CN106725382A - Sleep state judgement system and method based on action and HRV measurements - Google Patents
Sleep state judgement system and method based on action and HRV measurements Download PDFInfo
- Publication number
- CN106725382A CN106725382A CN201611236012.XA CN201611236012A CN106725382A CN 106725382 A CN106725382 A CN 106725382A CN 201611236012 A CN201611236012 A CN 201611236012A CN 106725382 A CN106725382 A CN 106725382A
- Authority
- CN
- China
- Prior art keywords
- heart rate
- computing module
- sleep
- sleep state
- hrv
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000007958 sleep Effects 0.000 title claims abstract description 81
- 230000009471 action Effects 0.000 title claims abstract description 42
- 238000000034 method Methods 0.000 title claims description 23
- 238000005259 measurement Methods 0.000 title abstract description 14
- 230000008859 change Effects 0.000 claims abstract description 31
- 230000001133 acceleration Effects 0.000 claims abstract description 24
- 230000003860 sleep quality Effects 0.000 claims abstract description 12
- 230000003287 optical effect Effects 0.000 claims abstract description 11
- 210000004204 blood vessel Anatomy 0.000 claims abstract description 7
- 230000017531 blood circulation Effects 0.000 claims abstract description 5
- 238000001514 detection method Methods 0.000 claims abstract description 4
- 230000009885 systemic effect Effects 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 7
- 230000036385 rapid eye movement (rem) sleep Effects 0.000 claims description 4
- 230000002618 waking effect Effects 0.000 claims description 3
- 238000010183 spectrum analysis Methods 0.000 claims description 2
- 230000005059 dormancy Effects 0.000 claims 2
- 230000000630 rising effect Effects 0.000 claims 1
- 230000000392 somatic effect Effects 0.000 claims 1
- 238000012544 monitoring process Methods 0.000 abstract description 3
- 230000036541 health Effects 0.000 abstract description 2
- 210000003414 extremity Anatomy 0.000 description 22
- 210000004556 brain Anatomy 0.000 description 6
- 210000000707 wrist Anatomy 0.000 description 5
- 239000008280 blood Substances 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
- 210000000038 chest Anatomy 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 208000013738 Sleep Initiation and Maintenance disease Diseases 0.000 description 1
- 208000032140 Sleepiness Diseases 0.000 description 1
- 206010041349 Somnolence Diseases 0.000 description 1
- 210000001015 abdomen Anatomy 0.000 description 1
- 210000003423 ankle Anatomy 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 206010022437 insomnia Diseases 0.000 description 1
- 208000030523 mesoaxial synostotic syndactyly with phalangeal reduction Diseases 0.000 description 1
- 230000001766 physiological effect Effects 0.000 description 1
- 230000035790 physiological processes and functions Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 238000012706 support-vector machine Methods 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
Classifications
-
- 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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
-
- 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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
-
- 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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
- A61B5/024—Measuring pulse rate or heart rate
- A61B5/02405—Determining heart rate variability
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
-
- 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
-
- 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
- A61B2562/02—Details of sensors specially adapted for in-vivo measurements
- A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Molecular Biology (AREA)
- General Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Veterinary Medicine (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Physics & Mathematics (AREA)
- Public Health (AREA)
- Cardiology (AREA)
- Physiology (AREA)
- Anesthesiology (AREA)
- Pulmonology (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention discloses a kind of sleep state judgement system based on action and HRV measurements, including 3-axis acceleration sensor module, limb action number computing module, optical sensor module, pulse wave signal computing module, heart rate and heartbeat interval computing module, heart rate variability metrics computing module, the sleep state computing module for sequentially connecting.Collect human body limb three-dimensional acceleration data in setting time；Calculate the limb action quantity within this time；The skin surface light intensity change information that blood flow volume change causes in detection user's blood vessel；Obtain pulse wave signal；Calculate heart rate and often fight the eartbeat interval time；Heart rate or heartbeat time interval sequence are analyzed, the index of correlation of HRV is obtained；Using sleep state, algorithm model calculates sleep quality state by stages.The present invention substantially increases the accuracy and convenience of sleep quality status monitoring, effectively instructs people to improve the health care of sleep state and arranges the reasonable length of one's sleep to adjust condition.
Description
Technical field
The present invention relates to sleep state monitoring technical field, more particularly to a kind of sleep based on action and HRV measurements
Condition discrimination system and method.
Background technology
Sleep is the important physiological activity that everyone is required for carrying out, and sleep can help human body to set up, and alleviates feelings
Thread, therefore the normal life of the sleep to people of abundance is very necessary.In modern society, with the people of the symptoms such as insomnia, somnolence
Not within minority, usually the life on daytime to people makes a big impact, and frequently results in other mind ＆ body problems.Due to sleep
When human body physiological state with it is clear-headed when have very big difference, human body does not have sense of independence under sleep state, generally cannot self understand
The sleep state of self, and sleep state lower body there occurs which changes.Therefore sleep quality is differentiated using certain means
State and display sleep state change have very benefit greatly to everybody, especially understand dormant change feelings
Condition, the treatment of the illness related to sleep to some also has very great help.
Current maximally effective sleep state method of discrimination is to measure the brain wave under human body hypnagogic state, by observing brain electricity
The waveform change of ripple, it can be seen directly that dormant situation of change.But needed in head-mount brain during brain wave
Electrical wave measurement's instrument, greatly interference can be caused to sleep, in daily life without operability.
On the market existing utilization wearable device using 3-axis acceleration sensor measurement human body wrist movement method come
User's sleep state is judged, especially by wrist movement number of times per minute in whole section of sleep of statistics user, Ran Houli
Residing sleep state per minute in whole section of user sleep (including clear-headed, shallow sleep, sound sleep) is judged with the method for segment processing.
This mode is to a certain extent effective, and it is exactly to fall asleep with waking state most directly to embody, and human body is moved
The number of times of work has notable difference, as long as therefore measure the size of this difference, just can accurately judge very much human body be in it is clear-headed also
Under being sleep state.But substantially, the foundation of segmentation of sleeping as previously described is brain wave, therefore in a sleep state, human body
It is to be slept or sound sleep in shallow, or REM sleep, the discriminant approach of unique entirely accurate is that human body electroencephalogram's ripple is measured
And classify.Act the relevance electric with brain in a sleep state due to human body very faint, surveyed using 3-axis acceleration sensor
Measure wrist movement size or quantity, then differentiate accordingly human body be in it is shallow sleep or sound sleep be completely it is inaccurate.
The content of the invention
Based on the problem that above-mentioned prior art is present, the present invention proposes a kind of sleep shape based on action and HRV measurements
State judgement system and method, by detecting that human body limb acts number, and the change of skin surface light intensity realizes that human body HRV is detected,
And sleep quality state is monitored accordingly.
A kind of sleep state judgement system based on action and HRV measurements of the invention, the system includes what is sequentially connected
3-axis acceleration sensor module 101, limb action number computing module 102, optical sensor module 103, pulse wave signal meter
Calculate module 104, heart rate and heartbeat interval computing module 105, heart rate variability metrics computing module 106, sleep state calculate mould
Block 107；Wherein：
3-axis acceleration sensor module 101, for measuring human body limb acceleration signal；
Limb action number computing module 102, time of the limbs in systemic presupposition is calculated according to human body limb acceleration signal
Interior action number；
Optical sensor module 103, for the blood in detection user's blood vessel after at least one LED light irradiation skin surface
The skin surface light intensity change information that fluid capacitance product change causes；
Pulse wave signal computing module 104, pulse wave signal is obtained according to light intensity change information；
Heart rate and heartbeat interval computing module 105, for calculating heart rate and often fighting the eartbeat interval time；
Heart rate variability metrics computing module 106, becomes for being analyzed acquisition heart rate to heart rate or heartbeat interval sequence
The index of correlation of the opposite sex, time domain and/or frequency domain are carried out using to the heart rate in systemic presupposition certain hour or heartbeat interval sequence
The method of analysis；
Sleep state computing module 107, according to limb action number and the index of correlation of HRV, using mould of sleeping
Type calculates sleep state；
The sleep model 108, for description action number and heart rate variability metrics pass respectively between sleep state
System.
A kind of sleep state method of discrimination based on action and HRV measurements of the invention, the method is comprised the following steps：
Step 1, using human body limb three-dimensional acceleration data in 3-axis acceleration sensor module collection setting time；
Step 2, using limb action number computing module according to three-dimensional acceleration data, calculate the limb action within this time
Quantity；
Step 3, the blood flow volume change in user's blood vessel is detected after green glow irradiates skin surface using optical detecting module
The skin surface light intensity change information for causing；
Step 4, pulse wave signal is obtained according to above-mentioned light intensity change information using pulse wave signal computing module；
Step 5, heart rate is calculated using heart rate and eartbeat interval computing module and is often fought the eartbeat interval time；
Step 6, heart rate or heartbeat time interval sequence are analyzed using heart rate variability metrics computing module, obtained
The index of correlation of HRV, that is, use carries out time domain to the heart rate in the systemic presupposition time or heartbeat time interval sequence
And/or the method for frequency-domain analysis；
Step 7, using sleep state computing module according to limb action number and both indexs of HRV and human body
Algorithm model calculates sleep quality state to the sleep state that dormant relation is set up by stages.
Compared with prior art, the present invention substantially increases the accuracy and convenience of sleep quality status monitoring, economical
Practicality, can effectively instruct people to improve the health care of sleep state and arrange the reasonable length of one's sleep to adjust condition, with more extensive
Range of application.
Brief description of the drawings
Fig. 1 is the sleep state judgement system structural representation based on action and HRV measurements of the invention；
Fig. 2 is the sleep state method of discrimination overall flow schematic diagram based on action and HRV measurements of the invention.
Specific embodiment
The present invention is described in further detail with specific embodiment below in conjunction with the accompanying drawings.
As shown in figure 1, be the sleep state judgement system structural representation based on action and HRV measurements of the invention, should
System includes following 8 modules：
3-axis acceleration sensor module 101, for measuring human body limb acceleration signal；The 3-axis acceleration sensor
Module is close to wrist, but is not limited only to this, can also be arranged on the positions such as ankle, thorax abdomen；
Limb action number computing module 102, time of the limbs in systemic presupposition is calculated according to human body limb acceleration signal
Interior action number；
Optical sensor module 103, for the blood in detection user's blood vessel after at least one LED light irradiation skin surface
The skin surface light intensity change information that fluid capacitance product change causes；The optical detecting module is close to wrist, but is not limited only to this,
Can also be provided at the positions such as finger, arm, the palm of the hand and chest；
Pulse wave signal computing module 104, pulse wave signal is obtained according to light intensity change information；
Heart rate and heartbeat interval computing module 105, for calculating heart rate and often fighting the eartbeat interval time；
Heart rate variability metrics computing module 106, becomes for being analyzed acquisition heart rate to heart rate or heartbeat interval sequence
The opposite sex index of correlation, can using the heart rate in systemic presupposition certain hour or heartbeat interval sequence are carried out time domain and/or
The method of frequency-domain analysis；
Sleep state computing module 107, according to the index of correlation of described limb action number and HRV, utilizes
Algorithm model calculates sleep state.
The sleep model 108, for description action number and heart rate variability metrics pass respectively between sleep state
System, including but not limited to simple statistics model, artificial neural network, SVMs isotype identification intelligent algorithm model.
By taking specific embodiment as an example, the LED in optical sensor module can be white light LEDs, green light LED or red
Light and near infrared light LED combination, it is optimal with green light LED.It can be the combination of one or more LEDs.The peak value ripple of green light LED
Scope long is 520nm~575nm.
The index of correlation of HRV include but is not limited to LF (low frequency power), HF (high frequency power), TP (general power),
MEAN (phase average value between RR), SDNN (phase population standard deviation between RR), r-MSSD (the square square root of phase difference between RR).
It is of the invention to realize that the sleep state based on action and HRV measurements sentences method for distinguishing, comprise the following steps：
Step 1, accelerate the number of degrees using all human body limb three-dimensionals in 3-axis acceleration sensor module collection certain hour
According to；
Step 2, using limb action number computing module according to three-dimensional acceleration data, calculate the limb action within this time
Quantity；
Step 3, the blood flow volume change in user's blood vessel is detected after green glow irradiates skin surface using optical detecting module
The skin surface light intensity change information for causing；
Step 4, pulse wave signal is obtained according to above-mentioned light intensity change information using pulse wave signal computing module；
Step 5, heart rate is calculated using heart rate and eartbeat interval computing module and is often fought the eartbeat interval time；
Step 6, acquisition is analyzed to heart rate or heartbeat time interval sequence using heart rate variability metrics computing module
The index of correlation of HRV, can use is carried out to the heart rate in systemic presupposition certain hour or heartbeat time interval sequence
Time domain and/or the method for frequency-domain analysis；
Step 7, using sleep state computing module according to limb action number and both indexs of HRV and human body
Algorithm model calculates sleep quality state to the sleep state that dormant relation is set up by stages.
The content of above-mentioned steps of the present invention is illustrated by the following examples：
The utilization pulse wave signal computing module of step 3 obtains pulse wave signal according to light intensity change information, and it is specially：
The signal transactings such as denoising are filtered using pulse wave signal computing module to described light intensity change information to obtain
Pulse wave signal.
The utilization heart rate and heartbeat interval computing module of step 4 calculate heart rate and often fight the eartbeat interval time, and it is specially：
Detected by carrying out to pulse wave crest/trough/gradient maxima using heart rate and eartbeat interval computing module or
Spectrum analysis obtains heart rate and often fights the eartbeat interval time.
The utilization sleep state computing module of step 7 according to the index of correlation of limb action number and HRV both
Algorithm model calculates sleep quality state to the sleep state that index is set up with the relation of sleep quality state by stages, and its is specific
For：
Sleep state computing module judges that human body is in waking state or hypnagogic state according to limb action number, further according to
HRV index of correlation and using sleep state by stages algorithm model hypnagogic state carried out it is shallow sleep, sound sleep, REM sleep
By stages.
Sleep state judgement system and method based on action and HRV measurements of the invention, are judged by human action number
Whether human body is in hypnagogic state；Recycle the index of correlation of human body HRV carries out by stages, obtaining at human body to sleep quality process
In the shallow analysis method for sleeping state, deep sleep and REM sleep state.
The above, only presently preferred embodiments of the present invention is used to help understand the method for the present invention and core concept, right
In those of ordinary skill in the art, according to thought of the invention, change is had in specific embodiments and applications
Part, so this specification content should not be construed as limiting the invention.
Claims (5)
1. it is a kind of based on the sleep state judgement system for acting and HRV is measured, it is characterised in that the system includes what is sequentially connected
3-axis acceleration sensor module (101), limb action number computing module (102), optical sensor module (103), pulse wave
Signal of change module (104), heart rate and heartbeat interval computing module (105), heart rate variability metrics computing module (106), sleep
Dormancy state computation module (107)；Wherein：
3-axis acceleration sensor module (101), for measuring human body limb acceleration signal；
Limb action number computing module (102), according to human body limb acceleration signal calculating limbs within the time of systemic presupposition
Action number；
Optical sensor module (103), for the blood flow in detection user's blood vessel after at least one LED light irradiation skin surface
The skin surface light intensity change information that volume change causes；
Pulse wave signal computing module (104), pulse wave signal is obtained according to light intensity change information；
Heart rate and heartbeat interval computing module (105), for calculating heart rate and often fighting the eartbeat interval time；
Heart rate variability metrics computing module (106), for being analyzed acquisition heart rate variability to heart rate or heartbeat interval sequence
Property index of correlation, using carrying out to the heart rate in systemic presupposition certain hour or heartbeat interval sequence time domain and/or frequency domain point
The method of analysis；
Sleep state computing module (107), according to limb action number and the index of correlation of HRV, using model of sleeping
Calculate sleep state；
Sleep model (108), for description action number and heart rate variability metrics relation respectively between sleep state.
2. it is a kind of based on the sleep state method of discrimination for acting and HRV is measured, it is characterised in that the method is comprised the following steps：
Step (1), using human body limb three-dimensional acceleration data in 3-axis acceleration sensor module collection setting time；
Step (2), using limb action number computing module according to three-dimensional acceleration data, calculate the limb action number within this time
Amount；
Step (3), using optical detecting module green glow irradiation skin surface after detect user's blood vessel in blood flow volume change draw
The skin surface light intensity change information for rising；
Step (4), pulse wave signal is obtained according to above-mentioned light intensity change information using pulse wave signal computing module；
Step (5), heart rate is calculated using heart rate and eartbeat interval computing module and is often fought the eartbeat interval time；
Step (6), heart rate or heartbeat time interval sequence are analyzed using heart rate variability metrics computing module, obtain the heart
The index of correlation of rate variability, i.e., using the heart rate in the systemic presupposition time or heartbeat time interval sequence are carried out time domain and/
Or the method for frequency-domain analysis；
Step (7), using sleep state computing module according to limb action number and both indexs of HRV and human body sleeping
Algorithm model calculates sleep quality state to the sleep state that the relation of dormancy state is set up by stages.
3. it is as claimed in claim 2 based on the sleep state method of discrimination for acting and HRV is measured, it is characterised in that the step
Suddenly the utilization pulse wave signal computing module of (3) obtains pulse wave signal according to light intensity change information, and it is specially：
The signal transactings such as denoising are filtered to described light intensity change information and obtain pulse wave signal.
4. it is as claimed in claim 5 based on the sleep state method of discrimination for acting and HRV is measured, it is characterised in that step (4)
Utilization heart rate and heartbeat interval computing module calculate and heart rate and often fight the eartbeat interval time, it is specially：
By carrying out to pulse wave, crest/trough/gradient maxima is detected or spectrum analysis obtains heart rate and eartbeat interval of often fighting
Time.
5. it is as claimed in claim 5 based on the sleep state method of discrimination for acting and HRV is measured, it is characterised in that the step
Suddenly the utilization sleep state computing module of (7) is according to both indexs of the index of correlation of limb action number and HRV and people
Algorithm model calculates sleep quality state to the sleep state that the relation of somatic sleep state is set up by stages, and it is specially：
Sleep state computing module judges that human body is in waking state or hypnagogic state according to limb action number, further according to heart rate
Variability index of correlation and using sleep state by stages algorithm model hypnagogic state is carried out it is shallow sleep, sound sleep, REM sleep divide
Phase.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611236012.XA CN106725382A (en) | 2016-12-28 | 2016-12-28 | Sleep state judgement system and method based on action and HRV measurements |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611236012.XA CN106725382A (en) | 2016-12-28 | 2016-12-28 | Sleep state judgement system and method based on action and HRV measurements |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106725382A true CN106725382A (en) | 2017-05-31 |
Family
ID=58924627
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611236012.XA Pending CN106725382A (en) | 2016-12-28 | 2016-12-28 | Sleep state judgement system and method based on action and HRV measurements |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106725382A (en) |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107169307A (en) * | 2017-07-07 | 2017-09-15 | 中北大学 | Health risk assessment method and apparatus |
| CN107890339A (en) * | 2017-11-09 | 2018-04-10 | 常熟理工学院 | A kind of sleep stage detection method and wearable sleep stage detection means |
| CN108209874A (en) * | 2018-01-03 | 2018-06-29 | 深圳北航新兴产业技术研究院 | A kind of method and apparatus of sleep mode automatically by stages |
| CN109222950A (en) * | 2018-10-19 | 2019-01-18 | 深圳和而泰数据资源与云技术有限公司 | Data processing method and device |
| CN109394174A (en) * | 2017-08-18 | 2019-03-01 | 美的集团股份有限公司 | Sleep state method of discrimination, device, computer equipment and readable storage medium storing program for executing |
| CN109745028A (en) * | 2017-11-07 | 2019-05-14 | 财团法人资讯工业策进会 | System and method for identifying infant needs |
| CN110251802A (en) * | 2019-06-11 | 2019-09-20 | 深圳迈睿智能科技有限公司 | Sleep inducing system and its sleep derivation method and sleep derivation device |
| CN111956197A (en) * | 2020-09-18 | 2020-11-20 | 深圳市爱都科技有限公司 | Sleep state detection method and device, electronic equipment and storage medium |
| CN112370013A (en) * | 2020-07-31 | 2021-02-19 | 新绎健康科技有限公司 | Method and system for determining sleep stage |
| CN112370058A (en) * | 2020-11-11 | 2021-02-19 | 西北工业大学 | Method for identifying and monitoring emotion of user based on mobile terminal |
| CN113518583A (en) * | 2019-03-11 | 2021-10-19 | 京瓷株式会社 | Sleep estimation system, sleep estimation device, and sleep estimation method |
| CN113951826A (en) * | 2021-10-25 | 2022-01-21 | 思澜科技（成都）有限公司 | Method, system and equipment for evaluating sleep condition |
| CN114145717A (en) * | 2021-12-08 | 2022-03-08 | 四川北易信息技术有限公司 | Sleep state analysis method based on PPG heart rate characteristic parameters and motion quantity |
| CN114159025A (en) * | 2021-11-23 | 2022-03-11 | 湖南云医链生物科技有限公司 | Sleep quality analysis method, device, equipment and storage medium |
| CN114366986A (en) * | 2022-01-13 | 2022-04-19 | 上海工程技术大学 | Sleep assisting method, medium and wearable device |
| CN116348039A (en) * | 2021-10-21 | 2023-06-27 | 谷歌有限责任公司 | Method and system for improving measurement of sleep data by classifying users based on sleeper type |
| EP4218576A4 (en) * | 2020-09-29 | 2024-03-27 | Guangdong Oppo Mobile Telecommunications Corp., Ltd. | Sleep monitoring method and apparatus, electronic device, and computer-readable medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103717125A (en) * | 2011-05-18 | 2014-04-09 | V视股份有限公司 | System and method for determining sleep and sleep stages of a person |
| CN104161509A (en) * | 2014-08-08 | 2014-11-26 | 申岱 | Heart rate variability analyzing method based on amplitude spectrum and instruments |
| CN105105732A (en) * | 2015-08-14 | 2015-12-02 | 姚丽峰 | System and method for implementing detection on pulse and heart rate and monitoring on emotion and fatigue degree |
-
2016
- 2016-12-28 CN CN201611236012.XA patent/CN106725382A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103717125A (en) * | 2011-05-18 | 2014-04-09 | V视股份有限公司 | System and method for determining sleep and sleep stages of a person |
| CN104161509A (en) * | 2014-08-08 | 2014-11-26 | 申岱 | Heart rate variability analyzing method based on amplitude spectrum and instruments |
| CN105105732A (en) * | 2015-08-14 | 2015-12-02 | 姚丽峰 | System and method for implementing detection on pulse and heart rate and monitoring on emotion and fatigue degree |
Cited By (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107169307A (en) * | 2017-07-07 | 2017-09-15 | 中北大学 | Health risk assessment method and apparatus |
| CN109394174A (en) * | 2017-08-18 | 2019-03-01 | 美的集团股份有限公司 | Sleep state method of discrimination, device, computer equipment and readable storage medium storing program for executing |
| CN109745028A (en) * | 2017-11-07 | 2019-05-14 | 财团法人资讯工业策进会 | System and method for identifying infant needs |
| CN107890339A (en) * | 2017-11-09 | 2018-04-10 | 常熟理工学院 | A kind of sleep stage detection method and wearable sleep stage detection means |
| CN107890339B (en) * | 2017-11-09 | 2020-09-08 | 常熟理工学院 | Sleep staging detection method and wearable sleep staging detection device |
| CN108209874B (en) * | 2018-01-03 | 2021-01-26 | 深圳北航新兴产业技术研究院 | Automatic sleep staging method and device |
| CN108209874A (en) * | 2018-01-03 | 2018-06-29 | 深圳北航新兴产业技术研究院 | A kind of method and apparatus of sleep mode automatically by stages |
| CN109222950A (en) * | 2018-10-19 | 2019-01-18 | 深圳和而泰数据资源与云技术有限公司 | Data processing method and device |
| CN109222950B (en) * | 2018-10-19 | 2021-08-06 | 深圳和而泰数据资源与云技术有限公司 | Data processing method and device |
| EP3939502A4 (en) * | 2019-03-11 | 2022-11-30 | Kyocera Corporation | Sleep estimation system, sleep estimation device, and sleep estimation method |
| CN113518583A (en) * | 2019-03-11 | 2021-10-19 | 京瓷株式会社 | Sleep estimation system, sleep estimation device, and sleep estimation method |
| CN110251802A (en) * | 2019-06-11 | 2019-09-20 | 深圳迈睿智能科技有限公司 | Sleep inducing system and its sleep derivation method and sleep derivation device |
| CN112370013A (en) * | 2020-07-31 | 2021-02-19 | 新绎健康科技有限公司 | Method and system for determining sleep stage |
| CN111956197A (en) * | 2020-09-18 | 2020-11-20 | 深圳市爱都科技有限公司 | Sleep state detection method and device, electronic equipment and storage medium |
| EP4218576A4 (en) * | 2020-09-29 | 2024-03-27 | Guangdong Oppo Mobile Telecommunications Corp., Ltd. | Sleep monitoring method and apparatus, electronic device, and computer-readable medium |
| CN112370058A (en) * | 2020-11-11 | 2021-02-19 | 西北工业大学 | Method for identifying and monitoring emotion of user based on mobile terminal |
| CN116348039A (en) * | 2021-10-21 | 2023-06-27 | 谷歌有限责任公司 | Method and system for improving measurement of sleep data by classifying users based on sleeper type |
| CN113951826A (en) * | 2021-10-25 | 2022-01-21 | 思澜科技（成都）有限公司 | Method, system and equipment for evaluating sleep condition |
| CN113951826B (en) * | 2021-10-25 | 2023-09-05 | 思澜科技（成都）有限公司 | Method, system and equipment for evaluating sleep condition |
| CN114159025A (en) * | 2021-11-23 | 2022-03-11 | 湖南云医链生物科技有限公司 | Sleep quality analysis method, device, equipment and storage medium |
| CN114159025B (en) * | 2021-11-23 | 2023-06-23 | 湖南云医链生物科技有限公司 | Sleep quality analysis method, device, equipment and storage medium |
| CN114145717A (en) * | 2021-12-08 | 2022-03-08 | 四川北易信息技术有限公司 | Sleep state analysis method based on PPG heart rate characteristic parameters and motion quantity |
| CN114145717B (en) * | 2021-12-08 | 2024-06-25 | 四川北易信息技术有限公司 | Sleep state analysis method based on PPG heart rate characteristic parameters and exercise amount |
| CN114366986A (en) * | 2022-01-13 | 2022-04-19 | 上海工程技术大学 | Sleep assisting method, medium and wearable device |
| CN114366986B (en) * | 2022-01-13 | 2023-11-24 | 上海工程技术大学 | Sleep assisting method, medium and wearable device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106725382A (en) | Sleep state judgement system and method based on action and HRV measurements | |
| CN109157202B (en) | Cardiovascular disease early warning system based on multi-physiological signal deep fusion | |
| CN107569226B (en) | The method and application of HRV are obtained based on piezoelectric sensing | |
| CN105142515B (en) | The method for determining the mankind's sleep stage for being conducive to waking up | |
| Bolanos et al. | Comparison of heart rate variability signal features derived from electrocardiography and photoplethysmography in healthy individuals | |
| EP3212062B1 (en) | Device for contraction monitoring | |
| CN106725383A (en) | Sleep state judgement system and method based on action and heart rate | |
| WO2018107915A1 (en) | General noninvasive blood glucose prediction method based on timing analysis | |
| CN204931634U (en) | Based on the depression evaluating system of physiologic information | |
| US20150245777A1 (en) | Detection of emotional states | |
| Quazi et al. | Towards the smart sensors based human emotion recognition | |
| CN104107037A (en) | Physiological information acquiring and processing system | |
| TW201019901A (en) | Sleep analysis system and analysis method thereof | |
| Murali et al. | A wearable device for physical and emotional health monitoring | |
| CN114145717B (en) | Sleep state analysis method based on PPG heart rate characteristic parameters and exercise amount | |
| CN106725326A (en) | Sleep quality assessment system and method based on human body HRV measurements | |
| CN116250820A (en) | Bioelectrical measurement health early warning system based on auricular point and early warning method thereof | |
| US12274541B1 (en) | Systems and methods for monitoring hydration | |
| CN108392176A (en) | A kind of Sleep architecture detection method based on the acquisition of heart impact signal | |
| CN106510641B (en) | A kind of method and system detecting human body difference sleep stage | |
| CN106108844B (en) | A kind of method and apparatus of determining sleep stage | |
| CN106108845B (en) | A kind of method and apparatus of determining sleep stage | |
| CN203290920U (en) | Portable emotion analysis meter | |
| CN106333674B (en) | Sleep cycle detection method and system in sleep state analysis | |
| CN106175698B (en) | Sleep cycle detection device in sleep state analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20170531 |