A multi-probe precise collection body fat parameter wearable device and calculation method

Abstract

The application discloses a kind of multi-probe point precise collection body fat parameter wearable device and algorithm, specifically related to body fat collection technical field, for solving the error and inaccuracy of body fat impedance parameter measured by the instability of existing measuring equipment and the physiological activity of tester;Including data processing module and the data acquisition module, test judging module, characteristic algorithm module, signal generation module and body fat adjusting module that are signal connected with data processing module;It is by obtaining equipment influence information and tester influence information to calculate body fat correction coefficient, according to the correction signal issued by wearable device, according to body fat correction coefficient, body fat rate is adjusted, inaccurate body fat rate measurement result caused by error or other factors can be avoided, more accurate body fat rate can be obtained, improve the accuracy and reliability of measurement.

Description

Technical Field

[0001] This invention relates to the field of body fat collection technology, and more specifically, to a wearable device and calculation method for accurately collecting body fat parameters at multiple points. Background Technology

[0002] Body fat measurement is a method of assessing physical health and body composition by measuring the amount of fat in the body. Body fat percentage refers to the percentage of fat tissue in the total body weight, and it is an important indicator for assessing obesity and body composition.

[0003] However, when measuring body fat in multiple parts of the body, the instability of the measuring equipment and the physiological activities of the test subject can cause errors and inaccuracies in the measured body fat impedance parameters, resulting in an insufficiently accurate body fat percentage that cannot properly reflect the test subject's health status.

[0004] To address the aforementioned problems, a technical solution is provided. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a wearable device and calculation method for accurately collecting body fat parameters at multiple probe points to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for calculating body fat parameters using multiple probes for precise acquisition includes the following steps:

[0008] Step S1: Obtain the contact range between each part of the test subject and the sensor of the body fat detector, and the pressure of the sensor of the body fat detector on each part of the test subject. Set the contact range threshold and the optimal pressure threshold. Compare the contact range between each part of the test subject and the sensor of the body fat detector with the contact range threshold. Compare the pressure of the sensor of the body fat detector on each part of the test subject with the optimal pressure threshold to determine whether the measurement conditions are met.

[0009] Step S2: After the measurement conditions are met, obtain the body fat impedance parameters and calculate the body fat percentage using the feature calculation method.

[0010] Step S3: Obtain the equipment influence information and the test subject influence information, and calculate the body fat correction coefficient based on the obtained equipment influence information and test subject influence information;

[0011] Step S4: Set the first threshold, the second threshold, and the third threshold for body fat correction coefficient. When the body fat correction coefficient is less than the first threshold and greater than the third threshold, the wearable device sends a remeasurement signal. When the body fat correction coefficient is greater than or equal to the first threshold and less than the second threshold, or when the body fat correction coefficient is less than or equal to the third threshold and greater than the second threshold, the wearable device sends a correction signal.

[0012] Step S5: When the wearable device sends a correction signal, calculate the corrected body fat percentage based on the body fat percentage and the body fat correction coefficient.

[0013] In a preferred embodiment, in step S1, the contact range between each part of the test subject and the sensor of the body fat detector and the pressure of the sensor of the body fat detector on each part of the test subject are obtained;

[0014] The test subjects' body fat measurements were achieved using a wearable device, which included multiple body fat detectors to sense body fat parameters.

[0015] Set the contact range threshold and the optimal pressure threshold;

[0016] The body fat measurement will only begin when the contact range between each part of the test subject and the sensor of the body fat detector is greater than or equal to the contact range threshold, and the pressure of the body fat detector sensor on each part of the test subject is within the optimal pressure threshold.

[0017] In a preferred embodiment, in step S2, after the measurement conditions are met, the body fat impedance parameters measured by the body fat detector are obtained. The body fat impedance parameters are obtained by measuring the body fat detector, and the body fat percentage is calculated by applying the feature calculation method to the body fat impedance parameters.

[0018] In a preferred embodiment, in step S3, device influence information and tester influence information are obtained;

[0019] Equipment-related information includes sensor offset ratio and skin pressure ratio; tester-related information includes temperature change ratio, body tremor value, and muscle tension.

[0020] The body fat correction coefficient is calculated by normalizing the sensor offset ratio, skin pressure ratio, temperature change ratio, body jitter value, and muscle tension. The expression for this coefficient is: ;

[0021] in, This is the body fat correction factor. As a preset value, These are sensor offset ratio, skin pressure ratio, temperature change ratio, body tremor value, and muscle tension, respectively. These are preset proportional coefficients for sensor offset ratio, skin pressure ratio, temperature change ratio, body tremor value, and muscle tension, respectively. .

[0022] In a preferred embodiment, the temperature change ratio is: Temperature change ratio = (Test subject temperature - Preset temperature + Body temperature increase) / Preset temperature;

[0023] The body tremor value is the standard deviation of the acceleration of the test subject's body tremor, and its expression is: ;

[0024] in, It is the first The acceleration at that moment. It is the average acceleration value of the test subject during the body fat test period. This is the total number of samples. This represents the body shaking value.

[0025] In a preferred embodiment, in step S4, a first threshold, a second threshold, and a third threshold for body fat correction coefficient are set.

[0026] When the body fat correction coefficient is less than the first threshold, the wearable device sends a remeasurement signal; when the body fat correction coefficient is greater than the third threshold, the wearable device sends a remeasurement signal.

[0027] The wearable device sends a correction signal in two cases: when the body fat correction coefficient is greater than or equal to the first threshold and less than the second threshold, and when the body fat correction coefficient is less than or equal to the third threshold and greater than the second threshold.

[0028] In a preferred embodiment, in step S5, after the wearable device sends a correction signal, the body fat percentage is adjusted according to the body fat correction coefficient: ;

[0029] in, The value should not be 0. These are the first threshold, the second threshold, and the third threshold for body fat correction coefficient. Body fat percentage The first adjustment coefficient, This is the second adjustment coefficient; To correct body fat percentage.

[0030] In a preferred embodiment, a wearable device for accurately acquiring body fat parameters at multiple probe points includes a data processing module and a data acquisition module, a test judgment module, a feature calculation module, a signal generation module, and a body fat regulation module that are signal-connected to the data processing module.

[0031] Data acquisition module: The data acquisition module acquires the contact range between each part of the test subject and the sensor of the body fat detector, as well as the pressure of the sensor of the body fat detector on each part of the test subject;

[0032] Data acquisition module: The data acquisition module acquires the body fat impedance parameters measured by the body fat detector;

[0033] The data acquisition module acquires information on the impact of the equipment and the impact of the tester. After the data processing module calculates the body fat correction coefficient based on the information on the impact of the equipment and the impact of the tester, the body fat correction coefficient is obtained.

[0034] Test judgment module: Set contact range threshold, set optimal pressure threshold, and judge whether the measurement conditions are met: When the contact range between each part of the test subject and the sensor of the body fat detector is greater than or equal to the contact range threshold, and the pressure of the sensor of the body fat detector on each part of the test subject is within the optimal pressure threshold, the body fat measurement of the test subject will then begin.

[0035] Feature Calculation Module: The body fat impedance parameters are sent to the feature calculation module, and the body fat percentage is obtained after the feature calculation module performs the calculation.

[0036] Signal generation module: The body fat correction coefficient is sent to the signal generation module. When the body fat correction coefficient is less than the first threshold, the signal generation module sends a remeasurement signal; when the body fat correction coefficient is greater than the third threshold, the signal generation module sends a remeasurement signal; for the two cases where the body fat correction coefficient is greater than or equal to the first threshold and less than the second threshold, and when the body fat correction coefficient is less than or equal to the third threshold and greater than the second threshold, the signal generation module sends a correction signal.

[0037] Body fat regulation module: After the signal generation module sends a correction signal, the body fat regulation module calculates the body fat correction coefficient and body fat percentage through the data processing module to obtain the corrected body fat percentage.

[0038] The technical effects and advantages of the wearable device and calculation method for accurately collecting body fat parameters at multiple probe points according to the present invention are as follows:

[0039] 1. The body fat correction coefficient is calculated through normalization. By setting different thresholds, the wearable device can send remeasurement or correction signals, further ensuring the accuracy of the measurement results. At the same time, after sending the remeasurement signal, the wearable device can also focus on checking the test subject's own physical condition to ensure the stability of the body during the test and protect the health and safety of the test subject.

[0040] 2. By adjusting the body fat percentage based on the correction signal and body fat correction coefficient, calculations are performed separately for two cases: the measured body fat impedance parameter is too small compared to the actual value, and the measured body fat impedance parameter is too large compared to the actual value. The calculated corrected body fat percentage avoids inaccurate body fat percentage measurement results caused by errors or other factors, resulting in a more accurate body fat percentage and improving the accuracy and reliability of the measurement. After obtaining the corrected body fat percentage, the body fat percentage of each part is compared and analyzed according to the healthy body fat percentage range corresponding to each part. Based on the comparison results, more accurate and correct suggestions and warnings are given to the tester through the wearable device. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of a multi-probe point precise acquisition and calculation method for body fat parameters according to the present invention;

[0042] Figure 2 This is a schematic diagram of the structure of a wearable device for accurately collecting body fat parameters at multiple probe points according to the present invention. Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example

[0044] Figure 1 This invention presents a calculation method for accurately collecting body fat parameters at multiple probe points, comprising the following steps:

[0045] Step S1: Obtain the contact range between each part of the test subject and the sensor of the body fat detector, and the pressure of the sensor of the body fat detector on each part of the test subject. Set the contact range threshold and the optimal pressure threshold. Compare the contact range between each part of the test subject and the sensor of the body fat detector with the contact range threshold. Compare the pressure of the sensor of the body fat detector on each part of the test subject with the optimal pressure threshold to determine whether the measurement conditions are met.

[0046] Step S2: After the measurement conditions are met, obtain the body fat impedance parameters and calculate the body fat percentage using the feature calculation method.

[0047] Step S3: Obtain the equipment influence information and the test subject influence information, and calculate the body fat correction coefficient based on the obtained equipment influence information and test subject influence information.

[0048] Step S4: Set the first threshold, the second threshold, and the third threshold for body fat correction coefficient. When the body fat correction coefficient is less than the first threshold and greater than the third threshold, the wearable device sends a remeasurement signal. When the body fat correction coefficient is greater than or equal to the first threshold and less than the second threshold, or when the body fat correction coefficient is less than or equal to the third threshold and greater than the second threshold, the wearable device sends a correction signal.

[0049] Step S5: When the wearable device sends a correction signal, calculate the corrected body fat percentage based on the body fat percentage and the body fat correction coefficient.

[0050] In step S1, the contact range between each part of the test subject and the sensor of the body fat detector, and the pressure of the body fat detector sensor on each part of the test subject are obtained. This means that body fat is measured at multiple points using the body fat detector at each part. It is determined whether the contact range of each part is greater than the set contact range threshold, and whether the pressure of each part is within the set optimal pressure threshold. When the contact range and pressure of all parts meet the requirements, body fat measurement of the test subject can begin. The specific details are as follows:

[0051] The test subject's body fat measurement is based on a wearable device, which includes multiple body fat detectors to sense body fat parameters. These are worn on the limbs and neck, meaning the wearable device is worn on multiple parts of the body.

[0052] A body fat detector is an electronic device that calculates a person's body fat percentage by measuring the body's bioelectrical impedance. This device typically uses a dual-frequency current (50 kHz and 500 kHz) to pass through the body's tissues and then measures the impedance encountered as it passes through the tissues.

[0053] The body fat detector is used to measure multiple parts of the test subject's body, including but not limited to the neck and limbs. The body fat impedance parameters measured at each part are different.

[0054] The contact range between each part of the test subject and the sensor of the body fat detector, as well as the pressure of the body fat detector sensor on each part of the test subject, are obtained.

[0055] Set a contact range threshold. When the contact range between each part of the test subject and the sensor of the body fat detector is less than the contact range threshold, the body fat detection needs to be adjusted to ensure that the sensor of the body fat detector makes full contact with each part of the test subject.

[0056] An optimal pressure threshold is set. If the pressure applied by the body fat detector's sensor to each part of the test subject deviates from the optimal threshold, the measurement of body fat will be inaccurate. Excessive pressure may compress tissue, reducing local blood flow and affecting the measurement results. Conversely, insufficient pressure may prevent the sensor from making proper or tight contact with the skin, also affecting the accuracy of the measurement.

[0057] Determining if the measurement conditions are met: Body fat measurement of the test subject will only begin when the contact range between each part of the test subject and the sensor of the body fat detector is greater than or equal to the contact range threshold, and the pressure of the body fat detector sensor on each part of the test subject is within the optimal pressure threshold.

[0058] The sensor is a device on the body fat detector that comes into direct contact with the skin, and it measures body fat impedance parameters.

[0059] Pressure sensors and other sensors are used to detect the contact between the body fat detector's sensor and the test subject's body surface, thereby determining the contact range; pressure sensors or force sensors are used to measure the pressure exerted by the body fat detector's sensor on each part of the test subject.

[0060] In step S2, after the measurement conditions are met, the body fat impedance parameters measured by the body fat detector are obtained. The body fat percentage is calculated using the feature calculation method based on the body fat impedance parameters. The measurement process of the body fat percentage measured by the body fat detector is described below:

[0061] Body fat impedance parameters are obtained by measuring body fat detectors. These parameters are then applied using a feature calculation method to calculate body fat percentage.

[0062] Feature calculus is one of the commonly used methods in the field of body fat percentage measurement, and its technology is relatively mature. The basic idea of ​​feature calculus is to establish a mathematical model based on body fat percentage data of a large population, and to obtain the test subject's information, including characteristic parameters such as age, height, weight, and gender, and to calculate the test subject's body fat percentage; the methods used include, but are not limited to, the capsule method; this invention will not elaborate on feature calculus methods.

[0063] In step S3, the device impact information and the tester impact information are obtained.

[0064] Equipment-related information includes sensor offset ratio and skin pressure ratio, while tester-related information includes temperature change ratio, body tremor value, and muscle tension.

[0065] The sensor offset ratio is the ratio of the maximum offset distance between the sensor and the preset position to the allowable offset distance during body fat measurement. The larger the sensor offset ratio, the smaller the contact area between the sensor and the skin at the preset position. The measured body fat impedance parameter will usually be larger. This is because the reduced contact area between the skin at the preset position and the sensor will lead to a longer path length for the current, thereby increasing the resistance and making the measured impedance parameter larger.

[0066] Among them, the maximum distance of sensor offset from preset position refers to the maximum distance the sensor deviates from the preset position during body fat measurement; the preset position is the preset position where the sensor contacts the skin during body fat measurement; the allowable offset distance refers to the maximum offset distance that the sensor can be allowed during body fat measurement without significantly affecting the measurement accuracy. The size of the allowable offset distance is set according to the actual situation.

[0067] The maximum distance offset between the sensor and the preset position can be measured using the following methods:

[0068] A marker point or line is pre-set on the sensor to indicate the preset position where the sensor contacts the skin; during body fat measurement, the position of the sensor when it contacts the skin is recorded; by measuring the distance between the recorded sensor position and the preset position, the maximum distance of the sensor's offset from the preset position is calculated.

[0069] The skin pressure ratio is the ratio of the pressure exerted by the sensor on the skin at a preset location to the safe pressure. During measurement, the pressure between the sensor and the skin varies depending on the measurement operation and posture. However, if the tester exerts excessive force or uses an incorrect posture, the pressure between the sensor and the skin may be too high, which could affect the measurement results. The greater the pressure between the sensor and the skin at the preset location, the smaller the measured body fat impedance parameter will be compared to the actual value. This is because a higher pressure between the skin and the sensor at the preset location compresses the skin tissue, reduces the gap, shortens the path of current through the skin, and thus reduces resistance, resulting in a smaller measured body fat impedance parameter.

[0070] The safe pressure is the maximum allowable pressure between the sensor and the skin at the preset location during the measurement process. The safe pressure setting is determined based on factors such as the size and model of the body fat detector.

[0071] Sensors such as pressure sensors or force sensors are used to measure the pressure of the body fat detector on the skin at a preset location.

[0072] Temperature Change Ratio: The temperature measured in the temperature change ratio refers to the temperature of the skin surface at the point of contact between the test subject and the body fat detector. Temperature Change Ratio = (Test Subject Temperature - Preset Temperature + Temperature Increase) / Preset Temperature. The temperature increase refers to the difference between the temperature at the end of the test and the temperature at the beginning of the test. If the temperature increases, the temperature increase is positive; if the temperature decreases, the temperature increase is negative. The test subject temperature refers to the temperature at the beginning of the test. The preset temperature is the normal human body temperature, and its specific setting depends on factors such as the test subject's age and gender, which will not be elaborated here. A higher temperature change ratio will result in a lower measured body fat impedance parameter than the actual body fat impedance parameter. This is because increased temperature leads to a decrease in the resistance of body tissues, resulting in a lower measured body fat impedance parameter.

[0073] Body tremor value: The body tremor value is the standard deviation of the acceleration of the test subject's body tremors. The standard deviation of acceleration refers to the degree of change of acceleration over a period of time, and can be calculated using the following formula: .

[0074] in, It is the first The acceleration at that moment. It is the average acceleration value of the test subject during the body fat test period. This is the total number of samples. This represents the body shaking value.

[0075] The greater the body shaking value, the larger the measured body fat impedance parameter will be compared with the actual value. This is because body shaking causes unstable contact between the test subject and the body fat measuring device, which affects the path of the measured current through the body and the corresponding resistance value calculation. The standard deviation of acceleration can reflect the degree of body shaking. Therefore, when the body shaking value is greater, the standard deviation of acceleration will also increase accordingly, resulting in a larger measured body fat impedance parameter.

[0076] Common tools for measuring acceleration include accelerometers and gyroscopes, which are worn on the body of the test subject.

[0077] Muscle tension: When muscle tension increases, electrical currents in the body will pass more easily through muscle tissue, thus reducing the amount of current passing through adipose tissue; this will result in a lower measured body fat impedance parameter.

[0078] The magnitude of muscle tension can be measured using electromyography (EMG). EMG is a method for measuring the electrical activity of muscles. By measuring the weak electrical signals generated by the muscles, it determines the degree of muscle contraction and the magnitude of muscle tension. EMG typically uses electrodes attached to the skin to record electrical activity signals, which are then amplified, processed, and analyzed to obtain relevant data on muscle activity.

[0079] Electromyography (EMG) data can be used to represent muscle tension in several ways, commonly including the amplitude and frequency of the EMG signal. The amplitude of the EMG signal is usually expressed as the average amplitude of the signal per unit time, while the frequency of the EMG signal refers to the rate of change of electrical potential within the signal.

[0080] In this invention, muscle tension is represented by the amplitude of electromyographic (EMG) signals. The amplitude of EMG signals refers to the intensity of muscle electrical activity. During static muscle contraction, the amplitude of EMG signals is positively correlated with muscle tension, that is, the amplitude of EMG signals increases with the increase of muscle tension. Static muscles refer to the use of muscles in a static state, such as maintaining body posture or supporting heavy objects. In this case, the muscles need to exert continuous force to maintain the static state, which is called static contraction.

[0081] The body fat correction coefficient is calculated by normalizing the sensor offset ratio, skin pressure ratio, temperature change ratio, body jitter value, and muscle tension. The expression for this coefficient is: .

[0082] in, This is the body fat correction factor. As a preset value, These are sensor offset ratio, skin pressure ratio, temperature change ratio, body tremor value, and muscle tension, respectively. These are preset proportional coefficients for sensor offset ratio, skin pressure ratio, temperature change ratio, body tremor value, and muscle tension, respectively. .

[0083] In step S4, a first threshold, a second threshold, and a third threshold for body fat correction coefficient are set. The first threshold is less than the second threshold, and the second threshold is less than the third threshold. When the body fat correction coefficient is greater than the second threshold, it indicates that the measured body fat impedance parameter is larger than the actual value. When the body fat correction coefficient is less than the second threshold, it indicates that the measured body fat impedance parameter is smaller than the actual value.

[0084] When the body fat correction coefficient is less than the first threshold, the measured body fat impedance parameter is significantly smaller than the actual value, and the wearable device sends a remeasurement signal. When the body fat correction coefficient is greater than the third threshold, the measured body fat impedance parameter is significantly larger than the actual value, and the wearable device sends a remeasurement signal. Based on the remeasurement signal from the wearable device, the professional technicians conducting the body fat measurement inspect the body fat detector. If any problems are found, they are repaired. At the same time, the test subject's physical condition is checked to ensure stability during the test. A second measurement is then scheduled.

[0085] When the body fat correction coefficient is greater than or equal to the first threshold of the body fat correction coefficient, and the body fat correction coefficient is less than the second threshold of the body fat correction coefficient, the measured body fat impedance parameter is smaller than the actual value.

[0086] When the body fat correction coefficient is less than or equal to the third threshold of the body fat correction coefficient, and the body fat correction coefficient is greater than the second threshold of the body fat correction coefficient, the measured body fat impedance parameter is larger than the actual value.

[0087] The wearable device sends a correction signal in two cases: when the body fat correction coefficient is greater than or equal to the first threshold and less than the second threshold, and when the body fat correction coefficient is less than or equal to the third threshold and greater than the second threshold.

[0088] It is worth noting that the preset value is used to adjust the size of the body fat correction coefficient, so that the body fat correction coefficient, the first threshold of the body fat correction coefficient, the second threshold of the body fat correction coefficient, and the third threshold of the body fat correction coefficient are all always positive numbers.

[0089] The body fat correction factor is calculated through normalization. By setting different thresholds, the wearable device can send remeasurement or correction signals, further ensuring the accuracy of the measurement results. Simultaneously, after sending a remeasurement signal, the wearable device can also monitor the test subject's physical condition to ensure stability during the test and protect the test subject's health and safety.

[0090] In step S5, the body fat percentage is adjusted according to the correction signal emitted by the wearable device and the body fat correction coefficient to obtain a more accurate body fat percentage.

[0091] For the two cases where the body fat correction coefficient is greater than or equal to the first threshold and less than the second threshold, and where the body fat correction coefficient is less than or equal to the third threshold and greater than the second threshold, the body fat percentage is adjusted according to the body fat correction coefficient: .

[0092] in, The value should not be 0. These are the first threshold, the second threshold, and the third threshold for body fat correction coefficient. Body fat percentage The first adjustment coefficient, This is the second adjustment coefficient; To correct body fat percentage.

[0093] By adjusting the body fat percentage based on the correction signal and body fat correction coefficient, and calculating the corrected body fat percentage for two cases—one where the measured body fat impedance parameter is too small compared to the actual value and the other where it is too large compared to the actual value—inaccurate body fat percentage measurements due to errors or other factors can be avoided, resulting in a more accurate body fat percentage and improving the accuracy and reliability of the measurement.

[0094] After obtaining the corrected body fat percentage, the body fat percentage of each part is compared and analyzed according to the healthy range of body fat percentage corresponding to each part. Based on the comparison results, suggestions and warnings are given to the tester through a wearable device.

[0095] Different body parts correspond to different healthy body fat percentage ranges. Below are some common body parts and their corresponding healthy body fat percentage ranges:

[0096] Overall body fat percentage: Men generally have a range of 6%–24%, and women generally have a range of 16%–30%, but this should be adjusted according to factors such as age and body type.

[0097] Abdominal body fat percentage: Generally between 6% and 12% for men and between 16% and 22% for women, but should be adjusted according to factors such as age and body type.

[0098] Body fat percentage in the buttocks: Generally between 9% and 21% for men and between 19% and 28% for women, but this should be adjusted according to factors such as age and body type.

[0099] Thigh body fat percentage: Men generally have 15%-25% and women generally have 20%-30%, but this should be adjusted according to factors such as age and body type.

[0100] Calf fat percentage: Men generally have 12%-20% and women generally have 18%-28%, but this should be adjusted according to factors such as age and body type. Example

[0101] The difference between Embodiment 2 and Embodiment 1 is that this embodiment introduces a wearable device for accurately collecting body fat parameters at multiple probe points.

[0102] Figure 2 A schematic diagram of the structure of a wearable device for accurately collecting body fat parameters at multiple probe points is provided. The wearable device for accurately collecting body fat parameters at multiple probe points includes a data processing module and a data acquisition module, a test judgment module, a feature calculation module, a signal generation module and a body fat regulation module that are signal-connected to the data processing module.

[0103] Data acquisition module: The data acquisition module acquires the contact range between each part of the test subject and the sensor of the body fat detector, as well as the pressure of the sensor of the body fat detector on each part of the test subject;

[0104] Data acquisition module: The data acquisition module acquires the body fat impedance parameters measured by the body fat detector;

[0105] The data acquisition module acquires information on the impact of the equipment and the impact of the test subject. After the data processing module calculates the body fat correction coefficient, the information on the impact of the equipment and the impact of the test subject is used.

[0106] Test judgment module: Set contact range threshold, set optimal pressure threshold, and judge whether the measurement conditions are met: compare the contact range between each part of the test subject and the sensor of the body fat detector with the contact range threshold, and compare the pressure of the body fat detector sensor on each part of the test subject with the optimal pressure threshold. When the contact range between each part of the test subject and the sensor of the body fat detector is greater than or equal to the contact range threshold, and the pressure of the body fat detector sensor on each part of the test subject is within the optimal pressure threshold, the body fat measurement of the test subject will then begin.

[0107] Feature Calculation Module: The body fat impedance parameters are sent to the feature calculation module, and the body fat percentage is obtained after the feature calculation module performs the calculation.

[0108] Signal generation module: The body fat correction coefficient is sent to the signal generation module. When the body fat correction coefficient is less than the first threshold, the signal generation module sends a remeasurement signal; when the body fat correction coefficient is greater than the third threshold, the signal generation module sends a remeasurement signal; for the two cases where the body fat correction coefficient is greater than or equal to the first threshold and less than the second threshold, and when the body fat correction coefficient is less than or equal to the third threshold and greater than the second threshold, the signal generation module sends a correction signal.

[0109] Body fat regulation module: After the signal generation module sends a correction signal, the body fat regulation module calculates the body fat correction coefficient and body fat percentage through the data processing module to obtain the corrected body fat percentage.

[0110] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0111] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0112] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0113] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described device and module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0114] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or modules may be electrical, mechanical, or other forms.

[0115] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0116] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0117] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0118] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0119] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, 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 calculating body fat parameters with multi-probe precision acquisition, characterized in that, The method comprises the following steps: Step S1: obtaining the contact range of each part of the tester with the sensor of the body fat detector and the pressure of the sensor of the body fat detector on each part of the tester, setting a contact range threshold, setting a pressure optimal threshold, comparing the contact range of each part of the tester with the sensor of the body fat detector with the contact range threshold, comparing the pressure of the sensor of the body fat detector on each part of the tester with the pressure optimal threshold, and judging whether the measurement condition is reached; Step S2: after the measurement condition is reached, obtaining the body fat impedance parameter, and calculating the body fat rate by the characteristic calculation method; Step S3: obtaining the device influence information and the tester influence information, and calculating the body fat correction coefficient according to the obtained device influence information and the tester influence information; In step S3, the device influence information and the tester influence information are obtained. The device influence information includes the sensor offset ratio and the skin pressure ratio, and the tester influence information includes the temperature change ratio, the body jitter value and the muscle tension; The inductor offset ratio, skin pressure ratio, temperature change ratio, body shaking value and muscle tension are normalized to calculate a body fat correction coefficient, and the expression is: ; wherein, is a body fat correction coefficient, is a preset value, respectively are a sensor offset ratio, a skin pressure ratio, a temperature change ratio, a body jitter value, and a muscle tension; respectively are preset ratio coefficients of the sensor offset ratio, the skin pressure ratio, the temperature change ratio, the body jitter value, and the muscle tension, and ; Step S4: setting a body fat correction coefficient first threshold, a body fat correction coefficient second threshold and a body fat correction coefficient third threshold, when the body fat correction coefficient is less than the body fat correction coefficient first threshold or greater than the body fat correction coefficient third threshold, the wearable device sends a re-measurement signal; when the body fat correction coefficient is greater than or equal to the body fat correction coefficient first threshold and less than the body fat correction coefficient second threshold, or when the body fat correction coefficient is less than or equal to the body fat correction coefficient third threshold and greater than the body fat correction coefficient second threshold, the wearable device sends a correction signal; Step S5: when the wearable device sends a correction signal, the corrected body fat rate is calculated according to the body fat rate and the body fat correction coefficient.

2. The method of claim 1, wherein the method further comprises: calculating a body fat parameter using the plurality of body fat parameters. In step S1, the contact range of each part of the tester with the sensor of the body fat detector and the pressure of the sensor of the body fat detector on each part of the tester are obtained. The body fat measurement of the tester is realized based on the wearable device, and the wearable device comprises a plurality of body fat detectors to sense the body fat parameter. The contact range threshold is set, and the pressure optimal threshold is set. Until the contact range of each part of the tester with the sensor of the body fat detector is greater than or equal to the contact range threshold, and the pressure of the sensor of the body fat detector on each part of the tester is within the pressure optimal threshold, the measurement condition is reached, and the body fat measurement of the tester is started again.

3. The method of claim 2, wherein the method further comprises: determining a plurality of body fat parameters based on the plurality of body fat parameters determined for each of the plurality of points. In step S2, after the measurement condition is reached, the body fat impedance parameter measured by the body fat detector is obtained, the body fat impedance parameter is calculated by the characteristic calculation method, and the body fat rate is calculated by the characteristic calculation method.

4. The method of claim 1, wherein the method further comprises: calculating a body fat parameter using the plurality of body fat parameters. The temperature change ratio is: temperature change ratio = (tester temperature - preset temperature + body temperature increase number) / preset temperature. The body tremor value is the standard deviation of the acceleration of the tester's body tremor, and its expression is: ; wherein, is the acceleration at the time, is the average of the acceleration values of the tester during the time of the body fat test, is the total number of samples, is the body jiggle value.

5. The calculation method for multi-point precise acquisition of body fat parameters according to claim 1, characterized in that: In step S5, after the wearing device sends out the correction signal, the body fat rate is adjusted according to the body fat correction coefficient: ; wherein, is not equal to 0, are respectively a first threshold value of a body fat correction coefficient, a second threshold value of a body fat correction coefficient and a third threshold value of a body fat correction coefficient, is a body fat rate, is a first adjustment coefficient, is a second adjustment coefficient; is a corrected body fat rate.

6. A wearable device for multi-probe precise acquisition of body fat parameters, for implementing the calculation method of any one of claims 1-5, characterized in that it comprises: The data processing module, the data acquisition module, the test judgment module, the characteristic calculation module, the signal generation module and the body fat adjustment module are signal connected with the data processing module. The data acquisition module obtains the contact range of each part of the tester with the sensor of the body fat detector and the pressure of the sensor of the body fat detector on each part of the tester. Data acquisition module: the data acquisition module acquires the body fat impedance parameter measured by the body fat detector; The data acquisition module acquires the device influence information and the tester influence information, and obtains the body fat correction coefficient through the calculation of the data processing module after the device influence information and the tester influence information; Test judgment module: set the contact range threshold, set the pressure optimal threshold, judge whether the measurement condition is reached: when the contact range of each part of the tester with the sensor of the body fat detector is greater than or equal to the contact range threshold, and the pressure of the sensor of the body fat detector on each part of the tester is within the pressure optimal threshold, the body fat measurement of the tester is started again; Characteristic calculation module: the body fat impedance parameter is sent to the characteristic calculation module, and the body fat rate is obtained through the calculation of the characteristic calculation module; Signal generation module: the body fat correction coefficient is sent to the signal generation module, when the body fat correction coefficient is less than the first threshold of the body fat correction coefficient, the signal generation module sends a re-measurement signal; when the body fat correction coefficient is greater than the third threshold of the body fat correction coefficient, the signal generation module sends a re-measurement signal; for the two cases that the body fat correction coefficient is greater than or equal to the first threshold of the body fat correction coefficient and the body fat correction coefficient is less than the second threshold of the body fat correction coefficient and the body fat correction coefficient is less than or equal to the third threshold of the body fat correction coefficient and the body fat correction coefficient is greater than the second threshold of the body fat correction coefficient, the signal generation module sends a correction signal; Body fat adjustment module: after the signal generation module sends the correction signal, the body fat adjustment module obtains the corrected body fat rate through the calculation of the data processing module on the body fat correction coefficient and the body fat rate.

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