A method for assessing body composition data of human limbs based on bioimpedance vector analysis technology

Abstract

A method for evaluating body composition data of human limbs based on bioimpedance vector analysis technology is provided. [Solution] A method for evaluating body composition data of human limbs based on bioimpedance vector analysis technology includes the following steps: Step (a) provides a group of R-Xc diagrams of multiple human limbs. Each R-Xc diagram is composed of an X-axis, a Y-axis, a first vector, a second vector, and multiple tolerance intervals. The X-axis is the standard resistance / first geometric parameter of Z-transformation of each human limb of the group. The Y-axis is the standard reactance / first geometric parameter of Z-transformation of each human limb of the group. Step (b) separately corresponds the resistance / second geometric parameter and reactance / second geometric parameter of the measured limb obtained by the body composition analyzer to coordinates in the R-Xc diagram of the human limb, thereby allowing the body composition of the measured limb to be compared and evaluated with indexes representing the physiological characteristics of the group.

Description

[Technical Field]

[0001] The present invention relates to a bioimpedance vector analysis technique, and more particularly to a method for evaluating body composition data of human limbs based on the bioimpedance vector analysis technique. [Background technology]

[0002] Bioelectrical Impedance Vector Analysis (BIVA) is a technique for assessing the body composition by observing the distribution of intracellular fluid (ICF) and extracellular fluid (ECF) within the human body through the application of a weak electric current.

[0003] The human body's body composition includes muscle, fat, and bones. The most common method for evaluating body composition data is to display the evaluation data in a bar graph. As shown in Figure 1, when evaluating skeletal muscle mass, muscle mass is quantified using statistics and the quantified muscle mass is displayed in a first bar graph. The first bar graph is then used as an evaluation index to classify the subject into low, normal, and high muscle mass. The results of measuring the subject's skeletal muscle mass based on BIVA are then quantified and displayed in a second bar graph. The subject's muscle mass is then evaluated by comparing the second bar graph with the first bar graph to determine whether it is low, high, or normal.

[0004] However, the above-mentioned evaluation method cannot evaluate the expression index of the skeletal muscle mass of the measurement subject in comparison with the physiological characteristics of a group (e.g., athletes, elderly people, people in the same geographical location, people with the same physiological characteristics, or a specific age group, etc.). In other words, there is room for improvement in the conventional method for evaluating body composition data of human limbs. Summary of the Invention [Problem to be solved by the invention]

[0005] The main objective of the present invention is to provide a method for evaluating body composition data of a human body part based on bioelectrical impedance vector analysis technology, which can evaluate the body composition of a target body part by comparing it with an index representing a group of physiological characteristics, thereby improving industrial applicability. [Means for solving the problem]

[0006] To solve the above-mentioned problems, a method for evaluating body composition data of a human limb based on bioimpedance vector analysis technology includes the following steps:

[0007] Step (a) provides a plurality of R-Xc diagrams of the group of body parts by the calculation unit. Each R-Xc diagram comprises an X-axis, a Y-axis, a first vector, a second vector, and a plurality of tolerance intervals. The X-axis is the standard resistance / first geometric parameter (Z(R / G1)) of the Z-transform of each body part of the group. The Y-axis is the standard reactance / first geometric parameter (Z(Xc / G1)) of the Z-transform of each body part of the group. The X-axis and Y-axis are orthogonal, and their intersection is the origin. The X-axis and Y-axis separate the first, second, third, and fourth quadrants. The first, second, third, and fourth quadrants each represent one body composition state. The first and second vectors intersect at right angles through the origin. The plurality of tolerance intervals are expressed in percentage units. The multiple tolerance intervals are distributed circularly from the inside to the outside of the origin, with percentages increasing from the inside to the outside of the origin. The multiple tolerance intervals are distributed across the first, second, third, and fourth quadrants. Step (b) acquires the resistance / second geometric parameter (R / G2) and reactance / second geometric parameter (Xc / G2) of the body part to be measured using a body composition analyzer, separately corresponds the acquired resistance / second geometric parameter and reactance / second geometric parameter of the body part to one coordinate on the R-Xc diagram of the human body part, and simultaneously creates and evaluates body composition data of the body part to be measured based on the location of the coordinate (first, second, third, or fourth quadrant) and the tolerance intervals.

[0008] To summarize the above, compared with the prior art, the method of evaluating body composition data of human limbs based on bioimpedance vector analysis technology according to the present invention can evaluate the body composition of the limbs of the subject to be measured in comparison with the expression index of the physiological characteristics of the group to which it belongs, thereby improving industrial applicability. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a screen shot showing a method for evaluating body composition data according to the prior art. [Figure 2] 1 is a schematic diagram showing steps of the present invention; FIG. [Figure 3] FIG. 2 is a first R-Xc view displayed according to the first embodiment of the present invention. [Figure 4] FIG. 2 is a second R-Xc view displayed according to the first embodiment of the present invention. [Figure 5] FIG. 10 is a third R-Xc view displayed according to the first embodiment of the present invention. [Figure 6] FIG. 10 is a fourth R-Xc diagram displayed according to the first embodiment of the present invention. [Figure 7] FIG. 10 is a fifth R-Xc diagram displayed according to the first embodiment of the present invention. [Figure 8] FIG. 10 is a sixth R-Xc diagram displayed according to the first embodiment of the present invention. [Figure 9] FIG. 10 is a first R-Xc view displayed according to the second embodiment of the present invention. [Figure 10] FIG. 10 is a second R-Xc view displayed according to the second embodiment of the present invention. [Figure 11] FIG. 10 is a third R-Xc diagram displayed according to the second embodiment of the present invention. [Figure 12] FIG. 10 is a fourth R-Xc diagram displayed according to the second embodiment of the present invention. [Figure 13] FIG. 5 is a fifth R-Xc diagram displayed according to the second embodiment of the present invention. [Figure 14] FIG. 10 is a sixth R-Xc diagram displayed according to the second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0010] The technical features of the present invention will be described below with reference to the drawings.

[0011] (First embodiment) 2 to 8, the method 10 for evaluating body composition data of a human limb based on bioimpedance vector analysis technology according to the first embodiment of the present invention uses body composition data corresponding to soft tissue as an example. Soft tissue collectively refers to connective tissues excluding bone tissue, such as skin, subcutaneous fat, muscle, tendon, ligament, fascia, synovial membrane, bursa, joint capsule, peripheral nerve, fibrous tissue, lymphatic tissue, and vascular tissue. When evaluating body tissue data, body composition data corresponding to bone or fat can also be adopted according to actual needs.

[0012] In a first embodiment, a method 10 for assessing body composition data of a human limb based on bioimpedance vector analysis technology includes the following steps.

[0013] Step (a) provides a group of multiple R-Xc diagrams 20 of human body parts by a calculation unit. Each R-Xc diagram 20 is composed of an X-axis 30, a Y-axis 40, a first vector 50, a second vector 60, and multiple tolerance intervals 70. In the tolerance interval 70, the sample mean value x is used as an estimate of the overall mean value u, and the sample standard deviation S is used as an estimate of the overall standard deviation O, thereby estimating individual values ​​within the range, i.e., within the tolerance interval 70. The X-axis 30 is the standard resistance / first geometric parameter (Z(R / G1)) of the Z-transform of the group. The symbol R is resistance. The Y-axis 40 is the standard reactance / first geometric parameter (Z(Xc / G1)) of the Z-transform of the group. The symbol Xc is reactance.

[0014] The first embodiment uses a group of middle-aged and elderly people aged 45 to 65 as an example. Resistance and reactance are then determined by measuring the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and trunk of over 100 middle-aged and elderly people of various occupations, genders, and regions. The determined resistance and reactance are then standardized with the heights (Height, H) of the subjects to determine multiple parameters (R / H1, Xc / H1). In other words, the heights of the subjects are used as the first geometric parameter. Multiple R-Xc diagrams 20 of human limbs are then created by non-dimensionalizing each R / H1 and Xc / H1. When actually implementing the above method, the group is not limited to that of the first embodiment. Depending on actual needs, comparison subjects may include athletes, elderly people, people from the same region and with the same physiological characteristics, or a specific age group.

[0015] The X-axis 30 and the Y-axis 40 are perpendicular to each other, and their intersection is the origin 80. The origin 80 is the intersection point of the average values ​​of R / H and Xc / H. The X-axis 30 and the Y-axis 40 separate a first quadrant 41, a second quadrant 42, a third quadrant 43, and a fourth quadrant 44. The first quadrant 41, the second quadrant 42, the third quadrant 43, and the fourth quadrant 44 each represent a body composition state. The first vector 50 and the second vector 60 intersect perpendicularly through the origin 80. The multiple tolerance intervals 70 are expressed in percentages (%). The multiple tolerance intervals 70 are distributed in a circular pattern from the inside to the outside of the origin 80, with the percentage increasing from the inside to the outside of the origin 80. The multiple tolerance intervals 70 are distributed across the first quadrant 41, the second quadrant 42, the third quadrant 43, and the fourth quadrant 44.

[0016] In the first embodiment, a body composition measuring device is used as the calculation unit. A plurality of human body parts R-Xc diagrams 20 are displayed on the display screen of the body composition measuring device. When actually implementing the above method, the calculation unit may be a computer, tablet, or hardware device with calculation capabilities other than the body composition measuring device. In other words, the calculation unit is not limited to that in the first embodiment.

[0017] In the first embodiment, there are six R-Xc diagrams of human limbs and body parts 20, including a first R-Xc diagram 21 corresponding to the whole body, a second R-Xc diagram 22 corresponding to the right upper limb, a third R-Xc diagram 23 corresponding to the left upper limb, a fourth R-Xc diagram 24 corresponding to the right lower limb, a fifth R-Xc diagram 25 corresponding to the left lower limb, and a sixth R-Xc diagram 26 corresponding to the trunk. When actually implementing the above method, the number, order, or arrangement of the R-Xc diagrams of human limbs and body parts 20 may be changed according to actual needs. That is, the number of R-Xc diagrams of human limbs and body parts 20 and the corresponding human body parts of the first R-Xc diagram 21 to the sixth R-Xc diagram 26 are not limited to those in the first embodiment.

[0018] In the first embodiment, the first quadrant 41 displays a body composition with a relatively low water content. The second quadrant 42 displays a body composition with a relatively high soft tissue content. The third quadrant 43 displays a body composition with a relatively high water content. The fourth quadrant 44 displays a body composition with a relatively low soft tissue content. When actually implementing the above method, if the body composition data of a human body part corresponds to bones or fat, the meanings displayed in the first quadrant 41, second quadrant 42, third quadrant 43, and fourth quadrant 44 will change depending on the body composition data of the human body part evaluated by bioimpedance vector analysis.

[0019] In the first embodiment, the plurality of tolerance intervals 70 are divided into a 50% tolerance interval 71, a 75% tolerance interval 72, and a 90% tolerance interval 73 from the inside to the outside of the origin 80. That is, the percentages of the plurality of tolerance intervals 70 increase gradually from the inside of the origin 80, and are 50%, 75%, and 90%. When actually implementing the above method, the tolerance intervals 70 are not limited to those in the first embodiment, and the number and percentages may be changed according to actual needs.

[0020] In the first embodiment, as shown in FIGS. 3 to 8 , the 50% tolerance interval 71, the 75% tolerance interval 72, and the 90% tolerance interval 73 are separated by contour lines 90. The contour line 90 closest to the origin 80 is defined as the first contour line 91. The contour line 90 farthest from the origin 80 is defined as the third contour line 93. The contour line 90 located between the first contour line 91 and the third contour line 93 is defined as the second contour line 92. The range of the origin 80 enclosed by the first contour line 91 is the 50% tolerance interval 71. The range between the first contour line 91 and the second contour line 92 is the 75% tolerance interval 72. The range between the second contour line 92 and the third contour line 93 is the 90% tolerance interval 73. The multiple tolerance intervals 70 are each identified by a different color. The color intensity becomes lighter as the range changes from the 50% tolerance interval 71 to the 90% tolerance interval 73. Each contour line 90 is formed by a change in color intensity as it transitions from the 50% tolerance interval 71 to the 90% tolerance interval 73 and delimits the tolerance interval 70 .

[0021] The first embodiment further includes a plurality of markers 100. The markers 100 are located on the outer sides of the plurality of R-Xc diagrams 20 and display patterns of the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and trunk. That is, the markers 100 correspond to the first R-Xc diagram 21, the second R-Xc diagram 22, the third R-Xc diagram 23, the fourth R-Xc diagram 24, the fifth R-Xc diagram 25, and the sixth R-Xc diagram 26. The above-described technical features make it easy to distinguish the muscles of the human limbs to be measured corresponding to the first R-Xc diagram 21, the second R-Xc diagram 22, the third R-Xc diagram 23, the fourth R-Xc diagram 24, the fifth R-Xc diagram 25, and the sixth R-Xc diagram 26, but this is not a requirement for achieving the objectives of the present invention.

[0022] In step (b), the resistance / second geometric parameter (R / G2) and reactance / second geometric parameter (Xc / G2) of the subject's body part are acquired using a body composition analyzer. The acquired resistance / second geometric parameter and reactance / second geometric parameter of the subject's body part are then individually associated with the coordinate P of the human body part R-Xc diagram 20. Based on the location of the coordinate P (first quadrant 41, second quadrant 42, third quadrant 43, or fourth quadrant 44) and the tolerance interval 70 (50% tolerance interval 71, 75% tolerance interval 72, or 90% tolerance interval 73), the subject's muscle mass is compared with the muscle mass of the group, and the tolerance interval 70 of the group is evaluated. The results of step (b) allow the subject to gain a deeper understanding of their own muscle condition.

[0023] In the first embodiment, the height of the subject is used as the second geometric parameter. That is, the resistance / second geometric parameter (R / H2) and the reactance / second geometric parameter (Xc / H2) are the body composition data of the subject corresponding to the human body part R-Xc diagram 20.

[0024] In Ohm's Law, the length (L) and circumference (C) of a human body part cause resistance, but they are easily detectable. Therefore, in the first embodiment, the height of the group is used as the first geometric parameter and the height of the subject is used as the second geometric parameter. When actually implementing the above method, if ease of data acquisition is not a consideration, the X-axis 30 may represent the group's height and circumference Z(R / H1,C1), the length and circumference Z(R / L1,C1), or the height, length and circumference Z(R / H1,L1,C1). The Y-axis 40 may represent the group's height and circumference Z(Xc / H1,C1), the length and circumference Z(Xc / L1,C1), or the height, length and circumference Z(Xc / H1,L1,C1). The resistance / second geometric parameter of the body part to be measured may be the height and circumference of the body part to be measured (R / H2,C2), the length and circumference of the body part to be measured (R / L2,C2), or the height, length and circumference of the body part to be measured (R / H2,L2,C2). The reactance / second geometric parameter of the body part to be measured may be the height and circumference of the body part to be measured (Xc / H2,C2), the length and circumference of the body part to be measured (Xc / L2,C2), or the height, length and circumference of the body part to be measured (Xc / H2,L2,C2). Since the measurement method is not limited to image scanning or tomography technology, the settings of the first geometric parameter and the second geometric parameter are not limited to this embodiment.

[0025] The above is an explanation of the technical features of the first embodiment. Next, we will explain the situation when an evaluation is actually performed.

[0026] As shown in Figures 2 to 7, the resistance and reactance obtained by measuring the target body part are assigned to the first to sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26. The results show that each coordinate P is located in the second quadrant 42 and the 75% tolerance range 72 within the first to sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26. This indicates that the target's whole body, right upper limb, left upper limb, right lower limb, left lower limb, and trunk muscles have relatively low water content. Specifically, because each coordinate P is located in the second quadrant 42 within the first to sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26, the body composition of the target body part is distributed within the 75% tolerance range 72, close to the 90% tolerance range 73.

[0027] In the method 10 for evaluating body composition data of human limbs based on bioelectrical impedance vector analysis technology according to the first embodiment, a first R-Xc diagram 21 displays the condition of the whole body. A second R-Xc diagram 22 displays the condition of the right upper limb. A third R-Xc diagram 23 displays the condition of the left upper limb. A fourth R-Xc diagram 24 displays the condition of the right lower limb. A fifth R-Xc diagram 25 displays the condition of the left lower limb. A sixth R-Xc diagram 26 displays the condition of the trunk. A first quadrant 41 displays a body composition with a relatively low water content. A second quadrant 42 displays a body composition with a relatively high soft tissue content. A third quadrant 43 displays a body composition with a relatively high water content. A fourth quadrant 44 displays a body composition with a relatively low soft tissue content. The tolerance zone 70 is divided into a 50% tolerance zone 71, a 75% tolerance zone 72, and a 90% tolerance zone 73 from the inside to the outside of the origin 80. The above-described technical features allow the subject to have a deeper understanding of their own muscle condition by comparing the subject's muscle mass with the muscle mass of the group and simultaneously evaluating which tolerance limit interval 70 the subject falls within within the group.

[0028] (Second embodiment) A method 10 for evaluating body composition data of a human body part based on bioelectrical impedance vector analysis technology according to the second embodiment of the present invention is shown in Figures 2, 9 to 14. The differences from the first embodiment are as follows:

[0029] As shown in Figures 9 to 14, in the second embodiment, the coordinates obtained by measuring the whole body, right upper limb, left upper limb, right lower limb, left lower limb and trunk of many measurement subjects are located within the first to sixth R-Xc diagrams 21', 22', 23', 24', 25', 26'.

[0030] In the second embodiment, the plurality of tolerance intervals 70' are divided into a 50% tolerance interval 71', a 75% tolerance interval 72', and a 90% tolerance interval 73' from the inside to the outside of the origin 80'.

[0031] In the second embodiment, the plurality of tolerance zones 70' are each delimited by a plurality of contour lines 90'. Each of the plurality of contour lines 90' is displayed in color. The color becomes darker from the contour line 90' ​​closest to the origin 80' outward. The color of the first contour line 91' is light gray. The color of the second contour line 92' is gray. The color of the third contour line 93' is black.

[0032] Other technical features and effects that can be achieved by the second embodiment of the present invention are the same as those of the first embodiment, so detailed descriptions thereof will be omitted. [Explanation of symbols]

[0033] 10: A method for evaluating body composition data of human limbs based on bioimpedance vector analysis technology 20: R-Xc diagram of human body parts 21, 21': First R-Xc diagram 22, 22': Second R-Xc diagram 23, 23': Third R-Xc diagram 24, 24': Fourth R-Xc diagram 25, 25': Fifth R-Xc diagram 26, 26': Sixth R-Xc diagram 30:X axis 40: Y-axis 41:First quadrant 42:Second quadrant 43: Third quadrant 44:Fourth quadrant 50: First Vector 60: Second Vector 70, 70': Tolerance interval 71, 71': 50% tolerance interval 72, 72': 75% tolerance interval 73, 73': 90% tolerance interval 80, 80': Origin 90, 90': Contour line 91, 91': First contour line 92, 92': Second contour line 93, 93': Third contour line 100: Marking P:Coordinate

Claims

1. A method for evaluating body composition data of a human limb based on bioimpedance vector analysis technology, comprising steps (a) and (b), In the step (a), a group of a plurality of human limb part R-Xc maps is provided by a calculation unit, and each of the plurality of human limb part R-Xc maps is composed of an X axis, a Y axis, a first vector, a second vector, and a plurality of tolerance intervals; The X-axis is the standard resistance / first geometric parameter (Z(R / G1)) of the Z-transform of each human body part of the group; the Y-axis is the standard reactance / first geometric parameter of the Z-transform of each body part of the group; the X-axis and the Y-axis are orthogonal to each other, and their intersection is the origin, the X-axis and the Y-axis divide a first quadrant, a second quadrant, a third quadrant, and a fourth quadrant, and the first quadrant, the second quadrant, the third quadrant, and the fourth quadrant each represent one body composition state, the first vector and the second vector are orthogonal to each other and pass through the origin; the plurality of tolerance intervals are expressed in percentages, the plurality of tolerance intervals are distributed in a circular pattern from the inside to the outside of the origin, the percentages increasing from the inside to the outside of the origin, and the plurality of tolerance intervals are distributed across the first quadrant, the second quadrant, the third quadrant, and the fourth quadrant; a body composition analysis device for analyzing the resistance / second geometric parameter (R / G2) and the reactance / second geometric parameter (Xc / G2) of the limb part of the subject to be measured; a body composition analysis device for analyzing the resistance / second geometric parameter and the reactance / second geometric parameter of the limb part of the subject to be measured, ...

2. 2. The method for evaluating body composition data of human limbs based on bioimpedance vector analysis technology according to claim 1, wherein the R-Xc diagrams of the human limbs are six, namely, a first R-Xc diagram, a second R-Xc diagram, a third R-Xc diagram, a fourth R-Xc diagram, a fifth R-Xc diagram and a sixth R-Xc diagram.

3. 3. The method for evaluating body composition data of human limbs based on bioelectrical impedance vector analysis technology according to claim 2, wherein the first R-Xc diagram, the second R-Xc diagram, the third R-Xc diagram, the fourth R-Xc diagram, the fifth R-Xc diagram or the sixth R-Xc diagram displays the whole body, the right upper limb, the left upper limb, the right lower limb, the left lower limb or the trunk of the human body.

4. the body composition data of the human limb body part is created using soft tissue as an evaluation part; 2. The method for evaluating body composition data of a human limb based on bioelectrical impedance vector analysis technology according to claim 1, wherein the first quadrant represents a body composition with a relatively high soft tissue content, the second quadrant represents a body composition with a relatively low water content, the third quadrant represents a body composition with a relatively low soft tissue content, and the fourth quadrant represents a body composition with a relatively high water content.

5. 2. The method for evaluating body composition data of a human limb based on bioelectrical impedance vector analysis technology according to claim 1, wherein the plurality of tolerance zones are divided into a 50% tolerance zone, a 75% tolerance zone, and a 90% tolerance zone from the inside to the outside of the origin.

6. 2. The method for evaluating body composition data of a human limb based on bioelectrical impedance vector analysis technology according to claim 1, wherein the plurality of tolerance zones are divided into a 50% tolerance zone, a 75% tolerance zone, and a 90% tolerance zone from the inside to the outside of the origin.

7. Further comprising a plurality of signs, The method for evaluating body composition data of a human limb based on bioimpedance vector analysis technology according to claim 1, wherein each of the plurality of markers is located outside the R-Xc diagram.

8. the first geometric parameter includes a height, a body part length, and a circumference of the group, or any one of them; 2. The method for evaluating body composition data of a human limb based on bioelectrical impedance vector analysis technology according to claim 1, wherein the second geometric parameter includes the height of the subject, the length and circumference of the limb, or any one of them.

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