JPH1156800A - Body composition estimation method, body composition estimation device, and computer-readable recording medium recording body composition estimation program - Google Patents

Abstract

(57) [Summary] [Problem] To individually calculate an accurate critical frequency. The disclosed body composition estimating method uses a multi-frequency current Ib applied to a subject's body to measure the subject's body's electrical impedance, and then obtains the subject's body based on the obtained electrical impedance for each frequency. Calculate the body impedance trajectory. Then, based on the obtained impedance locus, a critical frequency which is a frequency when both the reactance and the phase angle of the electric impedance are maximized is calculated.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a body composition estimation method, a body composition estimation apparatus, and a computer-readable recording medium on which a body composition estimation program is recorded. The present invention relates to a body composition estimating method, a body composition estimating apparatus, and a computer-readable recording medium that records a body composition estimating program, which are useful for estimating the state of distribution and body fat.

[0002]

2. Description of the Related Art In recent years, research on the electrical characteristics of living organisms has been conducted for the purpose of evaluating the body composition of humans and animals.
The electrical properties of living organisms vary significantly depending on the type of tissue or organ. For example, in the case of humans, the electrical resistivity of blood is around 150 Ωcm, whereas the electrical resistivity of bone and fat is 1 to 1. There is also 5 kΩ · cm. The electrical characteristics of the living body are determined by the bioelectric impedance (Bioelectric Impedanc
It is called e) and is measured by passing a small current between a plurality of electrodes attached to the body surface of a living body. From the bioelectrical impedance thus obtained, the body water distribution (extracellular fluid volume, intracellular fluid volume, the total body water volume (body fluid volume), etc.) of the subject and the state of body fat (body fat percentage) The method of estimating fat mass, lean mass, etc. is called the bioelectric impedance method ("Bioelectric impedance method as an evaluation method of body composition"), by Baumgartner, RN, etc.,
"Bioelectric impedance and its clinical application", Medical Electronics and Biotechnology, Hiroshi Kanai, 20 (3) Jun 1982, "Estimation of Water Distribution in Limbs by Impedance Method and Its Application",
Medical Electronics and Biotechnology, Makoto Haeno, 23 (6) 1985,
"Long-term measurement of urinary bladder volume by impedance method",
Ergonomics, written by Yasuo Kuchinomachi, 28 (3) 1992, etc.).

[0003] Bioelectric impedance is derived from the resistance of a living body to the current carried by ions in the body (resistance) and the reactance associated with various types of polarization processes created by cell membranes, tissue interfaces, or non-ionized tissue. Be composed. The capacitance (capacitance), which is the reciprocal of reactance, causes a time delay in current rather than voltage, and creates a phase shift (phase shift). This value is the arctangent of the ratio of reactance to resistance (arctangent), That is, it can be quantitatively determined as an electrical phase angle. The geometric relationship among the bioelectric impedance Z, the resistance R, the reactance X, and the electric phase angle φ depends on the frequency as shown by a solid line D as the impedance locus of the human body in FIG. At a frequency of 0 Hz, the bioelectrical impedance Z at the cell membrane-tissue interface is too high to conduct electricity. Thus, electricity flows only through the extracellular fluid and the measured bioelectrical impedance Z is purely resistance. Then, as the frequency increases,
The current penetrates the cell membrane, the reactance X increases, and the phase angle φ increases. The magnitude of the bioelectrical impedance Z is equal to the value of the vector defined by the formula (Z = R ² + X ² ). The frequency at which both the reactance X and the phase angle φ become maximum is the critical frequency f
C is one electrical characteristic value of the living body that is a conductive conductor. Beyond this critical frequency fc, the cell membrane-tissue interface loses its capacitive capacity and the reactance X decreases accordingly. At infinite frequency, the bioelectrical impedance again becomes purely equivalent to resistance.

Here, referring to the cells constituting the tissue of a living body, as shown in FIG.
Are surrounded by the cell membranes 2, 2,..., But the cell membranes 2, 2,.
Can be seen as a large capacitor. Therefore, the bioelectric impedance is, as shown in FIG. 12, an extracellular fluid impedance consisting only of extracellular fluid resistance 1 / Ye,
It can be considered as a parallel combined impedance of the intracellular fluid impedance formed by connecting the intracellular fluid resistance 1 / Yi and the cell membrane capacity Cm in series. Therefore, in the conventional body composition estimation method for estimating the body water distribution and body fat state of the subject using the bioelectric impedance method, the frequency of the sinusoidal alternating current to be passed between the surface electrodes attached to the limbs is determined. Is fixed to 50 kHz (FIG. 10) close to the critical frequency fC, and the bioelectrical impedance of the subject is measured assuming that the critical frequency is fC, and the parallel synthesis of the extracellular fluid impedance and the intracellular fluid impedance is performed. The impedance was obtained, and the body water distribution and body fat state of the subject were estimated based on the obtained parallel combined impedance. For example, the body fat percentage is calculated from the obtained parallel combined impedance, the lean body mass is obtained from the calculated body fat percentage, and it is assumed that about 73.2% of the lean body mass is water. Was calculated.

[0005]

In the above-mentioned conventional body composition estimation method, the frequency of the sinusoidal alternating current to be passed between the surface electrodes of the limbs is fixed at 50 kHz which is close to the critical frequency fC. The critical frequency fc is considered to be a frequency that separates the high-frequency region and the low-frequency region of the human body, and differs from individual to individual. Therefore, if the frequency is fixed at 50 kHz, there is a drawback that an accurate critical frequency fc cannot be calculated. Was.

The present invention has been made in view of the above circumstances, and has a body composition estimation method, a body composition estimation apparatus, and a computer-readable recording program for recording a body composition estimation program capable of individually calculating an accurate critical frequency. It is intended to provide a medium.

[0007]

According to a first aspect of the present invention, there is provided a method for estimating a body composition comprising the steps of: applying a multi-frequency probe current to a body of a subject; Measure the impedance, based on the electrical impedance for each frequency obtained by the measurement, calculate the impedance locus of the body of the subject, based on the impedance locus obtained by the calculation, the reactance of the electrical impedance and It is characterized in that a critical frequency which is a frequency when both of the phase angles are maximized is calculated.

According to a second aspect of the present invention, there is provided the body composition estimating method according to the first aspect, wherein a water removal amount to be set in artificial dialysis is estimated based on the critical frequency. And

A body composition estimating method according to a third aspect of the present invention is the body composition estimating method according to the second aspect, wherein the water removal amount is given as a negative correlation with the critical frequency. Is used to estimate the water removal amount.

According to a fourth aspect of the present invention, there is provided a body composition estimating apparatus for generating a multi-frequency probe current, applying the generated probe current of each frequency to the body of the subject, and setting the electrical impedance of the body of the subject. Bioelectric impedance measuring means for measuring the impedance, the impedance locus calculating means for calculating the impedance locus of the body of the subject based on the electric impedance for each frequency measured by the bioelectric impedance measuring means, the impedance locus Critical frequency calculating means for calculating a critical frequency which is a frequency at which both the reactance and the phase angle of the electric impedance are maximized, based on the impedance locus calculated by the calculating means. .

A body composition estimating apparatus according to a fifth aspect of the present invention is the body composition estimating apparatus according to the fourth aspect, wherein a water removal amount estimating a water removal amount to be set in artificial dialysis based on the critical frequency. It is characterized by comprising means.

A body composition estimating apparatus according to a sixth aspect of the present invention is the body composition estimating apparatus according to the fifth aspect, wherein the water removal amount estimating means has a negative correlation between the water removal amount and the critical frequency. The water removal amount is estimated using a body composition estimation formula given as

A computer-readable recording medium on which a body composition estimating program according to the present invention is recorded is a body composition estimator for estimating a body water distribution and a body fat state of a subject by a computer. A computer-readable recording medium on which a program is recorded, wherein the body composition estimation program is based on an electrical impedance for each frequency measured by applying a multi-frequency probe current to a subject's body. Making use of a least-squares calculation method to calculate an impedance locus, and calculating a critical frequency that is a frequency when both the reactance and the phase angle of the electric impedance are maximized from the calculated impedance locus. It is characterized by.

[0014] A computer-readable recording medium recording the body composition estimation program according to the invention according to claim 8 relates to the computer-readable recording medium recording the body composition estimation program according to claim 7, and The estimation program is characterized by causing a computer to estimate a water removal amount to be set in artificial dialysis based on the critical frequency.

According to a ninth aspect of the present invention, there is provided a computer-readable recording medium having recorded thereon the body composition estimating program according to the eighth aspect of the present invention. The estimation program is characterized by causing a computer to estimate the amount of water removal using a body composition estimation formula given as having a negative correlation with the critical frequency.

[0016]

In the configuration of the present invention, when the electric impedance of the body of the subject is measured by applying a multi-frequency probe current to the body of the subject, the subject is measured based on the obtained electric impedance for each frequency. Is calculated, the critical frequency is calculated based on the obtained impedance trajectory. In the configuration according to the second, fifth or eighth aspect, the amount of water removal to be set in artificial dialysis is estimated based on the obtained critical frequency. Therefore, according to the configuration of the present invention, an accurate critical frequency can be calculated. Claim 2
According to the configuration described in 5 or 8, it can be used as a standard for determining whether the water removal is performed mainly on the extracellular solution or the extracellular solution, and how much the removal amount should be set.

[0017]

Embodiments of the present invention will be described below with reference to the drawings. The description will be specifically made using an embodiment. FIG. 1 is a block diagram showing an electric configuration of a body composition estimating apparatus according to one embodiment of the present invention, and FIG.
FIG. 3 is a schematic diagram schematically showing a use state of the same device, FIG. 3 is an electrical equivalent circuit diagram of cells in tissue, FIG. 4 is an electrical equivalent circuit diagram of cells in tissue at infinite frequency, and FIG. FIG. 6 is an explanatory diagram for explaining a method of deriving a body composition estimation formula for estimating a water removal amount uf, FIG. 6 is a flowchart illustrating an operation processing procedure of the device, and FIG. 7 is a display example of a display device in the device. FIG. 8 is a timing chart for explaining the same operation, and FIG. 9 is a diagram showing another display example of the display device in the same device. The body composition estimating device 4 of this example relates to a device that measures the body water distribution (extracellular fluid volume, intracellular fluid volume, body fluid volume), lean mass, critical frequency, and the like of a subject, and displays the measurement result. As shown in FIG. 1 and FIG.
A signal output circuit 5 for flowing a multi-frequency current Ib as a measurement signal, a current detection circuit 6 for detecting a multi-frequency current Ib flowing through the body E of the subject, and a voltage Vp between the limbs of the subject. A voltage detection circuit 7, a keyboard 8 as an input device, a display 9 as an output device, a CPU (central processing unit) 10 for controlling various parts of the device and performing various arithmetic processes, and a processing program for the CPU 10. A ROM 11 for storing, a data area for temporarily storing various data and a RAM 12 for setting a work area of the CPU 10, and four RAMs that are conductively attached to the skin surface of the subject's back Ha or foot back Le during measurement. It is roughly composed of surface electrodes Hp, Hc, Lp, Lc.

First, the keyboard 8 includes numeric keys and function keys for inputting the height, weight, measurement time, and the like of the subject.
It is configured to include a mode selection key for selecting one of the body moisture distribution measurement mode and the body fat measurement mode, and a start / end switch for an operator (or a subject) to instruct measurement start / measurement end and the like. . Operation data and height / weight data supplied from the keyboard 8 are converted into key codes by a key code generation circuit (not shown) and supplied to the CPU 10. The CPU 10 temporarily stores the code-inputted various operation signals and height / weight data in the data area of the RAM 12. In this example, in the body fat measurement mode, the entire measurement period Tf and the number of sweeps N of the measurement signal Ia described later are input. In the body water distribution measurement mode, the total measurement time Tw, the measurement interval t, and the number of sweeps N are input, and the total measurement time Tw is, for example, considering a time sufficient to monitor the artificial dialysis, 4.5 hours, 5.5 hours, 5.5 hours, 6 hours, 6.5 hours, and 7 hours, and the measurement interval t can be arbitrarily selected from 10 minutes, 20 minutes, and 30 minutes. It has become. This allows
During the entire measurement time Tw, the temporal change of the body fluid volume TBW of the subject is measured. As described above, the operator may be allowed to freely set the time Tw, t using the keyboard 8 instead of selecting from several given times.

The signal output circuit 5 comprises a PIO (parallel interface) 51, a measurement signal generator 52 and an output buffer 53. Measurement signal generator 52
Is the CPU 10 via the PIO 51 at a predetermined sweep cycle.
When the signal generation instruction signal SG is supplied from the
For example, in the range of 1 kHz to 400 kHz and 15 kHz
Measurement signal (current) Ia that changes stepwise at a frequency interval of Hz
Are repeatedly generated over a predetermined number of sweeps N and input to the output buffer 53. The output buffer 53 sends the input measurement signal Ia to the surface electrode Hc as a multi-frequency current Ib while keeping the input measurement signal Ia in a constant current state. The surface electrode Hc is conductively affixed to the back Ha of the subject during measurement, so that a multi-frequency current Ib in the range of 100 to 800 μA flows through the body E of the subject. In the body moisture distribution measurement mode,
The supply cycle of the signal generation instruction signal SG matches the measurement interval t set by the operator using the keyboard 8.

The current detection circuit 6 includes an I / V converter (current / voltage converter) 61 and a BPF (bandpass filter).
62, an A / D converter 63 and a sampling memory 64. The I / V converter 61 flows between the body electrode Ec of the subject, that is, between the surface electrode Hc affixed to the back Ha of the subject (FIG. 2) and the surface electrode Lc affixed to the instep Le. The multi-frequency current Ib is detected and converted into a voltage Vb, and the voltage Vb obtained by the conversion is
Supply to F62. The BPF 62 receives the input voltage Vb
Of these, the voltage is supplied to the A / D converter 63 only through a voltage signal in a band of approximately 1 kHz to 400 kHz. The A / D converter 63 converts the analog input voltage Vb to a digital voltage signal Vb according to a digital conversion instruction issued by the CPU 10.
After the conversion, the digitized voltage signal Vb is used as the current data Vb and the measurement signal Ia
Is stored in the sampling memory 64 for each frequency of. Further, the sampling memory 64 is constituted by an SRAM, and outputs a digital voltage signal Vb temporarily stored for each frequency of the measurement signal Ia to the CPU 10 in response to a request from the CPU 10.
Send to 10.

The voltage detection circuit 7 includes a differential amplifier 71, a BPF (bandpass filter) 72, an A / D converter 73, and a sampling memory 74. The differential amplifier 71 includes a body electrode Ep of the subject, that is, a surface electrode Hp attached to the back portion Ha of the subject and a foot portion Le.
(Potential difference) between the surface electrode Lp and the surface electrode Lp
Is detected. The BPF 72 supplies the A / D converter 73 only through a voltage signal in a band of approximately 1 kHz to 400 kHz in the input voltage Vp. A / D converter 7
3 converts an analog input voltage Vp into a digital voltage signal Vp in accordance with a digital conversion instruction issued by the CPU 10.
After that, the digitized voltage signal Vp is stored as voltage data Vp in the sampling memory 74 for each sampling cycle and each frequency of the measurement signal Ia. Also,
The sampling memory 74 is composed of an SRAM, and sends a digital voltage signal Vp temporarily stored for each frequency of the measurement signal Ia to the CPU 10 in response to a request from the CPU 10. The CPU 10 has two A / D converters 6
3 and 73 are instructed to perform digital conversion at the same timing.

The ROM 11 includes, as processing programs for the CPU 10, in addition to the main program, for example, a bioelectrical impedance calculating subprogram, an impedance locus calculating subprogram, a frequency 0 impedance determining subprogram, a frequency infinite impedance determining subprogram, and a critical Frequency calculation subprogram, water removal estimation subprogram, intracellular fluid resistance calculation subprogram, lean mass estimation subprogram, body fat weight estimation subprogram, body fat percentage estimation subprogram, extracellular fluid volume estimation subprogram, intracellular It stores a fluid volume estimation subprogram, a body fluid volume estimation subprogram, a body fluid volume-fat free weight ratio calculation subprogram, a body fluid volume deviation calculation subprogram, and the like. The ROM 11 also stores numerical data obtained by dividing the body fluid volume TBWS in a normal state of the body of a normal healthy person, which has been statistically processed in advance, by the lean body mass LBMS.
It is preset and registered as the lean mass ratio (TBWS / LBMS). Various programs are stored in the ROM 11
10 to control the operation of the CPU 10. The recording medium for recording these subprograms is R
Not limited to a semiconductor memory such as the OM11, a magnetic disk such as a floppy disk (FD) or a hard disk (HD), or an optical disk such as a CD-ROM may be recorded.

Here, the above-described bioelectric impedance calculation subprogram causes the CPU 10 to sequentially read out current data and voltage data for each frequency stored in the sampling memories 64 and 74, and to read the biological data of the subject for each frequency. Calculate the electrical impedance. As described in the “Prior Art” section, the cell membranes 2, 2,... Can be regarded as large-capacity capacitors. Therefore, when the externally applied current is low in frequency, the solid lines A, As shown by A,..., Only the extracellular fluid 3 flows. However, as the frequency increases, the current flowing through the cell membranes 2, 2, ... increases, and when the frequency becomes very high,
As shown by broken lines B, B,... In FIG.

In the impedance locus calculation subprogram, the CPU 10 instructs the CPU 10 to start from the frequency 0 based on the bioelectric impedance of the subject at each frequency obtained by the operation of the bioelectric impedance calculation subprogram in accordance with the least squares calculation method. The processing procedure for calculating the impedance locus up to the frequency infinity is written. In the “Prior Art” section, cells in human body tissue are represented by a simple electrical equivalent circuit (FIG. 11). However, in actual human body tissue, cells of various sizes are irregularly arranged. Therefore, the impedance locus of the actual human body is an arc whose center is higher than the real axis as shown by a solid line D in FIG. 9, and the electrical equivalent circuit has a time constant τ = Cmk / It is represented by a distributed constant circuit in which Yik is distributed. In the figure, 1 / Ye is the extracellular fluid resistance, 1
/ Yik indicates the intracellular fluid resistance of each cell, and Cmk indicates the cell membrane capacity of each cell.

The impedance determination subprogram at the frequency 0 and the impedance determination subprogram at the infinite frequency are respectively provided to the CPU 10 based on the impedance trajectory obtained by operating the impedance trajectory calculation subprogram. A procedure for determining the subject's bioelectric impedance at infinity is written.

The critical frequency calculation subprogram includes CP
In U10, a procedure for calculating the critical frequency fc based on the impedance locus obtained by running the impedance locus calculation subprogram is written. The critical frequency fC can be obtained from the frequency of the data before and after exceeding the peak of the arc of the impedance locus (FIG. 9), and from the ratio of each data apart from the peak. The water removal amount estimation subprogram includes an optimum water removal amount uf to be set in artificial dialysis based on the critical frequency fc obtained by operation of the critical frequency estimation subprogram.
The estimation formula (1) for estimating is described. Here, the equation (1) is a regression equation of the water removal amount uf obtained as a result of conducting a sample survey in advance for a large number of subjects, and the constants α and β are f = water removal amount uf actually measured after completion of the artificial dialysis.
It was obtained by regression analysis with one explanatory variable of C. The correlation coefficient was 0.96, and a high correlation was confirmed. The regression line represented by the equation (1) is a straight line as shown in FIG.

[0027]

Uf = -αfC + β (1) uf: Amount of water removal of subject by artificial dialysis [l] fC: Critical frequency of subject [kHz] α, β: Constant

The subcellular fluid resistance calculation subprogram includes C
The PU 10 describes a calculation formula (2) for calculating the intracellular fluid resistance 1 / Yi based on both impedances obtained by the operation of the frequency 0-time impedance determination subprogram and the frequency infinity-time impedance determination subprogram. I have. At a frequency of 0 Hz, the measured bioelectrical impedance 1 / Y (0) is equal to the extracellular fluid resistance 1 / Y
e, the impedance 1 / Y obtained in the frequency 0 hour impedance determination subprogram.
(0) becomes the extracellular fluid resistance 1 / Ye to be determined (see equation (3)). At infinite frequency, as shown in FIG. 9, the cell membrane loses its capacitive capacity, and the measured bioelectrical impedance 1 / Y (Ｙ) becomes the intracellular fluid resistance 1 / Yi.
And the extracellular fluid resistance 1 / Ye (FIG. 4). Therefore, the intracellular fluid resistance 1 / Yi is accurately calculated from the bioelectrical impedances 1 / Y (0) and 1 / Y (∞) at the frequency of 0 and at the infinity.

[0029]

## EQU2 ## Yi = Y (∞) -Y (0) (2)

[0030]

## EQU3 ## Ye = Y (0) (3)

The lean mass estimation subprogram includes CP
In U10, the extracellular fluid resistance 1 / Ye obtained by the frequency 0 hour impedance determination subprogram and the intracellular fluid resistance 1 / Y obtained by the intracellular fluid resistance calculation subprogram
i, the subject's lean mass L based on the subject's height data H and weight data W input via the keyboard 8
The estimation formula (4) for estimating the BM is described. Here, Equation (4) is a multiple regression equation of lean body mass LBM obtained as a result of conducting a sample survey in advance on a large number of subjects, and constants a ₁ , b ₁ , c ₁ , and d ₁ are represented by DXA. The measured lean mass LBM was determined by performing multiple regression analysis on three explanatory variables of W, H ² Ye, and H ² Yi. By adding the weight W to the explanatory variable, the correlation coefficient with the data measured by DXA increases to 0.96.

[0032]

LBM = a ₁ W + b ₁ H ² Ye + c ₁ H ² Yi + d ₁ (4) LBM: lean body mass of subject [kg] W: subject weight [kg] H: subject height [cm] Ye: reciprocal of extracellular fluid resistance [1 / Ω] Yi: reciprocal of intracellular fluid resistance [1 / Ω] a ₁ , b ₁ , c ₁ , d ₁ : constant

The above body fat weight estimation subprogram is C
The PU 10 is caused to calculate the subject's body fat weight FAT by subtracting the lean body mass LBM from the subject's weight W. The body fat percentage estimation subprogram includes CPU1
0 to calculate the subject's body fat percentage% FAT based on the lean body mass LBM obtained by the lean body mass estimation subprogram and the body fat mass FAT obtained by the body fat mass estimation subprogram. The procedure (Equation (5)) is described.

[0034]

% FAT = 100FAT / (FAT + LBM) (5)

The extracellular fluid volume estimation subprogram includes CP
In U10, an estimation formula (6) for estimating the extracellular fluid volume Ve of the subject based on the extracellular fluid resistance 1 / Ye and the height data H of the subject is described. Here, equation (6)
Is a regression equation of the extracellular fluid volume Ve obtained as a result of conducting a sample survey in advance for a large number of subjects, and the constant b ₂ is a regression analysis of the extracellular fluid volume Ve with one explanatory variable of H ² Ye. That is what was sought.

[0036]

[6] ^{_{Ve = b 2 H 2 Ye ...}} ... (6) Ve: extracellular fluid volume of the subject [kg] H: height of the subject [cm] Ye: reciprocal of extracellular fluid resistance [1 / Ω] b ₂ :constant

The subcellular fluid volume estimation subprogram includes CP
In U10, an estimation formula (7) for estimating the intracellular fluid volume Vi of the subject based on the intracellular fluid resistance 1 / Yi and the height data H of the subject is described. Here, equation (7)
Is a regression equation of the intracellular fluid volume Vi obtained as a result of conducting a sample survey in advance on a large number of subjects, and the constant c ₂ is a regression analysis of the intracellular fluid volume Vi with one explanatory variable of H ² Yi. That is what was sought.

[0038]

Vi = c ₂ H ² Yi (7) Vi: Intracellular fluid volume of subject [kg] H: Height of subject [cm] Yi: Reciprocal of intracellular fluid resistance [1 / Ω] c ₂ :constant

The body fluid volume estimation subprogram includes a CPU 1
0 describes an estimation formula (8) for estimating the body fluid volume TBW of the subject based on the extracellular fluid resistance 1 / Ye, the intracellular fluid resistance 1 / Yi, the height data H and the weight data W of the subject. ing. Here, equation (8) is a multiple regression equation of the body fluid volume TBW obtained as a result of conducting a sample survey on a large number of subjects in advance, and constants a ₃ , b ₃ , c ₃ , and d ₃ are measured by DXA. The obtained body fluid volume TBW is obtained by performing multiple regression analysis on three explanatory variables W, H ² Ye, and H ² Yi.

[0040]

TBW = a ₃ W + b ₃ H ² Ye + c ₃ H ² Yi + d ₃ (8) TBW: body fluid volume of subject [kg] W: weight of subject [kg] H: height of subject [cm] Ye: Reciprocal of extracellular fluid resistance [1 / Ω] Yi: Reciprocal of intracellular fluid resistance [1 / Ω] a ₃ , b ₃ , c ₃ , d ₃ : constant

The body fluid amount-fat free weight ratio calculation subprogram describes a procedure for causing the CPU 10 to calculate the body fluid amount-fat free weight ratio (TBW / LBM) of the subject. Further, the body fluid volume deviation calculation subprograms, body fluid volume of the subject - lean weight ratio (TBW / LBM) to normal body fluid volume - fat weight (TBW _s / LBM _s) and fluid volume is the difference - removal Body fluid volume deviation ΔTB given by multiplying fat-to-weight ratio deviation Δ (TBW / LBM) by lean mass LBM
A procedure for calculating W (formula (9)) is described.

[0042]

ΔTBW = LBM ｛(TBW / LBM) − (TBWs / LBMs)｝ (9)

The data area of the RAM 12 includes, for example, a bioelectric impedance storage area for storing the bioelectric impedance of the subject obtained by the bioelectric impedance calculation subprogram for each frequency, and a keyboard 8.
A height and weight data storage area for storing the height and weight data of the subject input via the, and a body fat storage area for storing numerical values such as the body fat percentage obtained by the body fat percentage estimation subprogram are set. Is done.

The CPU 10 controls the various processing programs stored in the ROM 11 and uses the RAM 12
Subject's lean mass LBM, fat weight FAT, body fluid volume T
Processes for estimating BW and the like are sequentially executed. The display 9 includes, for example, a liquid crystal display panel capable of color display, and includes input data from the keyboard 8, calculation results of the CPU 10,
For example, a trend graph relating to a body fluid amount-fat free weight ratio, a body fluid amount deviation, a body fat percentage, an impedance locus (FIG. 9)
(A), (b)), extracellular fluid resistance, intracellular fluid resistance,
The height and weight of the subject are displayed.

Next, the operation of this example will be described. First, prior to the measurement, as shown in FIG. 2, the two surface electrodes Hc and Hp were electrically connected to the back part Ha of the subject, and the two surface electrodes Lp and Lc were connected to the instep part Le on the same side of the subject. Paste via cream (at this time, surface electrode H
c, Lc are attached to a portion farther from the center of the human body than the surface electrodes Hp, Lp). Body composition estimation device 4 having the above configuration
Is used, for example, as a monitor during dialysis,
The operator (or the subject himself / herself) operates the keyboard 8 of the body composition estimating device 4, operates the mode setting key, sets the body moisture distribution measurement mode, and further inputs the height H and weight W of the subject. At the same time, the total measurement time Tw from the start of measurement to the end of measurement, the measurement interval t (FIG. 8), the number of sweeps N
Set. In this example, it is assumed that the total measurement time Tw is selected to be 7 hours in consideration of a time sufficient to monitor dialysis, and that the measurement interval t is selected to be 30 minutes.
Data such as height H and weight W input from the keyboard 8 and set values are stored in the RAM 12.

Next, when the operator (or the subject himself / herself) turns on the start / end switch of the keyboard 8 in time with the start of dialysis, the CPU 10 operates according to the processing flow shown in FIG. To start. First, in step SP10, the CPU 10 supplies a signal generation instruction signal SG to the measurement signal generator 52 of the signal output circuit 5. When receiving the signal generation instruction signal SG from the CPU 10, the measurement signal generator 52 starts driving, and the frequency is 1 kHz to 400 at a predetermined sweep cycle during the entire measurement time.
A measurement signal Ia that changes stepwise in the range of kHz and at a frequency interval of 15 kHz is repeatedly generated and input to the output buffer 53. The output buffer 53 sends the input measurement signal Ia to the surface electrode Hc as a multi-frequency current Ib while maintaining the input measurement signal Ia in a constant current state (a constant value in a range of 100 to 800 μA). Thereby, the multifrequency current Ib of the constant current flows through the body E of the subject from the surface electrode Hc, and the measurement is started.

When the multi-frequency current Ib is supplied to the body E of the subject, the multi-frequency current Ib flowing between the limbs to which the surface electrodes Hc and Lc are attached is generated in the I / V converter 61 of the current detection circuit 6. After being detected and converted into an analog voltage signal Vb, it is supplied to the BPF 62. BP
In F62, 1 kHz is selected from the input voltage signal Vb.
Only the voltage signal components in the band of 400 kHz are allowed to pass and supplied to the A / D converter 63. A / D converter 6
In 3, the supplied analog voltage signal Vb is converted into a digital voltage signal Vb, and as current data Vb,
It is stored in the sampling memory 64 for each predetermined sampling period and for each frequency of the measurement signal Ia. In the sampling memory 64, the stored digital voltage signal Vb is
The data is sent to the CPU 10 in response to the request from the PU 10. On the other hand, in the differential amplifier 71 of the voltage detection circuit 7, the voltage Vp generated between the limbs to which the surface electrodes Hp and Lp are attached
Is detected and supplied to the BPF 72. In the BPF 72, a frequency of 1 kHz to 400
Only the voltage signal component in the kHz band is allowed to pass, and A
/ D converter 73. In the A / D converter 73,
The supplied analog voltage signal Vp is converted into a digital voltage signal Vp, and is stored as voltage data Vp in the sampling memory 74 for each predetermined sampling period and for each frequency of the measurement signal Ia. Sampling memory 74
Then, the stored digital voltage signal Vp is
Is sent to the CPU 10 in response to the request. CPU10
Is repeated until the number of sweeps of the probe current Ia reaches the specified number of sweeps N.

When the number of sweeps reaches the specified number N, the CPU 10 performs control to stop the measurement, and then proceeds to step SP11. The current data and the voltage data for each frequency stored in the sampling memories 64 and 74 are sequentially read, and the bioelectric impedance (average value of N times of the number of sweeps) of the subject for each frequency is calculated. The calculation of the bioelectric impedance includes the calculation of its components (resistance and reactance). Next, the CPU 10 activates the impedance locus calculation subprogram, and based on the subject's bioelectric impedance and its components (resistance and reactance) for each frequency obtained by the bioelectric impedance calculation subprogram, uses the least squares method. Is calculated from the frequency 0 to the frequency infinity according to the curve fitting method using The impedance locus calculated in this way is shown in FIG.
As shown in (b), the center is an arc that is higher than the real axis.

Next, under the control of the impedance determination subprogram at the time of frequency 0 and the impedance determination subprogram at the time of infinity at frequency 0, the CPU 10 executes the operation at the frequency 0 and the frequency 0, respectively, based on the impedance trajectories obtained by the impedance trajectory calculation subprogram. The bioelectric impedance of the subject at infinity is obtained. In other words, the points at which the arcs of the impedance locus intersect the X axis in the figure are the bioelectric impedances at the frequency of 0 Hz and infinity, respectively. Here, the bioelectric impedance at the frequency of 0 Hz is the required extracellular fluid resistance. next,
The CPU 10 obtains the critical frequency fc based on the impedance locus obtained by operating the impedance locus calculation subprogram according to the control of the critical frequency calculation subprogram. That is, the impedance locus (FIG. 1)
The frequency of the data before and after exceeding the vertex of the arc of 0) is obtained, and the frequency is obtained from the ratio of each data away from the vertex. next,
The CPU 10 calculates the intracellular fluid resistance based on both impedances obtained by the impedance determination subprogram at frequency 0 and the impedance determination subprogram at infinity frequency according to the intracellular fluid resistance calculation subprogram.

(A) At Body Moisture Distribution Measurement Mode Next, the process proceeds to step SP12, where the CPU 10 looks at a mode setting flag (not shown) and determines whether the current mode is the body moisture distribution measurement mode or the body fat measurement mode. Find out if there is. At this time, since the body moisture distribution measurement mode is set by the operator (or the subject), the CPU 10
Proceeds to step SP13, and first executes a process of estimating the water removal amount uf to be set by the subject by using the equation (1) under the control of the water removal amount estimation subprogram. next,
The CPU 10 executes a process of estimating the subject's extracellular fluid volume Ve by using the equation (6) under the control of the extracellular fluid volume estimation subprogram, and then executes the formula by controlling the intracellular fluid volume estimation subprogram. Using (7), a process for estimating the intracellular fluid volume Vi of the subject is executed. Further, the CPU 10
Is calculated by the control of the body fluid volume estimation subprogram,
Is used to estimate the body fluid volume TBW of the subject. Next, the CPU 10 estimates the lean body mass LBM of the subject by using the equation (4) under the control of the lean body mass estimation subprogram, and thereafter, under the control of the body fluid amount-lean mass ratio calculation subprogram. Then, the body fluid-to-fat weight ratio (TBW / LBM) is calculated, and finally, the current body fluid deviation ΔTBW of the subject is calculated by using the equation (9) under the control of the body fluid deviation calculating subprogram.

When the above series of calculation processing is completed, the CP
U10 is the calculated water removal volume uf, extracellular fluid volume Ve, intracellular fluid volume Vi, body fluid volume TBW, and lean mass LB of the subject.
M, body fluid amount-lean weight ratio (TBW / LBM), body fluid amount deviation ΔTBW, etc.
M12 and the process proceeds to step SP14, and as shown in FIG. 7, the trend graph (the elapsed time from the start of dialysis is set on the horizontal axis, and the body fluid amount-fat free weight ratio (TBW / LBM) is plotted on a line graph with the vertical axis being LBM), and the value of the body fluid-to-fat-free weight ratio (TBW / LBM) is plotted, and the water removal amount uf is displayed as a recommended water removal amount to be used as a guide. The fluid volume Ve, intracellular fluid volume Vi, body fluid volume deviation ΔTBW, body fluid volume TBW, and lean mass LBM are displayed on the screen as current data.

Thereafter, the process proceeds to step SP15, where the CPU
Step 10 determines whether the total measurement time Tw (FIG. 8) has elapsed. In this determination, if it is determined that the total measurement time Tw (7 hours in this example) has elapsed, the subsequent measurement processing is terminated. However, since the first measurement has just been completed, the total measurement time has been reached. It is determined that Tw has not yet elapsed, the process proceeds to step SP16, and waits for the elapse of time t (FIG. 6) corresponding to the measurement interval. During this waiting time, the trend graph screen of the display 9 is displayed. Then, when a time t (30 minutes in this example) corresponding to the measurement interval has elapsed, the process returns to step SP10, and the second measurement is started. Then, the above processing is performed,
This is repeated until the entire measurement time Tw has elapsed, that is, until the end of the dialysis.

(B) At the time of body fat measurement mode On the other hand, when the subject is lean body mass LBM, body fat mass FAT,
If you want to measure body fat percentage% FAT,
Prior to the measurement, the operator (or the subject himself / herself) operates the keyboard 8 of the body composition estimation device 4, operates the mode setting key to set the body fat measurement mode, and furthermore, the height H and weight W of the subject. And the total measurement time T
f and the number of sweeps N are set. Next, when the start / end switch of the keyboard 8 is pressed, the CPU 1
0 executes the above-described measurement calculation processing (step SP10 and step SP11). Then, step SP1
Proceeding to 2, the CPU 10 checks the mode setting flag and checks whether the current mode is the body moisture distribution measurement mode or the body fat measurement mode. This time, since the body fat measurement mode has been selected, the process proceeds to step SP17, and the CPU
10 is controlled by the lean mass estimation subprogram.
Using the formula (4), the lean mass LBM of the subject is estimated. Next, the CPU 10 estimates the fat weight FAT of the subject under the control of the body fat weight estimation subprogram, and then uses the equation (5) to control the body fat percentage FAT under the control of the body fat percentage estimation subprogram. Is calculated.

When the above series of calculation processing is completed, the CP
U10 stores the subject's lean body mass LBM, the body fat mass FAT, the body fat percentage% FAT, and the like in the RAM 12, and in step SP18, as shown in FIG. Fat weight FAT,
The display unit 9 displays the body fat percentage% FAT, the impedance locus, the extracellular fluid resistance, the height and weight of the subject, and the like. Then, the series of processing ends.

As described above, according to the above-described configuration, the extracellular fluid resistance 1 / Ye and the intracellular fluid resistance 1 / Yi can be reliably separated from each other, and contain no cell membrane capacitance component. In addition to the height H of the subject, the weight W is also considered, so that more accurate estimated values can be obtained for the lean body mass LBM, the body fat mass FAT, the body fluid volume TBW, and the like. For example, in the lean body mass LBM, the correlation coefficient with the data measured by DXA increases to 0.96. The impedance trajectory calculation subprogram makes use of the least-squares method to determine the impedance trajectory. From the obtained trajectory, the bioelectrical impedance at the frequency of 0 and infinity is obtained. Since the extracellular fluid resistance and the intracellular fluid resistance are calculated based on the impedance, it is possible to avoid the influence of stray capacitance and external noise when high frequency is applied, and to avoid direct application of direct current to the human body. Therefore, measurement accuracy is improved. Further, in the body water distribution measurement mode, the current value of the body fluid amount-fat free weight ratio (TBW / LBM) is trend-displayed on the display 9 and the water removal amount uf is displayed as a recommended water removal amount to be used as a guide. And the subject's current extracellular fluid volume Ve,
Intracellular fluid volume Vi, fluid volume deviation ΔTBW, fluid volume TBW,
Since the lean body mass LBM is displayed, it is used as a guide, for example, in artificial dialysis, whether water is removed mainly from the extracellular solution or extracellular solution, and how much the amount of water removal should be set. it can. In this case, it is not necessary to correct the influence of the difference in the physique of the subject.

The embodiments of the present invention have been described in detail with reference to the drawings. However, the specific configuration is not limited to the embodiments, and the design may be changed without departing from the scope of the present invention. Even if there is, it is included in the present invention. For example, in the above-described embodiment, four surface electrodes Hc, Hp, Lc, Lp
Of these, two surface electrodes Hc and Hp are attached to the back part Ha of the subject E, and the remaining two surface electrodes Lc and Lp are attached to the foot part Le of the subject E. However, the present invention is not limited to this. ,
For example, all four may be attached to one leg.
The frequency range of the measurement signal (current) Ia is 1 kHz.
It is not limited to 400 kHz. Similarly, the number of frequencies is arbitrary as long as it is plural. Also, instead of calculating the bioelectrical impedance, a bioelectrical admittance may be calculated, and accordingly, an admittance locus may be calculated instead of calculating an impedance locus. Further, in the above-described embodiment, the bioelectrical impedance at the time of the frequency of 0 and at the time of the infinity is obtained by using the curve fitting method by the least square method. However, the present invention is not limited to this. Can be avoided by other means, for example, 2
A measurement signal having a frequency (low frequency of 5 kHz or less and a high frequency of 200 kHz or more) is generated and applied to the subject, and the bioelectric impedance of the body of the subject at the low frequency is regarded as the bioelectric impedance at the frequency of 0. The bioelectric impedance of the body at a high frequency may be regarded as the bioelectric impedance at an infinite frequency.
Further, the trend graph of the display 9 may be a bar graph instead of the line graph. Further, the output device is not limited to the display device, and a printer may be used.

[0057]

As described above, according to the configuration of the present invention, an accurate critical frequency can be calculated for each individual. According to the configuration of claim 2, 5 or 8, since the estimation of the amount of water removal in artificial dialysis to be a guide is performed, whether the water removal is performed mainly on the extracellular fluid or extracellular fluid, It can be used as a guide for how much water removal should be set.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an electrical configuration of a body composition estimating apparatus according to an embodiment of the present invention.

FIG. 2 is a schematic diagram schematically showing a use state of the body composition estimation device.

FIG. 3 is an electrical equivalent circuit diagram of cells in a tissue.

FIG. 4 is an electrical equivalent circuit diagram of cells in a tissue at an infinite frequency.

FIG. 5 is an explanatory diagram for explaining a method of deriving a body composition estimation formula for estimating a water removal amount.

FIG. 6 is a flowchart showing an operation processing procedure of the body composition estimation device.

FIG. 7 is a diagram showing a display example of a display device in the body composition estimation device.

FIG. 8 is a timing chart for explaining the operation of the body composition estimation device.

FIG. 9 is a diagram showing another display example of the display device in the body composition estimation device.

FIG. 10 is a diagram showing an impedance locus of a human body.

FIG. 11 is a schematic diagram schematically showing cells in a tissue of a human body.

FIG. 12 is an electrical equivalent circuit diagram of cells in a tissue.

[Explanation of symbols]

4 Body Composition Estimation Device 5 Signal Output Circuit (Part of Bioelectric Impedance Calculation Means) 6 Current Detection Circuit (Part of Bioelectric Impedance Calculation Means) 7 Voltage Detection Circuit (Part of Bioelectric Impedance Calculation Means) 8 Keyboard 10 CPU (bioelectric impedance calculating means) 11 ROM 12 RAM 52 measurement signal generator 53 output buffer 61 I / V converter 62, 72 BPF 63, 73 A / D converter 64, 74 sampling memory 71 differential amplifier Hc, Hp , Lc, Lp Surface electrode E Subject's body Ha Subject's back part Le Subject's instep part Ia Measurement signal Ib Multi-frequency current (multi-frequency probe current) Vp Voltage between subject's limbs

Claims (9)

[Claims] 1. A multi-frequency probe current is applied to the body of a subject to measure the electrical impedance of the body of the subject, and based on the electrical impedance for each frequency obtained by the measurement, the body impedance of the subject is measured. Calculating an impedance locus, and calculating a critical frequency which is a frequency at which both the reactance and the phase angle of the electric impedance are maximized, based on the impedance locus obtained by the calculation. . 2. The body composition estimation method according to claim 1, wherein a water removal amount to be set in artificial dialysis is estimated based on the critical frequency. 3. Using a body composition estimation formula given as having the amount of water removal negatively correlated with the critical frequency,
The body composition estimation method according to claim 2, wherein the water removal amount is estimated. 4. A bioelectrical impedance measuring means for generating a multi-frequency probe current, applying the generated probe current of each frequency to a subject's body to measure an electrical impedance of the subject's body, Impedance trajectory calculation means for calculating an impedance trajectory of the body of the subject based on the electric impedance for each frequency measured by the measurement means, and based on the impedance trajectory calculated by the impedance trajectory calculation means, A body frequency estimating device comprising: a critical frequency calculating means for calculating a critical frequency which is a frequency at which both the reactance and the phase angle of the electrical impedance are maximized. 5. The body composition estimating apparatus according to claim 4, further comprising a water removal amount estimating means for estimating a water removal amount to be set in artificial dialysis based on the critical frequency. 6. The water removal amount estimating means estimates the water removal amount by using a body composition estimation formula given as having a negative correlation with the critical frequency. 6. The body composition estimation device according to 5. 7. A computer-readable recording medium recording a body composition estimation program for estimating a body water distribution and a body fat state of a subject's body by a computer, wherein the body composition estimation program is stored in a computer. Based on the electric impedance for each frequency measured by applying a multi-frequency probe current to the body of the subject, the least-squares method is used to calculate the impedance locus, and the calculated impedance is calculated. A computer-readable recording medium recording a body composition estimation program, wherein a critical frequency which is a frequency at which both the reactance and the phase angle of the electrical impedance are maximized is calculated from a trajectory. 8. The body composition estimating program according to claim 7, wherein the body composition estimating program causes a computer to estimate a water removal amount to be set in artificial dialysis based on the critical frequency. Computer readable recording medium. 9. The body composition estimating program causes a computer to estimate the water removal amount using a body composition estimation formula given as having the water removal amount in a negative correlation with the critical frequency. A computer-readable recording medium on which the body composition estimation program according to claim 8 is recorded.