CN107049240A - Physical age computational methods and bodily fat measurement system - Google Patents

Physical age computational methods and bodily fat measurement system Download PDF

Info

Publication number
CN107049240A
CN107049240A CN201710037290.0A CN201710037290A CN107049240A CN 107049240 A CN107049240 A CN 107049240A CN 201710037290 A CN201710037290 A CN 201710037290A CN 107049240 A CN107049240 A CN 107049240A
Authority
CN
China
Prior art keywords
age
virtual muscle
body weight
virtual
physical
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
Application number
CN201710037290.0A
Other languages
Chinese (zh)
Inventor
茆裕源
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Inventec Appliances Shanghai Corp
Inventec Appliances Pudong Corp
Inventec Appliances Corp
Original Assignee
Inventec Appliances Shanghai Corp
Inventec Appliances Pudong Corp
Inventec Appliances Corp
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Inventec Appliances Shanghai Corp, Inventec Appliances Pudong Corp, Inventec Appliances Corp filed Critical Inventec Appliances Shanghai Corp
Priority to CN201710037290.0A priority Critical patent/CN107049240A/en
Priority to TW106108222A priority patent/TWI629048B/en
Publication of CN107049240A publication Critical patent/CN107049240A/en
Pending legal-status Critical Current

Links

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4869Determining body composition
    • A61B5/4872Body fat
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01GWEIGHING
    • G01G19/00Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/44Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing persons
    • G01G19/50Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing persons having additional measuring devices, e.g. for height

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Surgery (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Pathology (AREA)
  • Veterinary Medicine (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physiology (AREA)
  • Psychiatry (AREA)
  • Signal Processing (AREA)
  • General Physics & Mathematics (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)

Abstract

A kind of physical age computational methods and bodily fat measurement system.Physical age computational methods comprise the following steps:Several body parameters are received by a parameters unit.A body fat rate is calculated according to this little body parameter.One virtual muscle body weight is calculated according to body fat rate.One virtual muscle ratio is calculated according to virtual muscle body weight.Physical age is calculated according to virtual muscle ratio.

Description

Physical age computational methods and bodily fat measurement system
Technical field
The invention relates to a kind of computational methods and measuring system, and in particular to a kind of physical age calculating side Method and bodily fat measurement system.
Background technology
Physical age judges healthy index to be a kind of, and body is shown with the gap of physical age and actual age Health status.Physical age is calculated in the past, it is necessary to measured by substantial amounts of reality in advance and set up physical age database. Then, when needing to calculate physical age, by the muscle weight to measure body of current impedance, and according to the muscle of body Weight and physical age database are to extrapolate physical age.However, by the muscle weight to measure body of current impedance, Must possess specific measurement apparatus, it is necessary to higher cost, and measuring speed is slower, also easily by environmental factor during measurement Influence, such as humidity.Therefore, how to improve disadvantages mentioned above has turned into the direction that industry is made great efforts.
The content of the invention
The present invention is related to a kind of physical age computational methods and bodily fat measurement system, and it is using virtual muscle weight and virtually Muscle ratio calculates physical age.
According to an aspect of the invention, it is proposed that a kind of physical age computational methods.Physical age computational methods include following Step:Multiple body parameters are received by a parameters unit.A body fat rate is calculated according to this little body parameter.According to body fat rate Calculate a virtual muscle body weight.One virtual muscle ratio is calculated according to virtual muscle body weight.Body is calculated according to virtual muscle ratio Age.
According to another aspect of the invention, it is proposed that a kind of bodily fat measurement system.Bodily fat measurement system includes a parameters unit And a processing unit.Parameters unit is to receive multiple body parameters.Processing unit is to receive this little body parameter, to analyze Go out a body fat rate.Processing unit calculates a virtual muscle body weight according to body fat rate, and a virtual flesh is calculated according to virtual muscle body weight Meat ratio, and the body age is calculated according to virtual muscle ratio.
Brief description of the drawings
More preferably understand in order to which the above-mentioned and other aspect to the present invention has, preferred embodiment cited below particularly, and coordinate attached Figure, is described in detail below:
Fig. 1 illustrates the flow chart of the physical age computational methods of the present invention.
Fig. 2 illustrates the block diagram of bodily fat measurement system according to an embodiment of the invention.
Fig. 3 illustrates the block diagram of bodily fat measurement system according to another embodiment of the present invention.
Fig. 4 illustrates the block diagram of bodily fat measurement system according to another embodiment of the present invention.
【Symbol description】
S102、S104、S106、S108、S110:Process step
100、200、300:Bodily fat measurement system
102、202、302:Parameters unit
202a、302a:Intelligent terminal
202b:Batheroom scale
104、204、304:Processing unit
206、306:Network
Embodiment
It refer to Fig. 1 and Fig. 2, Fig. 1 illustrate the flow chart of physical age computational methods of the invention.Fig. 2 is illustrated according to this Invent the block diagram of the bodily fat measurement system 100 of an embodiment.Bodily fat measurement system 100 includes parameters unit 102 and processing is single Member 104.Parameters unit 102 is, for example, a touch control screen, can receive user's input data.Parameters unit 102 is, for example, one Batheroom scale, the weight of measurable user simultaneously can receive user's input data.Processing unit 104 is, for example, a chip, an electricity The computer readable media of road plate or storage arrays program.
In step S102, multiple body parameters are received by parameters unit 102.Body parameter includes height, body weight, property The other and age.In one embodiment, parameters unit 102 is touch control screen, and user inputs multiple bodies by parameters unit 102 Body parameter, such as height, body weight, sex and age.In another embodiment, parameters unit 102 is batheroom scale, and user will be many Individual body parameter, such as height, sex and age are inputted to parameters unit 102, and measure body ginseng by parameters unit 102 Number, such as body weight.In this embodiment, due to body weight compared to other body parameters (namely height, sex and age) compared with Easily change, therefore the body weight of user can be obtained by way of measuring instantly, to obtain correct body parameter.
In step S104, processing unit 104 calculates body fat rate according to this little body parameter.In one embodiment, locate Reason unit 104 first calculates body-mass index (Body Mass Index, BMI), can be calculated by following formula, body quality refers to Square of number=body weight (kilogram)/height (rice).Then, processing unit 104 is calculated according to sex, age and body-mass index Body fat rate.The formula for the criterion that body fat rate can be moved council's suggestion by the U.S. is obtained.Body fat rate=(body quality refers to Number * 1.2)+(age * 0.23) -5.4- (sex * 10.8), if wherein male, then sex is 1;If women, then sex is 0.However, in the present invention, the calculation of body fat rate is not limited to this, it can also be calculated using other criterions.
In step S106, processing unit 104 calculates virtual muscle body weight according to body fat rate.Processing unit 104 is basis The body fat rate obtained in the body weight and step S104 that are obtained in step S102 calculates virtual muscle body weight.Specifically, handle single Member 104 calculates virtual muscle body weight, virtual muscle body weight (kilogram)=body weight (kilogram)-(body fat rate * body weight according to following formula (kilogram)).Wherein body fat rate is multiplied by the weight (kilogram) that body weight is body fat.Because the muscle mass in body is influence body year One of age important factor.Therefore, virtual muscle body weight proposed by the present invention is to remove the fat in body to be calculated.
In step S108, processing unit 104 calculates virtual muscle ratio according to virtual muscle body weight.It can be calculated by following formula Go out, virtual muscle ratio=body weight (kilogram)/virtual muscle body weight (kilogram).
Then, in step S110, processing unit 104 calculates physical age according to virtual muscle ratio.Specifically, handle Unit 104 is to calculate physical age by the way that whether virtual muscle ratio is equal to a special value for standard, and according to virtual muscle The size of ratio increases or decreases physical age.In one embodiment, it is standard with virtual muscle ratio 1.25, when virtual muscle ratio For 1.25 when, then processing unit 104 judges that physical age is consistent with the age, that is, physical age be equal to step S102 in The age arrived.When virtual muscle ratio often increases by 0.015 based on special value, then physical age increase is one-year-old, and works as Virtual muscle ratio often reduces 0.015 based on special value, then the physical age reduces one-year-old.As an example it is assumed that step The age that S102 is obtained is 20 years old, then when virtual muscle ratio is 1.25, then processing unit 104 judges physical age for 20 years old. When virtual muscle ratio is 1.265, then processing unit 104 judges physical age for 21 years old.When virtual muscle ratio is 1.235, Then processing unit 104 judges physical age for 19 years old.
Fig. 3 is refer to, it illustrates the block diagram of bodily fat measurement system 200 according to another embodiment of the present invention.Body fat is surveyed Amount system 200 includes a parameters unit 202 and a processing unit 204.In this embodiment, parameters unit 202 includes an intelligence A terminal 202a and batheroom scale 202b.User can pass through the input body parameter of network 206 using intelligent terminal 202a.Body weight Meter 202b then can actually measure the body weight of user.Processing unit 204 is, for example, then the remote server for being connected to network 206. It is single that the body weight that the every body parameter and batheroom scale that intelligent terminal 202a is inputted are obtained can be transferred to processing by network 206 Member 204 carries out computing, and wherein processing unit 204 can be only fitted to network 206, intelligent terminal 202a or batheroom scale 202b, not do Limitation.Processing unit 204 is calculated after physical age, and intelligent terminal 202a or batheroom scale 202b are being back to by network, with Inform its physical age of user.
Fig. 4 is refer to, it illustrates the block diagram of bodily fat measurement system 300 according to another embodiment of the present invention.Body fat is surveyed Amount system 300 includes a parameters unit 302 and a processing unit 304.In this embodiment, parameters unit 302 includes an intelligence Terminal 302a.User can pass through the input body parameter of network 306 using intelligent terminal 302a.Processing unit 304 is then for example It is the remote server for being connected to network 306.Every body parameter that intelligent terminal 302a is inputted can be transmitted by network 306 Computing is carried out to processing unit 304, wherein processing unit 304 can be only fitted to network 306, intelligent terminal 302a, not be limited. Processing unit 304 is calculated after physical age, and intelligent terminal 302a is being back to by network, to inform user's its body year Age.
It can calculate virtual muscle weight and virtual muscle ratio to calculate body consequently, it is possible to which user must only input body parameter The body age.Without the muscle weight to measure body by current impedance, and muscle weight and body year according to body Age database is to extrapolate physical age.Therefore, required hardware cost is relatively low and calculating speed is very fast.
In summary, although the present invention is disclosed above with preferred embodiment, so it is not limited to the present invention.This hair Those of ordinary skill in bright art, without departing from the spirit and scope of the present invention, when can make it is various change with profit Decorations.Therefore, protection scope of the present invention is worked as and is defined depending on the scope of the claims.

Claims (12)

1. a kind of physical age computational methods, it is characterised in that including:
Multiple body parameters are received by a parameters unit;
One body fat rate is calculated according to the multiple body parameter;
One virtual muscle body weight is calculated according to the body fat rate;
One virtual muscle ratio is calculated according to the virtual muscle body weight;And
The body age is calculated according to the virtual muscle ratio.
2. physical age computational methods as claimed in claim 1, it is characterised in that the multiple body parameter at least includes one Body weight and an age.
3. physical age computational methods as claimed in claim 2, it is characterised in that the step of receiving the multiple body parameter Including:
The age is inputted by the parameters unit;And
The body weight is measured by the parameters unit.
4. physical age computational methods as claimed in claim 2, it is characterised in that the virtual muscle body weight is that the body weight is subtracted The body fat rate and the product of the body weight.
5. physical age computational methods as claimed in claim 2, it is characterised in that the virtual muscle ratio is the body weight divided by should Virtual muscle body weight, when the virtual muscle ratio is 1.25, then the physical age is the age.
6. physical age computational methods as claimed in claim 5, it is characterised in that using the virtual muscle ratio as 1.25 be mark Standard, when the virtual muscle ratio often increases by 0.015, then physical age increase is one-year-old, and when the virtual muscle ratio is often reduced 0.015, then physical age reduction is one-year-old.
7. a kind of bodily fat measurement system, it is characterised in that including:
One parameters unit, to receive multiple body parameters;
One processing unit, to receive the multiple body parameter, to analyze a body fat rate;
Wherein, the processing unit calculates a virtual muscle body weight according to the body fat rate, and calculates one according to the virtual muscle body weight Virtual muscle ratio, and the body age is calculated according to the virtual muscle ratio.
8. bodily fat measurement system as claimed in claim 7, it is characterised in that the multiple body parameter at least includes a body weight And age.
9. bodily fat measurement system as claimed in claim 8, it is characterised in that the parameters unit is to measure the body weight.
10. bodily fat measurement system as claimed in claim 9, it is characterised in that the age is set by an intelligent terminal, and is carried Supply the processing unit.
11. bodily fat measurement system as claimed in claim 8, it is characterised in that the virtual muscle ratio is the body weight divided by the void Intend muscle body weight, and when the virtual muscle ratio is 1.25, then the physical age is the age.
12. bodily fat measurement system as claimed in claim 11, it is characterised in that using the virtual muscle ratio as 1.25 be standard, When the virtual muscle ratio often increases by 0.015, then physical age increase is one-year-old, and when the virtual muscle ratio often reduces 0.015, Then the physical age reduces one-year-old.
CN201710037290.0A 2017-01-18 2017-01-18 Physical age computational methods and bodily fat measurement system Pending CN107049240A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201710037290.0A CN107049240A (en) 2017-01-18 2017-01-18 Physical age computational methods and bodily fat measurement system
TW106108222A TWI629048B (en) 2017-01-18 2017-03-13 Physical age calculating method and body fat measuring system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710037290.0A CN107049240A (en) 2017-01-18 2017-01-18 Physical age computational methods and bodily fat measurement system

Publications (1)

Publication Number Publication Date
CN107049240A true CN107049240A (en) 2017-08-18

Family

ID=59599087

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710037290.0A Pending CN107049240A (en) 2017-01-18 2017-01-18 Physical age computational methods and bodily fat measurement system

Country Status (2)

Country Link
CN (1) CN107049240A (en)
TW (1) TWI629048B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107913063A (en) * 2017-10-31 2018-04-17 北京小米移动软件有限公司 Measure method, apparatus, Human fat balance and the storage medium of body fat rate
CN108417251A (en) * 2018-02-24 2018-08-17 优成商业管理(沈阳)有限公司 Nutritious food generation method, device, equipment and medium

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6321112B1 (en) * 1993-08-12 2001-11-20 Omron Corporation Device to provide data as a guide to health management
CN1398572A (en) * 2001-07-19 2003-02-26 株式会社百利达 Living body measuring equipment
JP2007195744A (en) * 2006-01-26 2007-08-09 Omron Healthcare Co Ltd Body composition meter
CN102088901A (en) * 2008-03-18 2011-06-08 欧姆龙健康医疗事业株式会社 Body composition meter
CN103429163A (en) * 2011-01-05 2013-12-04 皇家飞利浦电子股份有限公司 Device and method for determining actual tissue layer boundaries of a body
CN103687500A (en) * 2011-06-16 2014-03-26 N·V·努特里奇亚 Metabolic imprinting effects of specifically designed lipid component
CN104224172A (en) * 2013-06-19 2014-12-24 株式会社百利达 Body composition measuring apparatus and body composition measurement system
CN105534487A (en) * 2016-03-10 2016-05-04 苏州凯丰电子电器有限公司 Body fat rate detection device

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001321343A (en) * 2000-05-12 2001-11-20 Misaki:Kk Health index measuring device
US9747417B2 (en) * 2013-11-14 2017-08-29 Mores, Inc. Method and apparatus for enhanced personal care
WO2011063032A1 (en) * 2009-11-17 2011-05-26 Veralight, Inc. Method and apparatus to detect coronary artery calcification or disease
CN102971005A (en) * 2010-06-24 2013-03-13 贝林格尔.英格海姆国际有限公司 Diabetes therapy
CN105769341A (en) * 2014-12-23 2016-07-20 珠海云麦科技有限公司 Method and equipment for displaying body data

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6321112B1 (en) * 1993-08-12 2001-11-20 Omron Corporation Device to provide data as a guide to health management
CN1398572A (en) * 2001-07-19 2003-02-26 株式会社百利达 Living body measuring equipment
JP2007195744A (en) * 2006-01-26 2007-08-09 Omron Healthcare Co Ltd Body composition meter
CN102088901A (en) * 2008-03-18 2011-06-08 欧姆龙健康医疗事业株式会社 Body composition meter
CN103429163A (en) * 2011-01-05 2013-12-04 皇家飞利浦电子股份有限公司 Device and method for determining actual tissue layer boundaries of a body
CN103687500A (en) * 2011-06-16 2014-03-26 N·V·努特里奇亚 Metabolic imprinting effects of specifically designed lipid component
CN104224172A (en) * 2013-06-19 2014-12-24 株式会社百利达 Body composition measuring apparatus and body composition measurement system
CN105534487A (en) * 2016-03-10 2016-05-04 苏州凯丰电子电器有限公司 Body fat rate detection device

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107913063A (en) * 2017-10-31 2018-04-17 北京小米移动软件有限公司 Measure method, apparatus, Human fat balance and the storage medium of body fat rate
CN108417251A (en) * 2018-02-24 2018-08-17 优成商业管理(沈阳)有限公司 Nutritious food generation method, device, equipment and medium

Also Published As

Publication number Publication date
TWI629048B (en) 2018-07-11
TW201826998A (en) 2018-08-01

Similar Documents

Publication Publication Date Title
CN107086944A (en) A kind of method for detecting abnormality and device
CN109493244A (en) Method and Related product based on prediction model configuration demand for insurance
CN104155580B (en) Voltage sag source positioning method with association analysis and electric power calculation being combined
Rodríguez-Álvarez et al. ROC curve and covariates: extending induced methodology to the non-parametric framework
CN107767191A (en) A kind of method based on medical big data prediction medicine sales trend
CN107818824A (en) A kind of health model construction method and terminal for health evaluating
CN102081143B (en) Estimation method and system of battery capacity
CN109840671A (en) Operational development effect calculates equipment, operational development effect calculation method and recording medium
CN107146160A (en) Customer insured's analysis on the health status method and server
CN104376174B (en) Alternating current line parameter identification and correction method based on line impedance ratio
CN107049240A (en) Physical age computational methods and bodily fat measurement system
US20190328322A1 (en) Information processing apparatus and operation method thereof
CN103995963A (en) Calculation method for product reliability
KR20140094761A (en) Method for checkweighing food and apparatus thereof
KR20170006313A (en) Device and method for providing food distributing information
CN202995735U (en) Intelligent measuring system
CN215952731U (en) Intelligent weight scale
CN102136110A (en) Method for generating specification and size comparison table for scale clothes ordering and scale clothes ordering production method
CN115394442A (en) Development evaluation method, device, equipment and medium
DE202015105998U1 (en) Nutritional evaluation system
Shi et al. Estimating the mean and variance from the five-number summary of a log-normal distribution
CN115542236A (en) Method and device for estimating running error of electric energy meter
Su Confidence intervals for quantiles using generalized lambda distributions
CN106779400A (en) Method of user's electricity index contrast with analyzing
TW201743273A (en) Production control device and production control program

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

Application publication date: 20170818

RJ01 Rejection of invention patent application after publication