Method for evaluating composition data of each limb section body of human body by bioimpedance vector analysis technology

Abstract

The invention discloses a method for evaluating body composition data of each limb section of a human body by a biological impedance vector analysis technology, which comprises the following steps of: (a) providing a group of R-Xc graphs of a plurality of human limb sections, each R-Xc graph respectively having an X coordinate axis, a Y coordinate axis, a first vector line, a second vector line and a plurality of permissible intervals; the X coordinate axis is a standardized resistance / first geometric parameter of Z conversion of each human limb section of the group; the Y coordinate axis is a standardized reactance / first geometric parameter of Z conversion of each human limb section of the group; and (b) measuring the resistance / second geometric parameter and the reactance / second geometric parameter of each limb section of the testee through a body composition analyzer, and evaluating the performance index of the body composition of each limb section of the testee relative to the physiological characteristics of the group by corresponding to the coordinate points in the R-Xc graph of each human limb section.

Description

Technical Field

[0001] The present invention relates to bioelectrical impedance vector analysis technology, and particularly to a method for evaluating body composition data of each limb segment of the human body using bioelectrical impedance vector analysis technology. Background Art

[0002] Bioelectrical Impedance Vector Analysis (BIVA) is a technique for evaluating human body composition that uses weak electric currents to pass through the human body to understand the distribution between intracellular fluid (ICF) and extracellular fluid (ECF) within the human body.

[0003] Human body composition mainly includes muscle, fat, and bone. Currently, common methods for evaluating body composition data, such as Figure 1 As shown, it is presented in the form of a bar chart. Taking the evaluation of skeletal muscle mass as an example, first, the muscle mass is quantified into a first bar chart through statistics, and this first bar chart is used as a comparison index, which is divided into low, normal muscle mass, or high. When the skeletal muscle mass of the subject is measured by BIVA, the result is quantified into a second bar chart. By comparing the second bar chart with the first bar chart, it is possible to evaluate whether the muscle mass of the subject is low, normal, or high.

[0004] However, the above evaluation method cannot evaluate the performance index of the skeletal muscle mass of the subject compared to the physiological characteristics of a group (such as athletes, the elderly, people in the same geographical location, people with the same physiological characteristics, or people in a specific age group, etc.). Therefore, the above existing methods for evaluating body composition data of each limb segment of the human body still need to be improved. Summary of the Invention

[0005] The main object of the present invention is to provide a method for evaluating body composition data of each limb segment of the human body using bioelectrical impedance vector analysis technology. Compared with the prior art, the present invention can evaluate the performance index of the body composition of each limb segment of the subject compared to the physiological characteristics of a group, which can improve the industrial utilization.

[0006] To achieve the above object, the present invention provides a method for evaluating body composition data of each limb segment of the human body using bioelectrical impedance vector analysis technology, which includes:

[0007] (a) A computing unit provides complex R-Xc diagrams of a group of human body segments. Each of the R-Xc diagrams has an X coordinate axis, a Y coordinate axis, a first vector line, a second vector line, and a plurality of tolerance intervals. The X coordinate axis is the normalized resistance / first geometric parameter (Z(R / G1)) of a Z-transform of each human body segment of the group. The Y coordinate axis is the normalized reactance / first geometric parameter (Z(Xc / G1)) of a Z-transform of each human body segment of the group. The X coordinate axis and the Y coordinate axis intersect to form an origin, and the X coordinate axis and the Y coordinate axis divide a first quadrant, a second quadrant, a third quadrant, and a fourth quadrant, and these quadrants respectively represent a body composition state. The first vector line and the second vector line intersect and pass through the origin. The unit of the plurality of tolerance intervals is a percentage. The plurality of tolerance intervals are annular and are arranged from the inside to the outside of the origin. The percentage of the plurality of tolerance intervals increases from the inside to the outside, and the plurality of tolerance intervals cover the first quadrant, the second quadrant, the third quadrant, and the fourth quadrant. And (b) A resistance / second geometric parameter (R / G2) and a reactance / second geometric parameter (Xc / G2) of each segment of a subject are measured by a body composition analyzer. The resistance / second geometric parameter and the reactance / second geometric parameter of each segment of the subject are corresponded to a coordinate point in each of the human body segment R-Xc diagrams. Then, the position where the coordinate point is located is in the first quadrant, the second quadrant, the third quadrant, or the fourth quadrant, and in one of the tolerance intervals, that is, the body composition data of the plurality of segments of the subject is evaluated and completed.

[0008] Therefore, a method for evaluating body composition data of each segment of the human body by a bioimpedance vector analysis technique provided by the present invention can, compared with the prior art, evaluate the performance index of the body composition of each segment of the subject compared with the physiological characteristics of the group, and can improve the utilization of the industry. Brief Description of the Drawings

[0009] Figure 1 is a method for evaluating body composition data in the prior art;

[0010] Figure 2 is a block diagram of the present invention;

[0011] Figure 3 is the first R-Xc diagram of the first embodiment of the present invention;

[0012] Figure 4 is the second R-Xc diagram of the first embodiment of the present invention;

[0013] Figure 5 is the third R-Xc diagram of the first embodiment of the present invention;

[0014] Figure 6 The fourth R-Xc diagram of the first embodiment of the present invention;

[0015] Figure 7 The fifth R-Xc diagram of the first embodiment of the present invention;

[0016] Figure 8 The sixth R-Xc diagram of the first embodiment of the present invention;

[0017] Figure 9 The first R-Xc diagram of the second embodiment of the present invention;

[0018] Figure 10 The second R-Xc diagram of the second embodiment of the present invention;

[0019] Figure 11 The third R-Xc diagram of the second embodiment of the present invention;

[0020] Figure 12 The fourth R-Xc diagram of the second embodiment of the present invention;

[0021] Figure 13 The fifth R-Xc diagram of the second embodiment of the present invention;

[0022] Figure 14 The sixth R-Xc diagram of the second embodiment of the present invention.

[0023] Explanation of reference numerals:

[0024] 10: Method for evaluating body composition data of each limb segment of the human body by bioelectrical impedance vector analysis technology

[0025] 20: R-Xc diagram of human limb segment

[0026] 21: First R-Xc diagram

[0027] 22: Second R-Xc diagram

[0028] 23: Third R-Xc diagram

[0029] 24: Fourth R-Xc diagram

[0030] 25: Fifth R-Xc diagram

[0031] 26: Sixth R-Xc diagram

[0032] 30: X coordinate axis

[0033] 40: Y coordinate axis

[0034] 41: First quadrant

[0035] 42: Second quadrant

[0036] 43: Third quadrant

[0037] 44: Fourth quadrant

[0038] 50: First vector line

[0039] 60: Second vector line

[0040] 70: Tolerance interval

[0041] 71: 50% tolerance interval

[0042] 72: 75% tolerance interval

[0043] 73: 90% tolerance interval

[0044] 80: Origin

[0045] 90: Contour line

[0046] 91: First contour line

[0047] 92: Second contour line

[0048] 93: Third contour line

[0049] 100: Mark

[0050] P: Coordinate point

[0051] 21’: First R-Xc diagram

[0052] 22’: Second R-Xc diagram

[0053] 23’: Third R-Xc diagram

[0054] 24’: Fourth R-Xc diagram

[0055] 25’: Fifth R-Xc diagram

[0056] 26’: Sixth R-Xc diagram

[0057] 70’: Tolerance interval

[0058] 71’: 50% tolerance interval

[0059] 72’: 75% tolerance interval

[0060] 73’: 90% tolerance interval

[0061] 80’: Origin

[0062] 90’: Contour line

[0063] 91’: First contour line

[0064] 92’: Second contour line

[0065] 93’: The third contour line Detailed implementation manners

[0066] In order to elaborate on the technical features of the present invention in detail, the following first embodiment is hereby provided and described in conjunction with Figure 2-8 as follows.

[0067] The method 10 for evaluating the body composition data of each limb segment of a human body by using the bioelectrical impedance vector analysis technology provided by the first embodiment of the present invention, wherein the body composition data takes a soft tissue as an example, and the coverage range of the soft tissue includes skin, subcutaneous fat, muscle, tendon, tendon sheath, ligament, fascia, synovium, synovial bursa, joint capsule, peripheral nerve, fibrous tissue, lymphoid tissue, vascular tissue, and other connective tissues, and does not include bones and other fats. However, in actual implementation, if there is a need for evaluation, bones or fats can also be used as the body composition data.

[0068] The method 10 for evaluating the body composition data of each limb segment of a human body by using the bioelectrical impedance vector analysis technology includes:

[0069] (a) A computing unit provides a complex R-Xc diagram 20 of a group of human limb segments. Each R-Xc diagram 20 has an X coordinate axis 30, a Y coordinate axis 40, a first vector line 50, a second vector line 60, and a complex tolerance interval 70. The tolerance interval 70 uses the sample mean x as an estimate of the population mean u and the sample standard deviation S as an estimate of the population standard deviation O to estimate the individual values within this range, and this range is called the tolerance interval; the X coordinate axis 30 is a Z-transformed standardized resistance / first geometric parameter (Z(R / G1)) of the group, where R is resistance; the Y coordinate axis 40 is a Z-transformed standardized reactance / first geometric parameter (Z(Xc / G1)) of the group, where Xc is reactance.

[0070] In the first embodiment, the group is exemplified by middle-aged and elderly people (aged 45 to 65). The complex human body segment R-Xc diagram 20 is obtained by measuring the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and torso of a large number of middle-aged and elderly people (more than a hundred, including people of various occupations, genders, regions, etc.), and then standardizing the measured resistance and reactance with the height (Height, H) of the large number of subjects to obtain complex parameters (R / H1, Xc / H1). That is, the height of the large number of subjects is used as the first geometric parameter. Subsequently, each of the R / H1 and each of the Xc / H1 is further dimensionlessized to obtain the complex human body segment R-Xc diagram 20. In actual implementation, the group can also be selected as a comparison object according to requirements, such as athletes, the elderly, people in the same geographical location, people with the same physiological characteristics, or a specific age group, etc. Therefore, the implementation of the group is not limited to this embodiment only.

[0071] The X-axis 30 intersects with the Y-axis 40 to form an origin 80. The origin 80 is the intersection point of the averages of R / H and Xc / H. The X-axis 30 and the Y-axis 40 divide a first quadrant 41, a second quadrant 42, a third quadrant 43, and a fourth quadrant 44. These quadrants 41, 42, 43, and 44 respectively represent a body composition state. The first vector line 50 intersects with the second vector line 60 and passes through the origin 80. The unit of the complex tolerance interval 70 is percentage (%). The complex tolerance interval 70 is annular and arranged from the inside to the outside of the origin 80. The percentage of the complex tolerance interval 70 increases from the inside to the outside, and the complex tolerance interval 70 covers the first quadrant 41, the second quadrant 42, the third quadrant 43, and the fourth quadrant 44.

[0072] In the first embodiment, the calculation unit is exemplified by a body composition measuring instrument, and the complex human body segment R-Xc diagram 20 is exemplified by being presented on the display screen of the body composition measuring instrument. In actual implementation, the calculation unit can also be implemented as a computer, a tablet, or other hardware devices with computing functions. Therefore, the implementation form of the calculation unit is not limited to this embodiment only.

[0073] In the first embodiment, the number of the human body segment R-Xc diagrams 20 is six, namely a first R-Xc diagram 21, a second R-Xc diagram 22, a third R-Xc diagram 23, a fourth R-Xc diagram 24, a fifth R-Xc diagram 25 and a sixth R-Xc diagram 26; the human body segments represented by the first to the sixth R-Xc diagrams 26 are the whole body, the right upper limb, the left upper limb, the right lower limb, the left lower limb and the trunk respectively. In actual implementation, the number of the human body segment R-Xc diagrams 20 can be changed according to requirements, or the order or arrangement of the human body segments represented by each of the human body segment R-Xc diagrams 20 can be changed. Therefore, the number of the human body segment R-Xc diagrams 20 and the human body segments represented by the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, 26 are not limited to this embodiment only.

[0074] In the first embodiment, the body composition state represented by the first quadrant 41 is a low water percentage, the body composition state represented by the second quadrant 42 is a high soft tissue percentage, the body composition state represented by the third quadrant 43 is a high water percentage, and the body composition state represented by the fourth quadrant 44 is a low soft tissue percentage. In actual implementation, if bones or fat are used as the bioelectrical impedance vector analysis to evaluate the body composition data of each limb segment of the human body, the meanings represented by the first to the fourth quadrants 41, 42, 43, 44 will change according to the different bioelectrical impedance vector analysis for evaluating the body composition data of each limb segment of the human body.

[0075] In the first embodiment, the complex tolerance interval 70 is divided from the origin 80 from the inside to the outside into a 50% tolerance interval 71, a 75% tolerance interval 72 and a 90% tolerance interval 73, and the percentages of the complex tolerance interval 70 are 50%, 75% and 90% respectively. In actual implementation, the number and percentage of the tolerance interval 70 can be changed according to requirements. Therefore, the number and percentage of the tolerance interval 70 are not limited to this embodiment only.

[0076] In the first embodiment, as Figure 3-8As shown, the 50% tolerance interval 71, the 75% tolerance interval 72, and the 90% tolerance interval 73 are separated by a contour line 90 respectively. The contour line 90 closest to the origin 80 is a first contour line 91, the contour line 90 farthest from the origin 80 is a third contour line 93, and the contour line between the first contour line 91 and the third contour line 93 is a second contour line 92. The range of the first contour line 91 around the origin 80 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, and the range between the third contour line 93 and the second contour line 92 is the 90% tolerance interval 73. The plural tolerance intervals 70 each have a color, and the color fades from the 50% tolerance interval 71 to the 90% tolerance interval 73. Each contour line 90 is formed by the color difference between the 50% tolerance interval 71 and the 90% tolerance interval 73, thereby facilitating the separation of each tolerance interval 70.

[0077] In the first embodiment, it further includes plural markings 100. Each marking 100 is located outside each R-Xc diagram 20, and each marking 100 is respectively a graphic of the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and torso, and each marking 100 respectively corresponds to the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, 26; thus, it is easier to understand the muscles of each limb segment of a subject represented by the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, 26. However, this technical feature is not a necessary condition for achieving the present invention.

[0078] (b) The body composition analyzer measures a resistance / second geometric parameter (R / G2) and a reactance / second geometric parameter (Xc / G2) of each limb segment of the subject, and corresponds the resistance / second geometric parameter and reactance / second geometric parameter of each limb segment of the subject to a coordinate point P in each human limb segment R-Xc diagram 20. Then, the position where the coordinate point P is located is in the first quadrant 41, the second quadrant 42, the third quadrant 43, or the fourth quadrant 44, and belongs to the 50% tolerance interval 71, the 75% tolerance interval 72, or the 90% tolerance interval 73. That is, it is evaluated that the muscle mass of the subject compared to the muscle mass of the group is within which tolerance interval 70 of the group. Therefore, the subject can further understand his own muscle state.

[0079] In the first embodiment, the second geometric parameter takes the height of the subject as an example, that is, the resistance / second geometric parameter (R / H2) and the reactance / second geometric parameter (Xc / H2) are corresponding to each human limb segment R-Xc diagram 20 as a way to evaluate the body composition data of the subject.

[0080] Although in Ohm's law, both the limb length (length, L) and circumference (circumference, C) of the human body are factors contributing to resistance, for the sake of easy measurement, in this embodiment, the height of the group is directly used as the first geometric parameter, and the height of the subject is used as the second geometric parameter. In actual implementation, without considering the difficulty of obtaining data, the X-axis 30 can also be the height and circumference Z(R / H1, C1) of the group, or the limb length and circumference Z(R / L1, C1), or the height, limb length and circumference Z(R / H1, L1, C1), and the Y-axis can also be the height and circumference Z(Xc / H1, C1) of the group, or the limb length and circumference Z(Xc / L1, C1), or the height, limb length and circumference Z(Xc / H1, L1, C1); and the resistance / second geometric parameter of each limb of the subject can also be the height and circumference (R / H2, C2) of the subject, or the limb length and circumference (R / L2, C2), or the height, limb length and circumference (R / H2, L2, C2), and the reactance / second geometric parameter of each limb of the subject can also be the height and circumference (Xc / H2, C2) of the subject, or the limb length and circumference (Xc / L2, C2), or the height, limb length and circumference (Xc / H2, L2, C2), and the measurement method is not limited to techniques such as image scanning or tomography, so the implementation forms of the first and second geometric parameters are not limited to this embodiment only.

[0081] The above describes the technical features of the method provided by the first embodiment. The following describes the actual evaluation status.

[0082] As Figure 2-7 shown, by corresponding the resistance and reactance measured for each limb of the subject to the first to sixth R-Xc diagrams 21, 22, 23, 24, 25, 26, it can be known that each coordinate point P is located in the second quadrant 42 and the 75% tolerance interval 72 of the first to sixth R-Xc diagrams 21, 22, 23, 24, 25, 26. From this, it can be evaluated that the muscles of the whole body, right upper limb, left upper limb, right lower limb, left lower limb and trunk of the subject have a low water content ratio, and the coordinate point P is located in the second quadrant 42 of the first to sixth R-Xc diagrams 21, 22, 23, 24, 25, 26. From this, it can be evaluated that the body composition of each limb of the subject belongs to those of 75% and approaching 90% of people.

[0083] Therefore, the method 10 for evaluating the body composition data of each limb segment of the human body provided by the first embodiment of the present invention. The human limb segments represented by the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, 26 are the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and trunk respectively. Each of the first to the fourth quadrants 41, 42, 43, 44 represents a low water proportion, a high soft tissue proportion, a high water proportion, and a low soft tissue proportion respectively. Additionally, with the technical features of each of the 50% tolerance intervals 71, the 75% tolerance interval 72, and the 90% tolerance interval 73, it can evaluate whether the muscle mass of the subject compared to the muscle mass of the group falls within which tolerance interval 70 in the group. Thereby, the subject can further understand their own muscle state.

[0084] The method 10 for evaluating the body composition data of each limb segment of the human body provided by the second embodiment of the present invention, as Figure 2 and Figure 9-14 shown, is mainly generally the same as the aforementioned first embodiment. The difference is that:

[0085] In the second embodiment, as Figure 9-14 shown, the coordinates measured for the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and trunk of the large number of subjects are all displayed in the first to the sixth R-Xc diagrams 21’, 22’, 23’, 24’, 25’, 26’.

[0086] In the second embodiment, the plurality of tolerance intervals 70’ are divided from the origin 80’ from the inside to the outside into a 50% tolerance interval 71’, a 75% tolerance interval 72’, and a 95% tolerance interval 73’.

[0087] In the second embodiment, each of the tolerance intervals 70’ is separated by a contour line 90’, and the plurality of contour lines 90’ have a color. The color is from light to dark from the contour line 90’ closest to the origin 80’ outwards; where the first contour line 91’ is light gray, the second contour line 92’ is gray, and the third contour line 93’ is black.

[0088] The technical effects of the remaining technical features of the second embodiment of the present invention are the same as those of the aforementioned first embodiment, so they will not be elaborated further.

[0089] The specific embodiments described above have further elaborated on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and do not limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology, comprising: A computing unit provides a plurality of human limb segments of a group, wherein each of the R-Xc diagrams has an X-axis, a Y-axis, a first vector line, a second vector line, and a plurality of allowable intervals; the X-axis is a Z-transformed normalized resistance / first geometric parameter (Z(R / G1)) of each human limb segment of the group; the Y-axis is a Z-transformed normalized reactance / first geometric parameter (Z(Xc / G1)) of each human limb segment of the group; the X-axis and the Y-axis intersect to form a an origin, and the X-axis and the Y-axis are separated by a first quadrant, a second quadrant, a third quadrant, and a fourth quadrant, each representing an integral state; the first vector line and the second vector line intersect and pass through the origin; the unit of the multiple allowable intervals is a percentage, the multiple allowable intervals are circular and arranged from the inside to the outside of the origin, the percentage of the multiple allowable intervals increases from the inside to the outside, and the multiple allowable intervals cover the first quadrant, the second quadrant, the third quadrant, and the fourth quadrant; and A resistance / second geometric parameter (R / G2) and a reactance / second geometric parameter (Xc / G2) of each limb of a subject are measured by an integrated composition analyzer, and the resistance / second geometric parameter and the reactance / second geometric parameter of each limb of the subject are corresponded to a coordinate point in the R-Xc diagram of each human limb segment. The position of the coordinate point is located in the first quadrant, the second quadrant, the third quadrant or the fourth quadrant, and in the allowable interval of one of them, thus completing the evaluation of the body composition data of the multiple limb segments of the subject.

2. The method for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology according to claim 1, wherein: The number of the R-Xc diagrams of the human limb segment is 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. The method for evaluating body composition data of various human limb segments using bioimpedance 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 represent the human limb segments respectively, the whole body, right upper limb, left upper limb, right lower limb, left lower limb or torso.

4. The method for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology according to claim 1, wherein: The bioimpedance vector analysis evaluates the body composition data of each limb of the human body using soft tissue as an example, and the body composition states represented by the first quadrant, the second quadrant, the third quadrant, and the fourth quadrant are a high soft tissue ratio, a low water ratio, a low soft tissue ratio, and a high water ratio.

5. The method for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology according to claim 1, wherein: The plurality of tolerance intervals are divided from the origin from the inside to the outside into a 50% tolerance interval, a 75% tolerance interval, and a 90% tolerance interval.

6. The method for evaluating body composition data of various limb segments of the human body using bioimpedance vector analysis technology according to claim 1, wherein: The plurality of tolerance intervals are divided from the origin from the inside to the outside into a 50% tolerance interval, a 75% tolerance interval and a 95% tolerance interval.

7. The method for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology according to claim 1, wherein: It further includes a plurality of markings, each of which is located outside each of the R-Xc diagrams.

8. The method for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology according to claim 1, wherein: The first geometric parameter includes one or a combination of the height, limb length or circumference of the group; the second geometric parameter includes one or a combination of the height, limb length or circumference of the subject.

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