工业大学 | A kind of method and system judging sleep quality of human body based on UWB sensor |
| CN110037653A (en) * | 2018-01-17 | 2019-07-23 | 广东乐心医疗电子股份有限公司 | Sleep quality evaluation method and device for portable intelligent wearable equipment |
| CN110366387A (en) * | 2017-02-27 | 2019-10-22 | 博能电子公司 | Measurement and assessment sleep quality |
| CN111166297A (en) * | 2020-02-19 | 2020-05-19 | 赛博龙科技(北京)有限公司 | Method and device for evaluating sleep quality based on user sleep audio |
| CN111588630A (en) * | 2020-05-27 | 2020-08-28 | 深圳市安瑞国医科技有限公司 | Percutaneous nerve regulation and control strategy generation method and device |
| CN111867429A (en) * | 2018-03-07 | 2020-10-30 | Icbs有限公司 | Sleep environment adjusting device using reinforcement learning |
| CN115413236A (en) * | 2020-03-31 | 2022-11-29 | Infic株式会社 | Out-of-bed prediction notification device and program |
| CN116313090A (en) * | 2023-03-16 | 2023-06-23 | 上海外国语大学 | Sleep disorder risk assessment method and system based on resting state electroencephalogram data |
| CN116612894A (en) * | 2023-07-21 | 2023-08-18 | 北京中科心研科技有限公司 | Method and device for identifying sleep disorder and wearable equipment |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060020178A1 (en) * | 2002-08-07 | 2006-01-26 | Apneos Corp. | System and method for assessing sleep quality |
| US20100152546A1 (en) * | 2008-12-15 | 2010-06-17 | Julie Behan | Monitoring Sleep Stages to Determine Optimal Arousal Times and to Alert an Individual to Negative States of Wakefulness |
| CN102224503A (en) * | 2008-09-24 | 2011-10-19 | 比安卡医疗有限公司 | Contactless and minimal-contact monitoring of quality of life parameters for assessment and intervention |
| CN103780691A (en) * | 2014-01-20 | 2014-05-07 | 辛志宇 | Intelligent sleep system, user side system of intelligent sleep system, and cloud system of intelligent sleep system |
| CN104053397A (en) * | 2012-01-20 | 2014-09-17 | 欧姆龙健康医疗事业株式会社 | Sleep Display Program, Sleep Display Method And Sleep Display Device |
-
2016
- 2016-06-24 CN CN201610465633.9A patent/CN106073714A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060020178A1 (en) * | 2002-08-07 | 2006-01-26 | Apneos Corp. | System and method for assessing sleep quality |
| CN102224503A (en) * | 2008-09-24 | 2011-10-19 | 比安卡医疗有限公司 | Contactless and minimal-contact monitoring of quality of life parameters for assessment and intervention |
| US20100152546A1 (en) * | 2008-12-15 | 2010-06-17 | Julie Behan | Monitoring Sleep Stages to Determine Optimal Arousal Times and to Alert an Individual to Negative States of Wakefulness |
| CN104053397A (en) * | 2012-01-20 | 2014-09-17 | 欧姆龙健康医疗事业株式会社 | Sleep Display Program, Sleep Display Method And Sleep Display Device |
| CN103780691A (en) * | 2014-01-20 | 2014-05-07 | 辛志宇 | Intelligent sleep system, user side system of intelligent sleep system, and cloud system of intelligent sleep system |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110366387A (en) * | 2017-02-27 | 2019-10-22 | 博能电子公司 | Measurement and assessment sleep quality |
| CN110366387B (en) * | 2017-02-27 | 2022-09-27 | 博能电子公司 | Measuring and assessing sleep quality |
| CN107910054A (en) * | 2017-11-10 | 2018-04-13 | 泰康保险集团股份有限公司 | Sleep state determines method and device, storage medium and electronic equipment |
| CN108042108A (en) * | 2017-12-06 | 2018-05-18 | 中国科学院苏州生物医学工程技术研究所 | A kind of sleep quality monitoring method and system based on body shake signal |
| CN110037653A (en) * | 2018-01-17 | 2019-07-23 | 广东乐心医疗电子股份有限公司 | Sleep quality evaluation method and device for portable intelligent wearable equipment |
| CN111867429A (en) * | 2018-03-07 | 2020-10-30 | Icbs有限公司 | Sleep environment adjusting device using reinforcement learning |
| CN109199350B (en) * | 2018-09-30 | 2021-04-30 | 浙江凡聚科技有限公司 | Sleep disorder comprehensive testing and training method and system based on virtual reality situation |
| CN109199336A (en) * | 2018-09-30 | 2019-01-15 | 深圳个人数据管理服务有限公司 | A kind of sleep quality quantization method, device and equipment based on machine learning |
| CN109199350A (en) * | 2018-09-30 | 2019-01-15 | 浙江凡聚科技有限公司 | Sleep disturbance based on virtual reality situation is comprehensive to survey method for training and system |
| CN109222935A (en) * | 2018-11-01 | 2019-01-18 | 广东工业大学 | A kind of method and system judging sleep quality of human body based on UWB sensor |
| CN111166297B (en) * | 2020-02-19 | 2022-09-06 | 赛博龙科技(北京)有限公司 | Method and device for evaluating sleep quality based on user sleep audio |
| CN111166297A (en) * | 2020-02-19 | 2020-05-19 | 赛博龙科技(北京)有限公司 | Method and device for evaluating sleep quality based on user sleep audio |
| CN115413236A (en) * | 2020-03-31 | 2022-11-29 | Infic株式会社 | Out-of-bed prediction notification device and program |
| CN111588630B (en) * | 2020-05-27 | 2022-07-12 | 深圳市安瑞国医科技有限公司 | Percutaneous nerve regulation and control strategy generation method and device |
| CN111588630A (en) * | 2020-05-27 | 2020-08-28 | 深圳市安瑞国医科技有限公司 | Percutaneous nerve regulation and control strategy generation method and device |
| CN116313090A (en) * | 2023-03-16 | 2023-06-23 | 上海外国语大学 | Sleep disorder risk assessment method and system based on resting state electroencephalogram data |
| CN116612894A (en) * | 2023-07-21 | 2023-08-18 | 北京中科心研科技有限公司 | Method and device for identifying sleep disorder and wearable equipment |
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