CN108245157A - A kind of anti-plagiarism method of measuring body composition instrument algorithm - Google Patents
A kind of anti-plagiarism method of measuring body composition instrument algorithm Download PDFInfo
- Publication number
- CN108245157A CN108245157A CN201711352441.8A CN201711352441A CN108245157A CN 108245157 A CN108245157 A CN 108245157A CN 201711352441 A CN201711352441 A CN 201711352441A CN 108245157 A CN108245157 A CN 108245157A
- Authority
- CN
- China
- Prior art keywords
- impedance
- heart rate
- signal
- measuring
- algorithm
- 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.)
- Granted
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/053—Measuring electrical impedance or conductance of a portion of the body
- A61B5/0537—Measuring body composition by impedance, e.g. tissue hydration or fat content
-
- 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
-
- 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
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Surgery (AREA)
- General Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Veterinary Medicine (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Public Health (AREA)
- Animal Behavior & Ethology (AREA)
- Physics & Mathematics (AREA)
- Cardiology (AREA)
- Physiology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychiatry (AREA)
- Signal Processing (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
- Investigating Or Analyzing Materials By The Use Of Electric Means (AREA)
Abstract
The invention discloses a kind of anti-plagiarism methods of measuring body composition instrument algorithm, and this method comprises the following steps：101st, impedance signal is measured；102nd, heart rate signal is extracted from above-mentioned impedance signal；103rd, it recognizes correct heart rate feature and then enters step 104, otherwise exit；104th, bioelectrical impedance analysis algorithm is called to carry out human body component parameter calculating.The present invention can effectively defend the violences such as simulation test to test, and then crack the attack of body constituent measuring instrument bioelectrical impedance analysis algorithm, play the role of better protective constituent measuring instrument core algorithm, improve the safety and reliability of measuring instrument.
Description
Technical field
The invention belongs to the anti-plagiarism methods of bioelectrical impedance analysis instrument technical field, more particularly to measuring body composition instrument.
Background technology
Body fat scale bioelectrical impedance analysis instrument etc. in other words utilizes the weight of human body, height, age, gender and surveys
The human-body biological electrical impedance of amount as input parameter, is returned by big data analysis and with the control of other medical means and is divided
Analysis obtains bioelectrical impedance analysis algorithm, so as to export the composition parameter of human body, such as body fat rate, body moisture rate, body muscle mass
Etc., in order to which people carry out health analysis and reference.At present, different producers has different algorithms, but this algorithm
It is measured in the equipment such as Human fat balance by a large amount of analog samples (weight is simulated by weight machine, impedance passes through resistance simulation etc.),
The concrete numerical value of above-mentioned input and output parameter can be obtained, is easy for reversely obtaining above-mentioned human body by Fitting Analysis
Constituent analysis algorithm is very easy to crack, and is unfavorable for the safety and reliability of fat scale.
As patent application 201310712626.0 discloses a kind of side of the bioelectrical impedance analysis based on eight sections of impedance models
Method, including：According to input current and voltage is measured, using eight sections of human body impedance models, obtains six having about human body impedance
Imitate expression formula；Using five sections of impedance models of human body, left and right upper limb impedance value difference and left and right lower limb impedance value difference are obtained；It calculates
Obtain the expression formula of every section of human body impedance；According to the expression of different input currents and every section of human body impedance at least more than two
Formula obtains human body impedance value at least more than two；Choose one group of best eight sections of impedance value, and one group according to selection most preferably
Eight sections of impedance values, determine model of fit；The training in model of fit using multigroup known sample obtains the unknown system of model of fit
Number, and obtain human body component predictor formula；According to human body component predictor formula, unknown sample is analyzed, obtain human body into
Divide parameter.Using the method for the present invention, it is more accurate to analyze the human body component come.
Invention content
Based on this, therefore the present invention primary mesh be to provide a kind of anti-plagiarism method of measuring body composition instrument algorithm,
This method causes the difficulty that the form by analogue measurement reversely derives algorithm to increase, and the calculation is protected so as to play to a certain extent
The effect of method improves the safety and reliability of measuring instrument.
Another mesh of the present invention it is to provide a kind of anti-plagiarism method of measuring body composition instrument algorithm, this method is real
Existing simplicity can improve the accuracy of measurement at low cost.
To achieve the above object, the technical scheme is that：
A kind of anti-plagiarism method of measuring body composition instrument algorithm, it is characterised in that this method comprises the following steps：
101st, impedance signal is measured；
102nd, heart rate signal is extracted from above-mentioned impedance signal；
103rd, it recognizes correct heart rate feature and then enters step 104, otherwise exit；
104th, bioelectrical impedance analysis algorithm is called to carry out human body component parameter calculating.
In the step 101, the impedance signal of human body is measured by measuring electrode.
In the step 102, heart rate signal is extracted by heart rate extraction unit.
Further, the heart rate signal include according to the wave crest and/or trough of impedance signal carry out heart rate feature recognition and/
Or rate calculation.
Further, in the step 103, the heart rate signal feature recognition specifically identifies the point that an impedance declines
Peak-to-peak signal, and meet scheduled amplitude threshold and width threshold value.
Further, in the step 103, the heart rate signal feature recognition specifically identifies an impedance signal phase
The duration between amplitude and adjacent peaks or trough between adjacent wave peak and trough.
The measuring body composition instrument at least has impedance measuring unit and processing unit, and wherein impedance measuring unit includes
At least two excitation electrode, 2 measuring electrodes, impedance processing unit, for the measurement of human body impedance；The processing unit is used for
It is analyzed according to the impedance signal that the impedance measuring unit measures, including bioelectrical impedance analysis unit, for according to impedance
And other physiological parameters calculate the constituent of human body, including fat content, Lean mass, moisture；Further include heart rate
Extraction unit for extracting heart rate from impedance signal, is known including the use of wave crest/trough of impedance signal to extract heart rate feature
Other and/or rate calculation.
The anti-plagiarism method of body constituent measuring instrument algorithm of the present invention can effectively defend the violences such as simulation test
Test, and then the attack of body constituent measuring instrument bioelectrical impedance analysis algorithm is cracked, play better protective constituent measuring instrument core
The effect of center algorithm improves the safety and reliability of measuring instrument.
Meanwhile this method can also improve the accuracy of measurement at low cost.
Description of the drawings
Fig. 1 is the structure chart that the present invention implements Human fat balance.
Fig. 2 is the structure diagram that the present invention implements Human fat balance.
Fig. 3 is that the present invention implements impedance signal oscillogram.
Fig. 4 is that the present invention implements instead to plagiarize flow chart.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, it is right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Shown in Fig. 1, Human fat balance 100 as shown in Figure 1 is one kind of body composition analysis instrument, and that includes structure 101, peaces
Electrode on structure 101, including measuring electrode 105, measuring electrode 104 and excitation electrode 106, excitation electrode
103, for the measurement of impedance；Display screen 102 is further included, for showing information.Electrode 103~106, display screen 102 etc. are electrical
The control mainboard (because it is the prior art, therefore not shown) of Human fat balance 100 is connected to, forms the electronic section of Human fat balance.
The structure chart of the electronic section of Human fat balance 100 is illustrated in figure 2, wherein impedance measuring unit 108 includes electrode 103
~106, impedance processing unit 107, for the measurement of human body impedance signal；It is single that impedance measuring unit 108 is electrically connected to processing
Member 110.Processing unit 110 obtains impedance signal from impedance measuring unit 108, and passes through bioelectrical impedance analysis unit 109 and realize
Bioelectrical impedance analysis based on human body impedance, including such as Determination of Total Body Fat, moisture, Lean mass；Additionally include the heart
Rate extraction unit extracts heart rate or heart rate signature waveform by the waveform of impedance.
Impedance signal waveform as shown in Figure 3 illustrates a typical impedance pulse signal.Heartbeat drives blood
It is periodically flowed in body vessel, the minor change of impedance, therefore the human body life measured from impedance measuring unit 108 can be caused
It is observed that this variation in object electrical impedance waveform, here it is impedance heart rate impedance pulse signal in other words, as shown in Figure 3.
The adjacent wave crest of Fig. 3 middle impedance waves and the direct height difference H 1 of trough are the amplitude of Impedance Wave, and the adjacent wave crest of Impedance Wave it
Between time difference T1 be Impedance Wave period.Correct pulse/heart rate signal must meet in amplitude and on the period scheduled threshold
Value.For example, the heart rate of normal person should thus give the requirement of Impedance Wave Ct value between 40~200 beats/min,
In addition amplitude thus gives the amplitude threshold of Impedance Wave generally in 1ohm or so.Meet the impedance of period and amplitude threshold
Wave signal can be considered as just legal heart rate signal, could be used to calculate heart rate.In addition, impedance heart rate signal also has fixed spy
Sign, such as shown in Fig. 3 dashed circles, be the spiking of a decline, there is certain width L0 and height H0, there is this
The Impedance Wave signal of sample feature could calculate real heart rate signal.
The algorithm of body constituent measuring instrument as shown in Figure 4 is counter to plagiarize flow, specifically：
S1, impedance signal is measured by impedance measuring unit 108；
S2, the heart rate signal feature in impedance signal is extracted by heart rate extraction unit 111, including width as shown in Figure 3
Degree and period and the decline width L0 of spike and height H0；
Whether S3, amplitude H1 and cycle T 1 meet amplitude threshold and Ct value respectivelyEnter next step if meeting,
Otherwise terminate this flow；
S4, continue to judge decline peaks characteristic in impedance heart rate signal, whether width L0 and height H0 meet point respectively
Peak width threshold value and spike height thresholdEnter next step if meeting, otherwise terminate this flow.
S5, bioelectrical impedance analysis unit 109 are calculated by impedance and other physiological parameters (gender, age, weight, height)
Human body component, including fat content, Lean mass, moisture etc..
Therefore, the present invention can effectively defend the violences such as simulation test to test, and then crack body constituent measuring instrument human body
Better protective constituent measuring instrument core algorithm is played the role of in the attack of constituent analysis algorithm, improves the safety of measuring instrument
Property and reliability.
Meanwhile this method can also improve the accuracy of measurement at low cost.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement made within refreshing and principle etc., should all be included in the protection scope of the present invention.
Claims (7)
1. a kind of anti-plagiarism method of measuring body composition instrument algorithm, it is characterised in that this method comprises the following steps：
101st, impedance signal is measured；
102nd, heart rate signal is extracted from above-mentioned impedance signal；
103rd, it recognizes correct heart rate feature and then enters step 104, otherwise exit；
104th, bioelectrical impedance analysis algorithm is called to carry out human body component parameter calculating.
2. the anti-plagiarism method of measuring body composition instrument algorithm as described in claim 1, it is characterised in that the step 101
In, pass through the impedance signal of measuring electrode measurement human body.
3. the anti-plagiarism method of measuring body composition instrument algorithm as described in claim 1, it is characterised in that the step 102
In, heart rate signal is extracted by heart rate extraction unit.
4. the anti-plagiarism method of measuring body composition instrument algorithm as claimed in claim 3, it is characterised in that the heart rate signal
Heart rate feature recognition and/or rate calculation are carried out including the wave crest according to impedance signal and/or trough.
5. the anti-plagiarism method of measuring body composition instrument algorithm as claimed in claim 4, it is characterised in that the step 103
In, the heart rate signal feature recognition specifically identifies the spiking that an impedance declines, and meets scheduled amplitude threshold
And width threshold value.
6. the anti-plagiarism method of measuring body composition instrument algorithm as claimed in claim 5, it is characterised in that the step 103
In, the heart rate signal feature recognition specifically identifies the amplitude between an impedance signal adjacent peaks and trough, Yi Jixiang
Duration between adjacent wave peak or trough.
7. the anti-plagiarism method of measuring body composition instrument algorithm as described in claim 1, it is characterised in that the human body component
Measuring instrument at least have impedance measuring unit and processing unit, wherein impedance measuring unit include at least two excitation electrode, 2
Measuring electrode, impedance processing unit, for the measurement of human body impedance；The processing unit is used for according to the impedance measuring unit
The impedance signal of measurement is analyzed, including bioelectrical impedance analysis unit, for being calculated according to impedance and other physiological parameters
The constituent of human body, including fat content, Lean mass, moisture；Heart rate extraction unit is further included, for believing from impedance
Heart rate is extracted in number, heart rate feature recognition and/or rate calculation are extracted including the use of wave crest/trough of impedance signal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711352441.8A CN108245157B (en) | 2017-12-15 | 2017-12-15 | Anti-plagiarism method of human body composition measuring instrument algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711352441.8A CN108245157B (en) | 2017-12-15 | 2017-12-15 | Anti-plagiarism method of human body composition measuring instrument algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108245157A true CN108245157A (en) | 2018-07-06 |
| CN108245157B CN108245157B (en) | 2021-05-25 |
Family
ID=62723002
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711352441.8A Active CN108245157B (en) | 2017-12-15 | 2017-12-15 | Anti-plagiarism method of human body composition measuring instrument algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108245157B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109350055A (en) * | 2018-09-05 | 2019-02-19 | 广东小天才科技有限公司 | Physiological parameter detection and analysis method, terminal and computer readable storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1264570A (en) * | 1999-02-22 | 2000-08-30 | 株式会社百利达 | Hand biological impedance tester |
| US20040116819A1 (en) * | 2001-10-01 | 2004-06-17 | Eckhard Alt | Congestive heart failure monitor and ventilation measuring implant |
| US20090024044A1 (en) * | 2007-07-17 | 2009-01-22 | The General Electric Company | Data recording for patient status analysis |
| US20090275854A1 (en) * | 2008-04-30 | 2009-11-05 | Zielinski Todd M | System and method of monitoring physiologic parameters based on complex impedance waveform morphology |
| CN104706343A (en) * | 2013-12-11 | 2015-06-17 | 三星电子株式会社 | Bioimpedance sensor array for heart rate detection |
| CN105852839A (en) * | 2016-03-23 | 2016-08-17 | 中山大学 | Heart rate measuring method and device based on bioelectrical impedance technology |
| CN106175773A (en) * | 2016-07-11 | 2016-12-07 | 芯海科技（深圳）股份有限公司 | Hand held multiband impedance breath signal measures system and measuring method |
-
2017
- 2017-12-15 CN CN201711352441.8A patent/CN108245157B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1264570A (en) * | 1999-02-22 | 2000-08-30 | 株式会社百利达 | Hand biological impedance tester |
| US20040116819A1 (en) * | 2001-10-01 | 2004-06-17 | Eckhard Alt | Congestive heart failure monitor and ventilation measuring implant |
| US20090024044A1 (en) * | 2007-07-17 | 2009-01-22 | The General Electric Company | Data recording for patient status analysis |
| US20090275854A1 (en) * | 2008-04-30 | 2009-11-05 | Zielinski Todd M | System and method of monitoring physiologic parameters based on complex impedance waveform morphology |
| CN104706343A (en) * | 2013-12-11 | 2015-06-17 | 三星电子株式会社 | Bioimpedance sensor array for heart rate detection |
| CN105852839A (en) * | 2016-03-23 | 2016-08-17 | 中山大学 | Heart rate measuring method and device based on bioelectrical impedance technology |
| CN106175773A (en) * | 2016-07-11 | 2016-12-07 | 芯海科技（深圳）股份有限公司 | Hand held multiband impedance breath signal measures system and measuring method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109350055A (en) * | 2018-09-05 | 2019-02-19 | 广东小天才科技有限公司 | Physiological parameter detection and analysis method, terminal and computer readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108245157B (en) | 2021-05-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11547344B2 (en) | System and method for post-stroke rehabilitation and recovery using adaptive surface electromyographic sensing and visualization | |
| CN106108889B (en) | Electrocardiogram classification method based on deep learning algorithm | |
| FI124278B (en) | Measuring device and method for indicating strain | |
| Del Vecchio et al. | The relative strength of common synaptic input to motor neurons is not a determinant of the maximal rate of force development in humans | |
| CN107137071A (en) | It is a kind of to analyze the method that heart impact signal is used for calculating short-term heart beat value | |
| TWI583355B (en) | Heart rate detection method and heart rate detection device | |
| Haddad et al. | Fracture prediction of cardiac lead medical devices using Bayesian networks | |
| JP6748076B2 (en) | Cardiopulmonary fitness evaluation | |
| WO2018106146A3 (en) | Method and system for the non-invasive screening of physiological parameters and pathologies | |
| Fling et al. | Motor unit synchronization in FDI and biceps brachii muscles of strength-trained males | |
| Cao et al. | Surface EMG-force modelling for the biceps brachii and its experimental evaluation during isometric isotonic contractions | |
| Brandon et al. | Reliability of a combined biomechanical and surface electromyographical analysis system during dynamic barbell squat exercise | |
| CN108245157A (en) | A kind of anti-plagiarism method of measuring body composition instrument algorithm | |
| US9901267B2 (en) | Cardionpulmonary function evaluating apparatus and cardionpulmonary function evaluating method | |
| Maheedhar et al. | StayFit: A wearable application for Gym based power training | |
| Guidi et al. | Heart rate variability analysis during muscle fatigue due to prolonged isometric contraction | |
| CN106604679A (en) | Heartbeat detecting method and heartbeat detecting device | |
| EP3372152B1 (en) | Apparatus, method and computer program for determining whether a measured pulse waveform contains noise | |
| CN114176532A (en) | Clinical verification method for determining cfPWV parameters and application system thereof | |
| Hernandez et al. | Traditional sEMG fatigue indicators applied to a real-world sport functional activity: Roundhouse kick | |
| Hassan et al. | Derivation of simple muscle fatigue index for biceps muscle based on surface electromyography temporal characteristics | |
| Narayanan et al. | Generation and analysis of synthetic surface electromyography signals under varied muscle fiber type proportions and validation using recorded signals | |
| Holobar et al. | A signal-based approach for assessing the accuracy of high-density surface EMG decomposition | |
| Sowmya et al. | Analysis of Survival Probability and Its Association with Time to Task Failure in Induced Fatiguing Dynamic Contractions of Biceps Brachii Muscle using Surface Electromyography | |
| US20230039042A1 (en) | Muscle activation, and associated algorithms, systems and methods |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |