CN108968946A - A kind of female incretion management system based on HRV analysis - Google Patents
A kind of female incretion management system based on HRV analysis Download PDFInfo
- Publication number
- CN108968946A CN108968946A CN201810637908.1A CN201810637908A CN108968946A CN 108968946 A CN108968946 A CN 108968946A CN 201810637908 A CN201810637908 A CN 201810637908A CN 108968946 A CN108968946 A CN 108968946A
- Authority
- CN
- China
- Prior art keywords
- sdnn
- ulf
- signal
- hrv
- peak
- 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
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
-
- 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
-
- 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/42—Detecting, measuring or recording for evaluating the gastrointestinal, the endocrine or the exocrine systems
-
- 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
- A61B5/6813—Specially adapted to be attached to a specific body part
- A61B5/6823—Trunk, e.g., chest, back, abdomen, hip
-
- 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
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- Animal Behavior & Ethology (AREA)
- Veterinary Medicine (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Surgery (AREA)
- Physics & Mathematics (AREA)
- Cardiology (AREA)
- Physiology (AREA)
- Signal Processing (AREA)
- Endocrinology (AREA)
- Gastroenterology & Hepatology (AREA)
- Power Engineering (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychiatry (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
The present invention provides a kind of female incretion management systems based on HRV analysis, including the sign signal acquisition based on all kinds of sensings, BCG/ECG/PPG signal is separated from acquisition signal and is pre-processed, it is identified based on BCG/ECG/PPG signal peak and solves signal peak interphase, and then determine HRV time domain parameter SDNN, SDNN power spectrum is solved, ULF component is separated, it determines being associated with for ULF and basic female incretion, proposes corresponding health management scheme；The present invention is based on the long-term HRV time-frequency domain exponential trend analysis of user, and mentioned health management scheme and model are the analyses based on user's individuation data, and accuracy is high, and noninvasive unperturbed, and user experience is high.
Description
Technical field
The present invention relates to field of medical technology, and in particular to a kind of female incretion management system based on HRV analysis.
Background technique
Heart rate variability (Heart rate variability HRV) refers to what heart rate rhythm speed was occurred at any time
Variation.HRV is the subtle time change and its rule for analyzing cardiac cycle one by one.It is this to change the conventional heart recorded in body surface
It is often difficult to measure on electrograph or because small and not significant, the sinus rhythm of the rule of habit description is never etc. on routine electrocardiogram
It does not make a variation in heart rate.The research object of HRV is the time difference of gradually cardiac cycle, is enumerated between human body each cardiac cycle
Difference can show that a lot of unordered parameters seemingly reflect the continuous momentary fluctuation of heart rate.The fluctuation of heart rate is not accidental
But by internal neurohumoral regulation, the reaction made for the different physiological status of adaptation or certain pathological states.
The heart caused by the modulating action that the HF ingredient reflection respiratory activity of HRV is conducted finally by cardiac vagus nerve fiber
Rate fluctuating change, in document also referred to as " hennig-Lommel sign " (respiratory arrhythmia, RSA).Respiratory activity is logical
Crossing central mechanism and mechanicalness influences two approach and modulating action occurs to heart rate, and the peak height of the HF of HRV and heart fan walk outflow and live
The dynamic degree of modulation to heart rate is related in conspicuousness.
Spectrum analysis discovery, heart rate variability generally include high frequency (HF) ingredient and low frequency (LF) ingredient, some scholars are by LF
It is further divided into ultralow frequency and two kinds of low frequency.Wherein, radio-frequency component is synchronous with respiratory movement, therefore the respiratory component that is otherwise known as,
Occur within about 3 seconds primary, scholars think that radio-frequency component therein reflects parasympathetic function, and low-frequency component and high frequency at
The ratio (LF/HF) divided has reacted sympathetic activity.
Occur the detection and prevention of the human body diseases based on HRV, such as Publication No. now
The Chinese patent of CN201410334899.0 discloses a kind of assessment system of depression based on heart rate variance analyzing method
And then method is analyzed by heart rate variability linearity curve and is then analyzed by obtaining electrocardiosignal and pulse wave signal
The depression grade of tester.The for another example Chinese patent of Publication No. CN201510995537.0 discloses a kind of biological physiology shape
Condition feedback system and its operating method detect blood flow electric signal by photoelectric sensor, and it is raw to obtain HRV based on blood flow electric signal
Manage parameter value and pulse wave data and binding analysis biological physiology situation.But there is presently no about being analyzed based on HRV
The patent of female incretion management system, it is abnormal that endocrine disorder can allow the body of people to occur, and but will bring many diseases, be
A kind of body illness that women cannot ignore, therefore, the endocrine management system situation for effectively monitoring female body are avoided that
The generation of disease, and be adjusted in time, be conducive to female body sound development.
Summary of the invention
For the shortage of the prior art, the present invention provides a kind of female incretion management system based on HRV analysis, passes through
The analysis of long-time HRV time-frequency domain exponential trend obtains the data information of female body, and establishes health control according to information feedback
Scheme, the case where effectivelying prevent female endocrine dyscrasia generation.
To achieve the above object, the present invention adopts the following technical scheme:
A kind of female incretion management system based on HRV analysis, including it is data acquisition module, peak detection block, pre-
Processing module obtains heart rate variability curve module, HRV analysis module, model building module and model application module；
Ballistocardiography (BCG) when the data acquisition module is used to acquire long during user entirely sleeps, it is long when electrocardio
Scheme (ECG) and it is long when volume pulsation wave (PPG)；
The peak detection block be used for ballistocardiography when obtaining long, it is long when electrocardiogram and it is long when volume pulsation wave peak value
Point sequence, the peak point refer to the highest point of each heart beat cycle heart impact signal, electrocardiosignal and pulse wave signal waveform,
The time interval of adjacent peak point is a heart beat cycle；
The processing such as the preprocessing module is for being filtered the signal of acquisition, denoising, abnormal signal is discharged are correct to know
The peak value of other BCG, ECG and PPG signal；
The acquisition heart rate variability curve module is for obtaining BCG, ECG and PPG signal in a complete physiological period
Change curve；
The HRV analysis module is used to calculate the time domain parameter SDNN of heart rate variability, and solves SDNN power spectrum, point
Analyse the distribution of the HRV frequency indexs such as HF, LF and ULF；
The model building module is used to define women Endocrine basis and being associated with of ULF component in HRV, defines in women
Secreting function is associated with Endocrine basis index (HRV-ULF)；
The model application module is used to be judged according to the definition of model building module for the physical condition of women
And propose corresponding health management scheme.
The present invention specifically includes the following steps:
S1, using sensor acquisition user entirely sleep during it is long when ballistocardiography (BCG), it is long when electrocardiogram (ECG)
With it is long when volume pulsation wave (PPG)；
S2 separates BCG/ECG/PPG signal from acquisition signal, is pre-processed；
S3 solves signal peak interphase based on the identification of BCG/ECG/PPG signal peak, and then determines HRV time domain parameter
SDNN；
S4 solves SDNN power spectrum, separates ULF component, determines being associated with for ULF and women Endocrine basis, obtains basic
Endocrine index (HRV-ULF)；
S5, define Endocrine basis index (HRV-ULF) and endocrine function, between relationship, propose corresponding healthy
Managed Solution.
Preferably, the sensor in the step S1 includes piezoelectric transducer and/or singly leads EGC sensor and/or photoelectricity
Sensor, the piezoelectric transducer be placed in pillow under, under mattress with women without direct contact area, it is described singly to lead EGC sensor
Before being affixed on female chest, the photoelectric sensor is worn on women wrist.
Preferably, BCG signal is isolated in the signal of the piezoelectric transducer acquisition, by filtering, denoising, abnormal signal
After excluding pretreatment, the peak J of each BCG is identified, solve the J-J peak-to-peak phase, obtain the time domain parameter SDNN of HRV signal, specifically
Formula is as follows:
Wherein, T is that issue, Interval_JJ (i) are i-th of adjacent BCG signal between effectively J-J within the scope of detection time
Time value between J-J, Mean_JJ are the average value of the effective BCG J-J interphase of women sleep all night.
Preferably, ECG signal is isolated in the signal for singly leading EGC sensor acquisition, by filtering, denoising, exception
After the pretreatments such as signal exclusion, the peak R of ECG signal is identified, the calculating R-R peak-to-peak phase simultaneously solves time domain parameter using formula one
SDNN。
Preferably, PPG signal is isolated in the signal of the photoelectric sensor acquisition, by filtering, denoising, abnormal signal
After excluding pretreatment, the peak B in PPG signal is identified, calculate the B-B peak-to-peak phase and solve time domain parameter SDNN using formula one.
Preferably, acquiring women by sensor is more than a complete physiological period night SDNN data, and specific formula is such as
Under:
SDNN_T=[SDNN (1), SDNN (2) ..., SDNN (K)]TFormula two
Then, using time-frequency domain conversation, the frequency domain power spectrum of SDNN_T is solved, specific technical solution includes: that Fourier becomes
It changes, autocorrelation spectrum analysis, the methods of Fast Lomb-Scargle periodogram spectrum analysis, specific formula is as follows:
SDNN_F=[F (1), F (2) ..., F (K)]TFormula three
Then, bandpass filter is designed, the ULF component in K dimension power spectrum SDNN_F is solved, specific formula is as follows:
ULF=[ULF (1), ULF (2) ..., ULF (K)]TFormula four
Wherein, K is determining female physiological periodicity number of days, and SDNN (k), k=1,2 ..., K is the data of kth group SDNN whole night；F
(k), k=1,2 ..., K indicates the corresponding power spectrum of kth group SDNN；High frequency power value HF, low frequency are solved according to HRV power spectrum
Performance number LF and LF/HF ratio.
Preferably, based on a complete physiological period statistics, point of the record HRV frequency index such as women HF, LF and ULF
Cloth defines ULF and is associated with female incretion hormonal readiness according to trend analyses such as HF, LF, ULF.
Preferably, it is analyzed according to ULF fluctuation tendency, defines female incretion hormonal readiness Managed Solution, it is anti-in conjunction with ULF institute
The physiological period mirrored is formulated based on ULF level endocrine standby pregnant Managed Solution relevant to prediction physiological period, including interior point
Secrete function prediction, index disorder prediction, easily pregnant exponential forecasting and corresponding management scheme.
A kind of beneficial effect of female incretion management system based on HRV analysis provided by the invention is:
(1) by long-term ULF analysis of trend, the Endocrine hormone levels and easy pregnant water for user's individuation can be established
Flat evaluation model is managed female incretion health；And the noninvasive unperturbed of detection management method, user experience are high；
(2) the present invention is based on the long-term HRV time-frequency domain exponential trend analysis of user, mentioned health management scheme and model are bases
In the analysis of user's individuation data, accuracy is higher.
Detailed description of the invention
Fig. 1 is flow chart of steps of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Whole description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Ability
Domain ordinary person every other embodiment obtained without making creative work, belongs to protection of the invention
Range.
A kind of embodiment: female incretion management system based on HRV analysis.
The present invention includes data acquisition module, peak detection block, preprocessing module, obtains heart rate variability curvilinear mold
Block, HRV analysis module, model building module and model application module；
Ballistocardiography (BCG) when the data acquisition module is used to acquire long during user entirely sleeps, it is long when electrocardio
Scheme (ECG) and it is long when volume pulsation wave (PPG)；
The peak detection block be used for ballistocardiography when obtaining long, it is long when electrocardiogram and it is long when volume pulsation wave peak value
Point sequence, the peak point refer to the highest point of each heart beat cycle heart impact signal, electrocardiosignal and pulse wave signal waveform,
The time interval of adjacent peak point is a heart beat cycle；
The processing such as the preprocessing module is for being filtered the signal of acquisition, denoising, abnormal signal is discharged are correct to know
The peak value of other BCG, ECG and PPG signal；
The acquisition heart rate variability curve module is for obtaining BCG, ECG and PPG signal in a complete physiological period
Change curve；
The HRV analysis module is used to calculate the time domain parameter SDNN of heart rate variability, and solves SDNN power spectrum, point
Analyse the distribution of the HRV frequency indexs such as HF, LF and ULF；
The model building module is used to define women Endocrine basis and being associated with of ULF component in HRV, defines in women
Secreting function is associated with Endocrine basis index (HRV-ULF), defines female incretion functions of intestines and stomach level and Endocrine basis
Index (HRV-ULF) association；
The model application module is used to be judged according to the definition of model building module for the physical condition of women
And propose corresponding health management scheme.
The data acquisition module include using piezoelectric transducer be placed in pillow under, under mattress with human body without direct contact zone
Domain, obtain user entirely sleep during it is long when ballistocardiography (BCG), using singly lead EGC sensor be affixed on user front acquisition
User entirely sleep during it is long when electrocardiogram (ECG), user's wrist is worn on using photoelectric sensor, user is obtained and entirely sleeps
Volume pulsation wave when long during dormancy；
BCG signal is excluded into pretreatment by filtering and noise reduction, abnormal signal, the peak J of each BCG is identified, solves the peak J-J
Interphase obtains the time domain parameter SDNN of HRV signal, specific formula is as follows:
Wherein, T is that issue, Interval_JJ (i) are i-th of adjacent BCG signal between effectively J-J within the scope of detection time
Time value between J-J, Mean_JJ are the average value of the effective BCG J-J interphase of women sleep all night.
It singly leads in the signal of EGC sensor acquisition and isolates ECG signal, excluded by filtering, denoising, abnormal signal pre-
After processing, the peak R of ECG signal is identified, calculate the R-R peak-to-peak phase and solve time domain parameter SDNN using formula one.
PPG signal is isolated in the signal of photoelectric sensor acquisition, excludes pretreatment by filtering, denoising, abnormal signal
Afterwards, it identifies the peak B in PPG signal, calculate the B-B peak-to-peak phase and solves time domain parameter SDNN using formula one.
Acquiring women by sensor is more than a complete physiological period night SDNN data, specific formula is as follows:
SDNN_T=[SDNN (1), SDNN (2) ..., SDNN (K)]TFormula two
Then, using time-frequency domain conversation, the frequency domain power spectrum of SDNN_T is solved, specific technical solution includes: that Fourier becomes
It changes, autocorrelation spectrum analysis, the methods of Fast Lomb-Scargle periodogram spectrum analysis, specific formula is as follows:
SDNN_F=[F (1), F (2) ..., F (K)]TFormula three
Then, bandpass filter is designed, the ULF component in K dimension power spectrum SDNN_F is solved, specific formula is as follows:
ULF=[ULF (1), ULF (2) ..., ULF (K)]TFormula four
Finally, ULF Long-term change trend is obtained using the methods of small echo, empirical mode decomposition (EMD), low-pass filter group, it should
Long-term change trend can react women Endocrine basis trend.
Wherein, K is determining female physiological periodicity number of days, and SDNN (k), k=1,2 ..., K is the data of kth group SDNN whole night；F
(k), k=1,2 ..., K indicates the corresponding power spectrum of kth group SDNN；High frequency power value HF, low frequency are solved according to HRV power spectrum
Performance number LF and LF/HF ratio.
By user's interaction, determine that user's physiological period starts and deadline, starts to track to down ULF trend
One physiological period starts；It defines women Endocrine basis to be associated with ULF component in HRV, specifically be associated with as follows:
(1) in a complete determining female physiological periodicity K, when ULF component first appears obvious peak, which is located at life
Manage the later period in period, and same day HRV each parameter of frequency domain is in normal fluctuation range, then speculate peak value occur be due to estrogen,
Progesterone Secretion increases, and defines the peak value and correspond to the date as luteal phase；
(2) in a complete determining female physiological periodicity K, when obvious peak value occurs in ULF raising, and peak position is located at and works as
Near the preceding complete physiological period median of women, and ULF defines the peak value and corresponds to the date in trend is gradually reduced after peak value appearance
For female ovulatory period.
It defines female incretion function to be associated with Endocrine basis index (HRV-ULF), is determining ULF and female incretion
After the coupled relation of hormonal readiness, the Managed Solution for being directed to female incretion hormonal readiness as follows is carried out:
(1) in a complete determining female physiological periodicity K, when ULF low frequency trend is irregular, variation tendency is not united extremely
One, without obvious peak value within the periods such as corresponding corpus luteum, ovulation, then speculate that the secretion of user's hormone in vivo is disorderly in the current physiology period
Disorderly, in fact it could happen that the gynecological diseases such as irregular menstruation, fibroid, ovarian neoplasm.
(2) in a complete determining female physiological periodicity K, first according to ULF trend analysis, determine the specific life locating for it
Manage the period, after luteal phase, early period onset of ovulation, while to be higher than trend mean value horizontal for ULF index, then speculate women be pregnant probability compared with
It is high；When ULF index is in peak value, then speculate that the probability of pregnancy is high.
Based on above-mentioned criterion, by long-term ULF analysis of trend, the endocrine hormone water for user's individuation can be established
The flat evaluation model with easy pregnant level, and then manage female incretion health.
Claims (8)
1. a kind of female incretion management system based on HRV analysis, including data acquisition module, peak detection block, pre- place
Reason module, acquisition heart rate variability curve module, HRV analysis module, model building module and model application module, feature exist
In the system executes following steps:
S1, using sensor acquisition user entirely sleep during it is long when ballistocardiography (BCG), it is long when electrocardiogram (ECG) and grow
When volume pulsation wave (PPG)；
S2 separates BCG/ECG/PPG signal from acquisition signal, is pre-processed；
S3 solves signal peak interphase based on the identification of BCG/ECG/PPG signal peak, and then determines HRV time domain parameter SDNN；
S4 solves SDNN power spectrum, separates ULF component, determines being associated with for ULF and women Endocrine basis, obtains in basis and divides
Secrete index (HRV-ULF)；
S5 defines the relationship between Endocrine basis index (HRV-ULF) and endocrine function, proposes corresponding health control side
Case.
2. the female incretion management system as described in claim 1 based on HRV analysis, it is characterised in that: the step S1
In sensor include piezoelectric transducer or singly lead EGC sensor or photoelectric sensor, the piezoelectric transducer is placed in pillow
Under, under mattress with women without direct contact area, described singly to lead before EGC sensor is affixed on female chest, the photoelectric sensor is worn
It wears in women wrist.
3. the female incretion management system as claimed in claim 2 based on HRV analysis, it is characterised in that: the piezoelectricity passes
BCG signal is isolated in the signal of sensor acquisition, after filtering, denoising, abnormal signal exclude pretreatment, identifies each
The peak J of BCG solves the J-J peak-to-peak phase, obtains the time domain parameter SDNN of HRV signal, specific formula is as follows:
Wherein, T issue between effectively J-J within the scope of detection time, between Interval_JJ (i) is i-th of adjacent BCG signal J-J
Time value, Mean_JJ are the average value of the effective BCG J-J interphase of women sleep all night.
4. the female incretion management system as claimed in claim 3 based on HRV analysis, it is characterised in that: described singly to lead the heart
ECG signal is isolated in the signal of electric transducer acquisition, after filtering, denoising, abnormal signal exclude pretreatment, identifies ECG
The peak R of signal calculates the R-R peak-to-peak phase and solves time domain parameter SDNN using formula one.
5. the female incretion management system as claimed in claim 4 based on HRV analysis, it is characterised in that: the photoelectric transfer
PPG signal is isolated in the signal of sensor acquisition, after filtering, denoising, abnormal signal exclude pretreatment, identifies PPG signal
In the peak B, calculating B-B peak-to-peak phase simultaneously solves time domain parameter SDNN using formula one.
6. the female incretion management system as claimed in claim 5 based on HRV analysis, it is characterised in that: pass through sensor
Acquiring women is more than a complete physiological period night SDNN data, specific formula is as follows:
SDNN_T=[SDNN (1), SDNN (2) ..., SDNN (K)]TFormula two
Then, using time-frequency domain conversation, solve the frequency domain power spectrum of SDNN_T, specific technical solution include: Fourier transformation, from
Correlation-spectra analysis, Fast Lomb-Scargle periodogram spectral analysis method, specific formula is as follows:
SDNN_F=[F (1), F (2) ..., F (K)]TFormula three
Then, bandpass filter is designed, the ULF component in K dimension power spectrum SDNN_F is solved, specific formula is as follows:
ULF=[ULF (1), ULF (2) ..., ULF (K)]TFormula four
Wherein, K is determining female physiological periodicity number of days, and SDNN (k), k=1,2 ..., K is the data of kth group SDNN whole night；F(k),k
=1,2 ..., K indicates the corresponding power spectrum of kth group SDNN；High frequency power value HF, low frequency power are solved according to HRV power spectrum
Value LF and LF/HF ratio.
7. the female incretion management system as claimed in claim 6 based on HRV analysis, it is characterised in that: complete based on one
Whole physiological period statistics, records the distribution of women HF, LF and ULFHRV frequency index, according to HF, LF, ULF trend analysis, definition
ULF is associated with female incretion hormonal readiness.
8. the female incretion management system as claimed in claim 7 based on HRV analysis, it is characterised in that: fluctuated according to ULF
Trend analysis defines female incretion hormonal readiness Managed Solution, in conjunction with the physiological period that ULF is reflected, formulates and is based on ULF
Horizontal endocrine standby pregnant Managed Solution relevant to prediction physiological period, including endocrine function prediction, index disorder are predicted, easily
Pregnant exponential forecasting and corresponding management scheme.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810637908.1A CN108968946A (en) | 2018-06-20 | 2018-06-20 | A kind of female incretion management system based on HRV analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810637908.1A CN108968946A (en) | 2018-06-20 | 2018-06-20 | A kind of female incretion management system based on HRV analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108968946A true CN108968946A (en) | 2018-12-11 |
Family
ID=64541535
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810637908.1A Pending CN108968946A (en) | 2018-06-20 | 2018-06-20 | A kind of female incretion management system based on HRV analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108968946A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110236524A (en) * | 2019-06-17 | 2019-09-17 | 深圳市善行医疗科技有限公司 | A kind of monitoring method of determining female physiological periodicity, device and terminal |
| CN114041786A (en) * | 2022-01-11 | 2022-02-15 | 华南师范大学 | Ballistocardiogram signal detection method, ballistocardiogram signal detection device and ballistocardiogram signal detection equipment |
| CN117271977A (en) * | 2023-09-27 | 2023-12-22 | 北京津发科技股份有限公司 | HRV data preprocessing method and device and electronic equipment |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100249628A1 (en) * | 2008-08-22 | 2010-09-30 | Kortelainen Juha M | Extraction of heart inter beat interval from multichannel measurements |
| US20150359888A1 (en) * | 2014-06-13 | 2015-12-17 | Palo Alto Investors | Methods and Compositions for Restoring Homeostatic Capacity of a Subject |
| CN105380597A (en) * | 2014-09-03 | 2016-03-09 | 三星电子株式会社 | Electronic device and method for measuring vital signal |
| CN107126203A (en) * | 2016-02-28 | 2017-09-05 | 南京全时陪伴健康科技有限公司 | Human health information measures display system in real time |
| CN107569226A (en) * | 2017-09-27 | 2018-01-12 | 广州中科新知科技有限公司 | HRV method and application is obtained based on piezoelectric sensing |
| CN107595274A (en) * | 2017-09-27 | 2018-01-19 | 广州中科新知科技有限公司 | Back cushion based on HRV non-contact detection emotional stress |
-
2018
- 2018-06-20 CN CN201810637908.1A patent/CN108968946A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100249628A1 (en) * | 2008-08-22 | 2010-09-30 | Kortelainen Juha M | Extraction of heart inter beat interval from multichannel measurements |
| US20150359888A1 (en) * | 2014-06-13 | 2015-12-17 | Palo Alto Investors | Methods and Compositions for Restoring Homeostatic Capacity of a Subject |
| CN105380597A (en) * | 2014-09-03 | 2016-03-09 | 三星电子株式会社 | Electronic device and method for measuring vital signal |
| CN107126203A (en) * | 2016-02-28 | 2017-09-05 | 南京全时陪伴健康科技有限公司 | Human health information measures display system in real time |
| CN107569226A (en) * | 2017-09-27 | 2018-01-12 | 广州中科新知科技有限公司 | HRV method and application is obtained based on piezoelectric sensing |
| CN107595274A (en) * | 2017-09-27 | 2018-01-19 | 广州中科新知科技有限公司 | Back cushion based on HRV non-contact detection emotional stress |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110236524A (en) * | 2019-06-17 | 2019-09-17 | 深圳市善行医疗科技有限公司 | A kind of monitoring method of determining female physiological periodicity, device and terminal |
| CN114041786A (en) * | 2022-01-11 | 2022-02-15 | 华南师范大学 | Ballistocardiogram signal detection method, ballistocardiogram signal detection device and ballistocardiogram signal detection equipment |
| CN117271977A (en) * | 2023-09-27 | 2023-12-22 | 北京津发科技股份有限公司 | HRV data preprocessing method and device and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10750960B2 (en) | Passive arrythmias detection based on photoplethysmogram (PPG) inter-beat intervals and morphology | |
| CN109157202B (en) | Cardiovascular disease early warning system based on multi-physiological signal deep fusion | |
| EP3117767B1 (en) | Processing biological data | |
| CN107569226B (en) | The method and application of HRV are obtained based on piezoelectric sensing | |
| US7862515B2 (en) | Apparatus for detecting sleep apnea using electrocardiogram signals | |
| Oweis et al. | QRS detection and heart rate variability analysis: A survey | |
| CN102038497B (en) | Electrocardiosignal noise analysis method | |
| US8892181B2 (en) | Non-invasive fetal monitoring | |
| WO2020006845A1 (en) | Health reserve evaluation method, and device and application thereof | |
| KR20210148439A (en) | Wireless physiological monitoring device and systems | |
| Tadi et al. | Seismocardiography: Toward heart rate variability (HRV) estimation | |
| CN107126203A (en) | Human health information measures display system in real time | |
| CN108968946A (en) | A kind of female incretion management system based on HRV analysis | |
| CN109512409A (en) | A kind of cardiovascular health assessment device and its application method | |
| WO2016168979A1 (en) | Vital sign analysis method and system | |
| CN106108844B (en) | A kind of method and apparatus of determining sleep stage | |
| CN106108845B (en) | A kind of method and apparatus of determining sleep stage | |
| Surrel et al. | Low-power wearable system for real-time screening of obstructive sleep apnea | |
| CN105266764A (en) | Traditional Chinese medicine Zong qi measurement and evaluation device | |
| GB2469547A (en) | Measurement of heart rate variability | |
| CN113100725A (en) | Health state rapid detection device and method based on optical fiber sensor | |
| CN106333674B (en) | Sleep cycle detection method and system in sleep state analysis | |
| CN215191495U (en) | Non-contact sign monitoring system | |
| WO2022120125A1 (en) | Time domain processing of periodic physiological signals | |
| US20230170087A1 (en) | Systems and methods for remote pregnancy monitoring and management |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181211 |