TWM573213U - Bioelectrical impedance analysis instrument - Google Patents

Abstract

The present invention discloses a bioelectrical impedance analysis instrument, comprising: a bioelectrical impedance sensing device, a user interface device, a storage unit, and a processing unit. The bioelectrical impedance sensing device is used to obtain the bioelectrical impedance of the subject. The user interface device is configured to receive the personal data of the subject. The processing unit is electrically coupled to the bioelectrical impedance sensing device, the storage unit and the user interface device, and activates a bioelectrical impedance analysis prediction model of a group of the storage unit according to the personal data of the subject, and the processing unit transmits the bioelectrical impedance analysis. The predictive model converts the bioelectrical impedance of the subject, and calculates the estimated body composition data of the subject; wherein the bioelectrical impedance analysis predictive model is modeled based on multiple training materials of multiple training testers of the ethnic group. .

Description

Bioelectrical impedance analysis instrument

This creation is about a physiological data measuring device, and more particularly relates to a bioelectrical impedance analysis instrument.

In order to maintain a healthy body, it is necessary to analyze the body composition of the human body, for example, to measure the body fat mass and the muscle mass. Since the body fat machine has the advantages of being easy to use and low in cost, it is used by the public for daily use. . Body fat machines typically use bioelectrical impedance analysis to measure body composition.

Instruments using bioelectrical impedance analysis (BIA) are widely used by people of all ages. However, the conventional bioelectrical impedance analysis instrument uses the processing estimation method developed by the manufacturer itself to measure and estimate the body composition of all subjects, often ignoring the differences of the age groups or ethnic groups of individual subjects. It is inevitable that there is a certain error in the estimated body composition. Moreover, the body composition obtained by using bioelectrical impedance analyzers of different models and different brands may also be different, which causes users to be troubled in analyzing and comparing body composition.

Therefore, the instrument for measuring the body composition has yet to be improved, so that the population can measure the body composition more accurately and conveniently.

One of the aims of the present invention is to provide a bioelectrical impedance analysis instrument that can utilize a bioelectrical impedance analysis prediction model of a certain ethnic group (for example, an elderly population) to obtain a body composition data of a subject. The bioelectrical impedance analysis instrument according to the present invention can avoid the systematic error of the conventional bioelectrical impedance analysis instrument in different ethnic group measurement, thereby being effectively applied to evaluate the body composition of a certain ethnic group, such as an elderly person.

In order to achieve at least the above purposes, the present invention proposes a bioelectrical impedance analysis instrument, comprising: a bioelectrical impedance sensing device, a user interface device, a storage unit, and a processing unit. The bioelectrical impedance sensing device is used to obtain the bioelectrical impedance of a subject. The user interface device is configured to receive the personal data of the subject, and the personal data of the subject includes age information. The storage unit stores a population bioelectrical impedance analysis prediction model. The processing unit is electrically coupled to the bioelectrical impedance sensing device, the storage unit and the user interface device, and the bioelectrical impedance analysis prediction model is enabled according to the personal data of the subject, and the processing unit transmits the biological unit when the bioelectrical impedance analysis prediction model is enabled. The electrical impedance analysis predicts the model to convert the bioelectrical impedance of the subject, and calculates the estimated body composition data of the subject according to the bioelectrical impedance of the converted subject; wherein the bioelectrical impedance analysis predictive model is based on the ethnic group Train the tester's multiple training materials to model.

In one embodiment of the present invention, the bioelectrical impedance analysis prediction model of the ethnic group is a bioelectrical impedance analysis prediction model of an elderly group, and the processing unit is enabled when the age data in the subject's personal data is greater than or equal to the age threshold value. Bioelectrical impedance analysis prediction model.

In one embodiment of the present invention, the training materials include a plurality of personal data of the training testers, a plurality of measured bioelectrical impedances, and a plurality of target bioresistances.

In an embodiment of the present invention, the processing unit presents the estimated body composition data through the user interface device, wherein the estimated body composition data includes the muscle mass, the fat mass, the bone mass, the arm muscle mass, the trunk muscle mass, At least one of the amount of leg muscles.

In an embodiment of the present invention, the bioelectrical impedance sensing device includes a bioelectrical impedance measuring unit and a plurality of sensing portions. The plurality of sensing portions are electrically coupled to the bioelectrical impedance measuring unit. When the body of the subject contacts the sensing portions, the bioelectrical impedance measuring unit acquires the bioelectrical impedance of the subject.

In some embodiments of the present invention, the bioelectrical impedance sensing device is a portable device or a wearable device.

In some embodiments of the present invention, the bioelectrical impedance analysis instrument is one of a vertical device, a portable device, and a wearable device.

In one embodiment of the present invention, the bioelectrical impedance analysis apparatus further includes a communication unit electrically coupled to the processing unit and configured to communicate with an external device.

In one embodiment of the present invention, the bioelectrical impedance analysis prediction model of the ethnic group is a first bioelectrical impedance analysis prediction model, and the storage unit further stores a plurality of bioelectrical impedance analysis prediction models, and the bioelectrical impedance analysis prediction models. The first bioelectrical impedance analysis prediction model and a second bioelectrical impedance analysis prediction model of another group are included, and the processing unit activates one of the bioelectrical impedances selected from the bioelectrical impedance analysis prediction model according to the personal data of the subject. The prediction model is analyzed. When the selected bioelectrical impedance analysis prediction model is enabled, the processing unit converts the bioelectrical impedance of the subject through the selected bioelectrical impedance analysis prediction model, and calculates the bioelectrical impedance of the converted subject according to the bioelectrical impedance of the converted subject. The subject's estimate of body composition data.

Thereby, the above embodiment discloses a bioelectrical impedance analysis instrument which can utilize a bioelectrical impedance analysis prediction model of at least one group (for example, an elderly group) to obtain an estimated body composition data of the subject. The bioelectrical impedance analysis instrument of the embodiment can avoid the systematic error of the conventional bioelectrical impedance analysis instrument in different ethnic group measurement, thereby being effectively applied to evaluate the body composition of a certain ethnic group, such as an elderly person. In addition, the bioelectrical impedance analysis instrument according to the present invention can be implemented in any form such as a vertical device, a portable device or a wearable device, so as to be used and popularized by the public.

In order to fully understand the purpose, features and effects of this creation, the following specific examples, together with the attached drawings, provide a detailed description of the creation, as explained below:

Please refer to FIG. 1 , which is a schematic block diagram of a bioelectrical impedance analysis instrument according to an embodiment of the present invention. As shown in FIG. 1, the bioelectrical impedance analysis apparatus 1 includes a bioelectrical impedance sensing device 10, a user interface device 20, a storage unit 30, and a processing unit 40. The bioelectrical impedance sensing device 10 is configured to acquire a bioelectrical impedance of a subject. The user interface device 20 is configured to interact with the subject or present measurement results, such as receiving the personal data of the subject, and the subject's personal data includes age information. The user interface device 20 can be implemented in various manners such as a touch screen, an LCD screen, or a button. The storage unit 30 stores a bioelectrical impedance analysis prediction model 31 of a group. The storage unit 30 is, for example, various storage devices such as a memory or a hard disk. The processing unit 40 is electrically coupled to the bioelectrical impedance sensing device 10, the storage unit 30, and the user interface device 20, and activates the bioelectrical impedance analysis prediction model 31 according to the personal data of the subject. The processing unit 40 is, for example, any processing circuit such as a microprocessor, a microcontroller, or a special application integrated circuit.

When the bioelectrical impedance analysis prediction model 31 is enabled, the processing unit 40 converts the bioelectrical impedance of the subject through the bioelectrical impedance analysis prediction model 31, and calculates the estimated estimation of the subject according to the bioelectrical impedance of the converted subject. The body composition data is measured; wherein the bioelectrical impedance analysis prediction model 31 is modeled based on multiple training materials of a plurality of training testers of the ethnic group.

For example, the bioelectrical impedance analysis prediction model 31 is modeled based on multiple training materials of a plurality of training testers of a certain ethnic group (eg, an ethnic group, a region, a country, or a ethnic group), and such training materials include this The tester's multiple profiles, multiple measurements of bioelectrical impedance and multiple target bioresistances are trained. The bioelectrical impedance analysis prediction model 31 can be implemented and stored in the storage unit 30 using a program module or lookup table or other various means for the processing unit 40 to utilize or execute.

For example, the bioelectrical impedance analysis prediction model 31 of this group is a bioelectrical impedance analysis prediction model of an elderly group, such as a bioelectrical impedance analysis prediction model for an elderly population in a certain country or region, such as an elderly person over 65 years old in Taiwan. Thereby, the bioelectrical impedance analysis apparatus 1 can be configured to be able to obtain a more accurate estimated body composition data based on the bioelectrical impedance analysis prediction model 31 for subjects belonging to the elderly population. The body composition data is estimated to include at least one of a muscle mass, a fat mass, a bone mass, an arm muscle mass, a trunk muscle mass, and a leg muscle mass of the subject.

For example, for the modeling of the bioelectrical impedance analysis prediction model, the body composition data can be measured by dual energy X-ray absorptiometry (DXA) for each training tester in the measurement target group. Refer to the gold standard, and at the same time use the existing bioelectrical impedance analysis instrument to measure the bioelectrical impedance of the measurement training tester and the body composition data obtained. The accuracy of the measurement of body composition by the dual-energy X-ray absorber is higher than that of the conventional bioelectrical impedance analysis instrument. Dual-energy X-ray absorbers are generally bed-shaped and take up a large volume. When in use, the subject must lie flat on the platform under test of the dual energy X-ray absorptive device and be scanned by its scanning unit. Dual-energy X-ray absorbers are expensive, difficult to operate and maintain, are not portable, and are radioactive, so most medical institutions use them for clinical diagnostics and evaluation.

In addition, the test tester's profile may include age, height, weight, and gender, or may further include a body mass index (BMI), where BMI can be defined as the weight divided by the square of the height. For example, a dual-energy X-ray absorptiometer is used to measure the body composition of 438 health check-ups (179 males, 259 females, all over 65 years old), and is commercially available using a standing quadrupole eight-touch type. The bioelectrical impedance analysis instrument measures the bioelectrical impedance of the right arm, the left arm, the trunk, the right leg, and the left leg of the training tester, and the measurement frequency includes 1 kHz, 5 kHz, 50 kHz, 250 kHz, 500 kHz, and 1000 kHz. For example, using linear regression analysis, you can obtain values that estimate body composition data (such as muscle mass, fat mass, bone mass, arm muscle mass, trunk muscle mass, and leg muscle mass). Use personal data (such as age, height, weight, gender, BMI at least one) and bioelectrical impedance (measuring the bioelectrical impedance of various parts of the body of the training tester at different measurement frequencies) as a function of the independent variable From this, a bioelectrical impedance analysis prediction model can be derived. However, this creation is not limited by the examples related to the above modeling, and the bioelectrical impedance analysis prediction model can also be obtained by using other functional relationships or correspondence tables.

Referring to FIG. 1 again, the bioelectrical impedance analysis prediction model 31 is based on a linear regression formula. When the bioelectrical impedance analysis prediction model 31 is enabled, the processing unit 40 converts the subject through the bioelectrical impedance analysis prediction model 31. Bioelectrical impedance, for example, multiplies the right arm at a bioelectrical impedance (or bioelectrical impedance of other sites) measuring at 1 kHz by a corresponding factor. The processing unit 40 calculates the estimated body composition data of the subject according to the bioelectrical impedance of the converted subject, for example, multiplying the bioelectrical impedance of each part of the subject's body at different measurement frequencies by the corresponding The coefficients are added later, and the personal data (such as at least one of age, height, weight, gender, and BMI) is multiplied by the corresponding coefficient, and then the total result is estimated body composition data (such as muscle). The amount of any amount of data, amount of fat, bone mass, arm muscle mass, trunk muscle mass, and leg muscle mass).

In this way, the bioelectrical impedance analysis instrument 1 of the present embodiment can avoid the systematic error of the conventional bioelectrical impedance analysis instrument in different ethnic group measurement by using the bioelectrical impedance analysis prediction model 31, and thus can be effectively applied to evaluate a certain ethnic group, such as The body composition of the elderly. In the case where the bioelectrical impedance analysis prediction model 31 is an elderly population, the bioelectrical impedance analysis apparatus 1 can be used to monitor the nutritional status of the elderly, in addition to being able to accurately obtain the body composition of the elderly. Detecting ethnic minorities in the community.

In one embodiment of the present invention, the bioelectrical impedance analysis prediction model 31 of the ethnic group is a bioelectrical impedance analysis prediction model 31 of an elderly group, and the age data of the processing unit 40 in the subject's personal data is greater than or equal to the age threshold. The bioelectrical impedance analysis prediction model 31 is enabled for the value. For example, the bioelectrical impedance analysis apparatus 1 may have a normal mode and a group mode. When the subject inputs the age data in the personal data through the user interface device 20 is greater than or equal to the age threshold (for example, 65), the processing unit 40 enters. Ethnicity model to enable predictive models of bioelectrical impedance analysis for older communities. When the age data entered by the subject is less than the age threshold, the processing unit 40 enters the ethnic mode normal mode to enable a bioelectrical impedance analysis prediction model that is suitable for a population under 65 years or a general purpose.

Please refer to FIG. 2, which is a schematic block diagram of an embodiment of the bioelectrical impedance sensing device 10 of FIG. In one embodiment of the present invention, the bioelectrical impedance sensing device 10 includes a bioelectrical impedance measuring unit 110 and a plurality of sensing portions 121, 122, 123, and 124. The plurality of sensing portions 121-124 are electrically coupled to the bioelectrical impedance measuring unit 110. When the body of the subject contacts the sensing portions, the bioelectrical impedance measuring unit 110 acquires the bioelectrical impedance of the subject. Each sensing portion may also include one or more electrodes. For example, the subject can have the left and right hands touch the sensing portions 121 and 122, respectively, and simultaneously let the left and right feet contact the sensing portions 123 and 124, respectively, to measure the bioelectrical impedance. The bioelectrical impedance measuring unit 110 may include, for example, an alternating current generating circuit, a voltage measuring circuit, an analog digital converter, and the like. However, this creation is not limited by the above examples.

In some embodiments of the present invention, the bioelectrical impedance sensing device 10 is a portable device or a wearable device. For example, the bioelectrical impedance measuring unit 110 may be disposed on the wearable object to allow the user to perform the measurement by using the wearing method. The sensing portion can be disposed or configured as a wearable such as a glove, a bracelet, a foot cover or a foot ring.

Please refer to FIG. 3 , which is a schematic diagram of an embodiment of the bioelectrical impedance analysis instrument based on FIG. 1 . As shown in FIG. 3, the bioelectrical impedance analysis instrument 2 is implemented as a portable device, wherein the bioelectrical impedance analysis instrument 2 has a housing 100A and sensing portions 121A, 122A. Further, in another embodiment, the outer casing 100A of the bioelectrical impedance analysis instrument 2 can be changed to a wearable such as a clothes, a bracelet or the like to make the bioelectrical impedance analysis instrument 2 a wearable device.

Please refer to FIG. 4 , which is a schematic diagram of another embodiment of the bioelectrical impedance analysis instrument based on FIG. 1 . As shown in FIG. 4, the bioelectrical impedance analysis instrument 3 is an upright device in which the bioelectrical impedance analysis instrument 3 has a casing 100B, a plurality of sensing portions 121B, 122B, 123B, and 124B, and a user interface device 20B. The user interface device 20B is a touch screen, and may also include a button. The sensing units 121B and 122B are used to hold the left and right hands of the subject, and the sensing units 123B and 124B are used to measure the left and right feet of the subject. Other components of the bioelectrical impedance analysis instrument 3 are disposed in the outer casing 100B.

Please refer to FIG. 5, which is a schematic block diagram of another embodiment of the bioelectrical impedance analysis instrument based on FIG. 1. In one embodiment of the present invention, the bioelectrical impedance analysis instrument further includes a communication unit 50 electrically coupled to the processing unit 40 and configured to be wired (eg, USB or regional network, etc.) or wirelessly with the external device 90 ( Communicate such as Bluetooth or Wi-Fi. The external device 90 is, for example, a smart device such as a mobile phone or a tablet computer or a desktop computer, or may be a server connected through a network such as a cloud server. The processing unit 40 can transmit the body composition data or other data or status generated by the bioelectrical impedance analysis instrument to the external device 90 by the communication unit 50 for further storage, analysis or other purposes.

Referring to FIG. 5 again, in an embodiment of the present invention, the storage unit 30 based on the bioelectrical impedance analysis apparatus of FIG. 1 further stores a plurality of bioelectrical impedance analysis prediction models, and the bioelectrical impedance analysis prediction models include The first bioelectrical impedance analysis of a population of predictive models 31A and the second bioelectrical impedance analysis predictive model 32A of the second population.

The processing unit 40 enables the bioelectrical impedance analysis prediction model selected by one of the bioelectrical impedance analysis prediction models according to the personal data of the subject, and when the selected bioelectrical impedance analysis prediction model is enabled, the processing unit 40 transmits the selected organism. The electrical impedance analysis predicts the model to convert the bioelectrical impedance of the subject, and calculates the estimated body composition data of the subject based on the bioelectrical impedance of the converted subject. For example, the first bioelectrical impedance analysis prediction model 31A of the first group is a bioelectrical impedance analysis prediction model of the elderly population in Taiwan, and the second bioelectrical impedance analysis prediction model 32A of the second group is the age of Japan or other countries or regions. Bioelectrical impedance analysis prediction model for ethnic groups. The processing unit 40 activates the second bioelectrical impedance analysis prediction model 32A when the subject enters the country in the profile as Japan and the age exceeds the age threshold (eg, 65 or 70). The processing unit 40 activates the first bioelectrical impedance analysis prediction model 31A when the subject enters the country in the profile as Taiwan and the age exceeds the age threshold (eg, 65 or 70). In this way, the results of the body composition can be made more precise. However, this creation is not limited by the above examples, and the bioelectrical impedance analysis prediction model is not limited to the elderly population or the country. For example, a bioelectrical impedance analysis prediction model of more different ethnic groups can be established based on the bioelectrical impedance analysis instrument of FIG. For example, a bioelectrical impedance analysis prediction model such as China, the United States, or Canada, or a bioelectrical impedance analysis prediction model for young or adolescents.

Thereby, the above embodiment discloses a bioelectrical impedance analysis instrument, which can be configured to be able to obtain a more accurate estimated body composition data according to the bioelectrical impedance analysis prediction model for a subject belonging to a certain group. The bioelectrical impedance analysis instrument of the embodiment can avoid the systematic error of the conventional bioelectrical impedance analysis instrument in different ethnic group measurement by using the bioelectrical impedance analysis prediction model, and thus can be effectively applied to evaluate the body of a certain ethnic group, such as an elderly person. composition. For the example of the bioelectrical impedance analysis prediction model for the elderly population, the bioelectrical impedance analysis instrument can be used to accurately monitor the nutritional status of the elderly and to detect the community, in addition to being able to accurately obtain the body composition of the elderly. A group of people with less muscle. In addition, the bioelectrical impedance analysis instrument according to the present invention can be implemented in various forms such as a vertical device, a portable device or a wearable device, so as to facilitate the use and promotion of the population, and the body detection of the relevant ethnic group is carried out. Come to great help.

The present invention has been disclosed in the above preferred embodiments, and it should be understood by those skilled in the art that the present invention is only intended to depict the present invention and should not be construed as limiting the scope of the present invention. It should be noted that variations and permutations equivalent to those of the embodiments are intended to be included within the scope of the present invention. Therefore, the scope of protection of this creation is subject to the definition of the scope of patent application.

1, 2, 3‧‧‧ Bioelectrical impedance analysis instruments

10‧‧‧Bioelectrical impedance sensing device

20, 20A, 20B‧‧‧ user interface devices

30‧‧‧ storage unit

31, 31A, 32A‧‧‧ Bioelectrical impedance analysis prediction model

40‧‧‧Processing unit

50‧‧‧Communication unit

90‧‧‧External devices

100A, 100B‧‧‧ housing

110‧‧‧Bioelectrical impedance measuring unit

121~124‧‧‧Sensing Department

121A~122A‧‧‧Sensor Department

121B~124B‧‧‧Sense Department

Fig. 1 is a schematic block diagram of a bioelectrical impedance analysis instrument according to an embodiment of the present invention. FIG. 2 is a schematic block diagram of an embodiment of the bioelectrical impedance sensing device of FIG. 1. FIG. FIG. 3 is a schematic view showing an embodiment of the bioelectrical impedance analysis instrument based on FIG. 1. FIG. Fig. 4 is a schematic view showing another embodiment of the bioelectrical impedance analysis instrument based on Fig. 1. FIG. 5 is a schematic block diagram of another embodiment of the bioelectrical impedance analysis instrument based on FIG. 1. FIG.

Claims (9)

A bioelectrical impedance analysis apparatus includes: a bioelectrical impedance sensing device for acquiring a bioelectrical impedance of a subject; a user interface device for receiving the personal data of the subject, the subject's The personal data includes age data; a storage unit stores a bioelectrical impedance analysis prediction model of a group; and a processing unit electrically coupled to the bioelectrical impedance sensing device, the storage unit and the user interface device, and The biometric data of the subject is used to enable the bioelectrical impedance analysis prediction model, and when the bioelectrical impedance analysis prediction model is enabled, the processing unit converts the bioelectrical impedance of the subject through the bioelectrical impedance analysis prediction model, and according to The converted bioelectrical impedance of the subject calculates an estimated body composition data of the subject; wherein the bioelectrical impedance analysis predictive model is based on multiple training materials of the plurality of training testers of the ethnic group. mold. The bioelectrical impedance analysis instrument according to claim 1, wherein the bioelectrical impedance analysis prediction model of the ethnic group is a bioelectrical impedance analysis prediction model of an elderly group, and the age data of the processing unit in the personal data of the subject The bioelectrical impedance analysis prediction model is enabled when the threshold is greater than or equal to one age. The bioelectrical impedance analysis apparatus according to claim 1, wherein the training materials include a plurality of personal data of the training testers, a plurality of measured bioelectrical impedances, and a plurality of target bioresistances. The bioelectrical impedance analysis apparatus according to claim 1, wherein the processing unit presents the estimated body composition data through the user interface device, wherein the estimated body composition data includes a muscle mass, a fat mass, and a bone of the subject At least one of mass, arm muscle mass, trunk muscle mass, and leg muscle mass. The bioelectrical impedance analysis device of claim 1, wherein the bioelectrical impedance sensing device comprises: a bioelectrical impedance measuring unit; and a plurality of sensing portions electrically coupled to the bioelectrical impedance measuring unit When the body of the subject contacts the sensing portions, the bioelectrical impedance measuring unit acquires the bioelectrical impedance of the subject. The bioelectrical impedance analysis apparatus according to claim 5, wherein the bioelectrical impedance sensing device is a portable device or a wearable device. The bioelectrical impedance analysis instrument according to claim 1, wherein the bioelectrical impedance analysis instrument is one of a vertical device, a portable device, and a wearable device. The bioelectrical impedance analysis instrument of claim 1, wherein the bioelectrical impedance analysis instrument further comprises a communication unit electrically coupled to the processing unit and configured to communicate with an external device. The bioelectrical impedance analysis instrument according to claim 1, wherein the bioelectrical impedance analysis prediction model of the group is a first bioelectrical impedance analysis prediction model, and the storage unit further stores a plurality of bioelectrical impedance analysis prediction models. The bioelectrical impedance analysis prediction model includes the first bioelectrical impedance analysis prediction model and a second bioelectrical impedance analysis prediction model of another group, the processing unit enabling the bioelectrical impedance analysis according to the subject's personal data. A bioelectrical impedance analysis prediction model selected by one of the prediction models, wherein when the selected bioelectrical impedance analysis prediction model is enabled, the processing unit converts the bioelectrical impedance of the subject through the selected bioelectrical impedance analysis prediction model, The estimated body composition data of the subject is calculated according to the converted bioelectrical impedance of the subject.