Method for evaluating body composition data of each limb segment of human body using bioelectrical impedance vector analysis technology

Abstract

The present disclosure provides a method for evaluating body composition data of each limb segment of a human body using a bioelectrical impedance vector analysis technology, which comprises: (a) providing R-Xc graphs of multiple human body limb segments of a group, wherein each R-Xc graph has an X coordinate axis, a Y coordinate axis, a first vector line, a second vector line, and multiple tolerance intervals, the X coordinate axis represents a Z-transformed standardized resistance / first geometric parameter of each human body limb segment of the group, and the Y coordinate axis represents a Z-transformed standardized reactance / first geometric parameter of each human body limb segment of the group; and (b) measuring, by a body composition analyzer, a resistance / second geometric parameter and a reactance / second geometric parameter of each limb segment of a testee, which correspond to coordinate points in the R-XC graph of each human body limb segment, and evaluating performance indicators of body composition of each limb segment of the testee compared with physiological features of the group.

Description

Method for evaluating body composition data of human limb segments using bioimpedance vector analysis technology Technical Field

[0001] The present disclosure relates to bioimpedance vector analysis technology, and more particularly to a method for evaluating body composition data of various limb segments of the human body using bioimpedance vector analysis technology. Background Art

[0002] Bioelectrical Impedance Vector Analysis (BIVA) uses a weak electric current to pass through the human body to understand the distribution of cells, intercellular fluid (ICF), and extracellular fluid (ECF). It is a technology used to assess the body's composition.

[0003] The human body is primarily composed of muscle, fat, and bone. Currently, a common method for assessing body composition data is to present it in the form of a bar graph, as shown in Figure 1. Taking skeletal muscle mass as an example, muscle mass is first statistically quantified into a first bar graph. This first bar graph is used as an evaluation indicator and categorized as low, normal, or high muscle mass. After the subject's skeletal muscle mass is measured using BIVA, the result is quantified into a second bar graph. By comparing this second bar graph with the first bar graph, it is possible to assess whether the subject's muscle mass is low, normal, or high.

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

[0005] Summary of the Invention

[0006] The main purpose of the present disclosure is to provide a method for evaluating the body composition data of each limb segment of the human body using bioimpedance vector analysis technology. Compared with existing technologies, the present disclosure can evaluate the performance indicators of the body composition of each limb segment of the subject compared to the physiological characteristics of a group, which can enhance industrial utilization.

[0007] To achieve the above objectives, the present disclosure provides a method for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology, which comprises:

[0008] (a) A computing unit provides a plurality of human limb segment R-Xc diagrams of a group, each of which has an X-axis, a Y-axis, a first vector line, a second vector line, and a plurality of tolerance intervals. interval); 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 an origin, and the X-axis and the Y-axis separate a first quadrant, a second quadrant, a third quadrant, and a fourth quadrant, each representing a state of integral composition; the first vector line intersects the second vector line and passes through the origin; the unit of the multiple tolerance interval is a percentage, the multiple tolerance interval is circular, and is arranged from the origin from the inside to the outside. The percentage of the multiple tolerance interval increases from the inside to the outside, and the multiple tolerance interval covers 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 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 limb of the subject. 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 tolerance interval of one of them, that is, the body composition data of the multiple limbs of the subject are evaluated.

[0009] Therefore, the present disclosure provides a method for evaluating the body composition data of each limb segment of the human body using bioimpedance vector analysis technology. Compared with the existing technology, the present disclosure can evaluate the performance indicators of the body composition of each limb segment of the subject compared with the physiological characteristics of the group, which can improve the industry's utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] FIG1 is a method for evaluating body composition data in the prior art;

[0011] FIG2 is a block diagram of the present disclosure;

[0012] FIG3 is a first R-Xc diagram of the first embodiment of the present disclosure;

[0013] FIG4 is a second R-Xc diagram of the first embodiment of the present disclosure;

[0014] FIG5 is a third R-Xc diagram of the first embodiment of the present disclosure;

[0015] FIG6 is a fourth R-Xc diagram of the first embodiment of the present disclosure;

[0016] FIG7 is a fifth R-Xc diagram of the first embodiment of the present disclosure;

[0017] FIG8 is a sixth R-Xc diagram of the first embodiment of the present disclosure;

[0018] FIG9 is a first R-Xc diagram of the second embodiment of the present disclosure;

[0019] FIG10 is a second R-Xc diagram of the second embodiment of the present disclosure;

[0020] FIG11 is a third R-Xc diagram of the second embodiment of the present disclosure;

[0021] FIG12 is a fourth R-Xc diagram of the second embodiment of the present disclosure;

[0022] FIG13 is a fifth R-Xc diagram of the second embodiment of the present disclosure;

[0023] FIG14 is a sixth R-Xc diagram of the second embodiment of the present disclosure;

[0024] Explanation of the accompanying symbols: 10: Method for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology 20: R-Xc diagram of human limb segments 21: First R-Xc diagram 22: Second R-Xc diagram 23: Third R-Xc diagram 24: Fourth R-Xc diagram 25: Fifth R-Xc diagram 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 line 60: Second vector line 70: Allowable range 71: 50% allowable range 72: 75% allowable range 73: 90% allowable range 80: origin 90: contour line 91: first contour line 92: second contour line 93: third contour line 100: mark P: coordinate point 21': first R-Xc diagram 22': second R-Xc diagram 23': third R-Xc diagram 24': fourth R-Xc diagram 25': fifth R-Xc diagram 26': sixth R-Xc diagram 70': allowable interval 71': 50% allowable interval 72': 75% allowable interval 73': 90% allowable interval 80': origin 90': contour line 91': first contour line 92': second contour line 93': third contour line. DETAILED DESCRIPTION

[0025] In order to explain the technical features of the present disclosure in detail, the following first embodiment is described with reference to Figures 2-8.

[0026] The first embodiment of the present disclosure provides a method 10 for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology. The body composition data is based on soft tissue as an example. The soft tissue includes skin, subcutaneous fat, muscle, tendon, tendon sheath, ligament, fascia, synovium, bursa, joint capsule, peripheral nerve, fibrous tissue, lymphatic tissue, vascular tissue, and other connective tissue, but excludes bone and other fat. However, in actual implementation, if required, bone or fat can also be used as the body composition data.

[0027] The method 10 for evaluating body composition data of each limb segment using bioimpedance vector analysis technology comprises:

[0028] (a) A computing unit provides a plurality of R-Xc diagrams 20 of human limb segments of a group. Each R-Xc diagram 20 has an X-axis 30, a Y-axis 40, a first vector line 50, a second vector line 60, and a plurality of tolerance intervals 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. Individual values ​​within this range are estimated. This range is called the tolerance interval. The X-axis 30 represents a Z-transformed normalized resistance / first geometric parameter (Z(R / G1)) of the group, where R is resistance. The Y-axis 40 represents a Z-transformed normalized reactance / first geometric parameter (Z(Xc / G1)) of the group, where Xc is reactance.

[0029] In a first embodiment, the group is middle-aged and elderly people (aged 45 to 65) as an example. The plurality of human limb segment R-Xc diagrams 20 are 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 100 people, including people of various occupations, genders, and regions, etc.). The resistance and reactance obtained from the measurements are then normalized with the height (Height, H) of the large number of subjects to obtain the plurality of parameters (R / H1, Xc / H1). That is, the height of the large number of subjects is used as the first geometric parameter. Subsequently, each R / H1 and each Xc / H1 is further dimensionless to obtain the plurality of human limb segment R-Xc diagrams 20. In actual implementation, the group may also be selected as a comparison object based on demand, such as athletes, the elderly, people of the same geographical location, people with the same physiological characteristics, or people of a specific age group, etc. Therefore, the implementation of the group is not limited to this embodiment.

[0030] The X-axis 30 and the Y-axis 40 intersect to form an origin 80. The origin 80 is the intersection 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 quadrants 41, 42, 43, and 44 respectively represent an integral state. The first vector line 50 and the second vector line 60 intersect and pass through the origin 80. The unit of the multiple allowable interval 70 is percentage (%). The multiple allowable interval 70 is circular and arranged from the inside to the outside of the origin 80. The percentage of the multiple allowable interval 70 increases from the inside to the outside. The multiple allowable interval 70 covers the first quadrant 41, the second quadrant 42, the third quadrant 43, and the fourth quadrant 44.

[0031] In the first embodiment, the computing unit is exemplified by a body composition measuring instrument, and the plurality of human limb segment R-Xc diagrams 20 are presented on the display screen of the body composition measuring instrument. In actual implementation, the computing unit can also be implemented as a computer, a tablet, or other hardware device with computing capabilities. Therefore, the implementation of the computing unit is not limited to this embodiment.

[0032] In the first embodiment, the number of the human limb 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 limb segments represented by the first to sixth R-Xc diagrams 26 are the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and torso, respectively. In actual implementation, the number of the human limb segment R-Xc diagrams 20 can be changed as needed, or the order or arrangement of the human limb segments represented by each human limb segment R-Xc diagram 20 can be changed. Therefore, the number of the human limb segment R-Xc diagrams 20 and the human limb segments represented by the first to sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26 are not limited to this embodiment.

[0033] In the first embodiment, the first quadrant 41 represents a body composition with a low water content, the second quadrant 42 represents a body composition with a high soft tissue content, the third quadrant 43 represents a body composition with a high water content, and the fourth quadrant 44 represents a body composition with a low soft tissue content. In actual implementation, if bone or fat is used as the body composition data for each limb segment in the bioimpedance vector analysis, the meanings of the first through fourth quadrants 41, 42, 43, and 44 will vary depending on the body composition data for each limb segment in the bioimpedance vector analysis.

[0034] In the first embodiment, the plurality of allowable intervals 70 are divided from the origin 80 from the inside to the outside into a 50% allowable interval 71, a 75% allowable interval 72, and a 90% allowable interval 73. The percentages of the plurality of allowable intervals 70 are 50%, 75%, and 90%, respectively. In actual implementation, the number and percentages of the allowable intervals 70 can be changed as needed. Therefore, the number and percentages of the allowable intervals 70 are not limited to this embodiment.

[0035] In the first embodiment, as shown in FIG3-8 , the 50% tolerance interval 71, the 75% tolerance interval 72, and the 90% tolerance interval 73 are respectively separated by a contour line 90. The contour line 90 closest to the origin 80 is a first contour line 91, and the contour line 90 farthest from the origin 80 is a third contour line 93. 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 plurality of tolerance intervals 70 each have a color, and the color is from dark to light from the 50% tolerance interval 71 to the 90% tolerance interval 73. Each of the contour lines 90 The color difference between the 50% tolerance interval 71 and the 90% tolerance interval 73 is formed, thereby facilitating the separation of the tolerance intervals 70 .

[0036] In the first embodiment, a plurality of marks 100 are further included, each of which is located on the outside of each R-Xc diagram 20, and each of the marks 100 is a diagram of the whole body, right upper limb, left upper limb, right lower limb, left lower limb and torso, and each of the marks 100 corresponds to the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26 respectively; therefore, it is easier for people to understand that the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26 represent the muscles of each limb segment of a subject, but this technical feature is not a necessary condition for achieving the present disclosure.

[0037] (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 the R-Xc diagram 20 of each limb segment of the human body. The position of the coordinate point P is located in the first quadrant 41, the second quadrant 42, the third quadrant 43 or the fourth quadrant 44, and belongs to the 50% allowable interval 71, the 75% allowable interval 72 or the 90% allowable interval 73. That is, the assessment is completed to determine which of the allowable intervals 70 of the group the muscle mass of the subject lies in compared to the muscle mass of the group, thereby allowing the subject to further understand his or her own muscle condition.

[0038] In the first embodiment, the second geometric parameter is based on the height of the subject, that is, the resistance / second geometric parameter (R / H2) and the reactance / second geometric parameter (Xc / H2) are corresponding to each of the human limb segments R-Xc diagram 20 as a method of evaluating the subject's body composition data.

[0039] Although, in Ohm's law, the length (L) and circumference (C) of a human limb are both factors that cause resistance, in consideration of ease of 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 data acquisition, 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 The height and circumference of the subject (R / H2, C2), or the limb length and circumference (R / L2, C2), or the height, limb length and circumference (R / H2, L2, C2). The reactance / second geometric parameter of each limb of the subject can also be the height and circumference of the subject (Xc / H2, C2), or the limb length and circumference (Xc / L2, C2), or the height, limb length and circumference (Xc / H2, L2, C2). The measurement method is not limited to imaging scanning or tomography scanning technology, so the implementation of the first and second geometric parameters is not limited to this embodiment.

[0040] The above describes the technical features of the method provided by the first embodiment. The following describes the status during actual evaluation.

[0041] As shown in Figures 2-7, the resistance and reactance measured at each limb of the subject correspond to the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26. It can be seen that each coordinate point P is located in the second quadrant 42 and the 75% allowable range 72 of the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26. Therefore, it can be assessed that the muscles of the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and trunk of the subject all have a low water content, and the coordinate point P is located in the second quadrant 42 of the first to the sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26. Therefore, it can be assessed that the body composition of each limb of the subject belongs to 75% and close to 90% of people.

[0042] Therefore, the method 10 for evaluating body composition data of various human limb segments using bioimpedance vector analysis technology provided in the first embodiment of the present disclosure, through the human limb segments represented by the first to sixth R-Xc diagrams 21, 22, 23, 24, 25, and 26, respectively, are the whole body, right upper limb, left upper limb, right lower limb, left lower limb, and trunk. The first to fourth quadrants 41, 42, 43, and 44 respectively represent a low water content, a high soft tissue content, a high water content, and a low soft tissue content. In addition, the technical features of the 50% allowable interval 71, the 75% allowable interval 72, and the 90% allowable interval 73 can be used to evaluate the muscle mass of the subject compared to the muscle mass of the group, and to determine within which of the allowable intervals 70 of the group the subject falls, thereby allowing the subject to further understand his or her own muscle condition.

[0043] The second embodiment of the present disclosure provides a method 10 for evaluating body composition data of various limb segments using bioimpedance vector analysis technology, as shown in FIG2 and FIG9-14 . The method 10 is similar to the first embodiment described above, but differs in that:

[0044] In the second embodiment, as shown in Figures 9-14, the coordinates measured for the whole body, right upper limb, left upper limb, right lower limb, left lower limb and torso of a large number of subjects are displayed in the first to sixth R-Xc figures 21', 22', 23', 24', 25', and 26'.

[0045] In the second embodiment, the plurality of allowable intervals 70 ′ are divided from the origin 80 ′ from the inner to the outer sides into a 50% allowable interval 71 ′, a 75% allowable interval 72 ′, and a 95% allowable interval 73 ′.

[0046] In the second embodiment, each of the allowable intervals 70' is separated by a contour line 90', and the plurality of contour lines 90' have a color, and the color is from light to dark from the contour line 90' ​​closest to the origin 80' outward; wherein the first contour line 91' is light gray, the second contour line 92' is gray, and the third contour line 93' is black.

[0047] The technical effects of the remaining technical features of the second embodiment of the present disclosure are the same as those of the aforementioned first embodiment, and therefore will not be repeated here.

[0048] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present disclosure. It should be understood that the above are only specific embodiments of the present disclosure and are not intended to limit the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present disclosure should be included in the scope of protection of the present disclosure.

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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