A frequency division multiplexing bioimpedance multi-frequency measurement system and method

Abstract

The present application relates to a kind of frequency division multiplexing biological impedance multi-frequency measurement system and method.The method is aimed at the frequency range of biological tissue impedance change, the problem that excitation signal and response signal are difficult to sample in whole cycle in actual measurement is solved, and the accuracy of biological tissue impedance measurement is improved.Using the OFDM frequency division multiplexing idea minimizes crest factor, uses grouping search algorithm to optimize the phase at each excitation frequency, reduces peak factor, and improves signal-to-noise ratio;And an adaptive dynamic synchronous sampling rate adjustment method combined with window function optimization is proposed, which realizes whole cycle sampling and makes the optimal scheme of Fourier change spectrum resolution to fall in the measurement frequency range, and improves the measurement accuracy.

Description

Technical Field

[0001] The present invention relates to a frequency division multiplexing bioimpedance multi-frequency measurement system and method. Background Art

[0002] There are many types of bioimpedance measurement instruments. Highly integrated chips based on commercial impedance measurement chips such as AD5933 / AD5940, ARF4300 and MAX30002 usually have higher measurement accuracy, wider measurement frequency band and wider impedance measurement range, and are widely used in the market.

[0003] However, most impedance measurements focus on static single-frequency or swept-frequency measurements of biological tissue. Single-frequency measurement methods measure only a single frequency at a time, and most are based on measurements of biological tissue at 50 kHz. Tissue assessment is limited by the single-frequency measurement, resulting in single measurement parameters and limited information. While swept-frequency impedance measurement methods can measure information at multiple frequencies within a given frequency range in a time-sharing manner, they take a long time and lack real-time performance, resulting in the loss of much useful information for dynamic tissue assessment. Specifically, the impedance measurement range of these commercially available chips is less than 150 kHz, failing to meet the 10-250 kHz frequency range required for tissue impedance changes. While commercial bioimpedance measurement chips based on ASIC technology have expanded their measurement bandwidth, their fixed architecture and functionality limit configuration flexibility and applicability, making them incapable of customized impedance measurement for different biological tissues. Therefore, achieving parallel dynamic impedance measurement with multi-frequency excitation is an urgent challenge in bioimpedance measurement.

[0004] Biological tissue impedance measurement usually requires orthogonal or discrete Fourier transform demodulation analysis of the excitation current and the corresponding steady-state response voltage signal. However, due to the difficulty in achieving full-cycle sampling of the excitation signal and the response signal in actual measurement, the spectrum leakage caused by signal truncation will affect the accuracy of biological tissue impedance measurement. Although windowing can convert the truncated non-periodic signal into an approximate periodic signal and reduce the impact of spectrum leakage on the results, it will increase the complexity of measurement data analysis. In addition, because the spectrum calculated by discrete Fourier transform is limited to the spectrum at discrete points, the spectral resolution is limited. That is, the real spectral components contained in the measured signal do not fall exactly on the corresponding spectral lines, which will produce a fence effect that affects the accuracy of biological tissue impedance measurement. Summary of the Invention

[0005] The present invention aims to provide a frequency-division multiplexed bioimpedance multi-frequency measurement system and method. This system minimizes the crest factor by leveraging OFDM frequency-division multiplexing, optimizes the phase at each excitation frequency using a group search algorithm, reduces the crest factor, and improves the signal-to-noise ratio. Furthermore, a method for optimizing the window function with adaptive dynamic synchronous sampling rate adjustment is proposed to achieve an optimal solution for full-cycle sampling and ensuring that the Fourier transform spectrum resolution falls within the measurement frequency range, thereby improving measurement accuracy.

[0006] To achieve the above object, the technical solution of the present invention is: a frequency division multiplexing bioimpedance multi-frequency measurement system, comprising:

[0007] MCU central control unit, which includes:

[0008] A clock module is used to generate a clock signal;

[0009] a signal generator, generating a multi-frequency excitation voltage signal based on a clock signal;

[0010] ADC adaptive sampling module, which performs ADC sampling on the amplified and filtered response voltage signal;

[0011] The MCU digital signal processing module performs DSP processing on the ADC sampled signal to extract the impedance information of the biological tissue;

[0012] Also includes:

[0013] The voltage-controlled constant current source module outputs low-energy multi-frequency excitation current based on the multi-frequency excitation voltage signal;

[0014] The differential amplifier module amplifies and filters the response voltage signal generated by the biological tissue and the reference resistor;

[0015] A power module, used to supply power to the entire device;

[0016] The signal generator generates the excitation waveform based on DDS technology, and at the same time draws on the idea of ​​OFDM orthogonal frequency division multiplexing to minimize the crest factor. It adopts a group search algorithm to optimize the phase at each excitation frequency, reduce the crest factor, and improve the signal-to-noise ratio. It generates a superposition of sinusoidal waves in multiple frequency bands at the same time to achieve the output of multi-frequency excitation voltage signals.

[0017] In one embodiment of the present invention, a Bluetooth module is further included for enabling communication between the MCU central control unit and the mobile terminal.

[0018] The application further provides a frequency division multiplexing bioimpedance multi-frequency measurement method, which is based on the system and adopts a method of adaptive dynamic synchronous sampling rate adjustment combined with window function optimization.

[0019] In an embodiment of the application, the multi-frequency excitation voltage signal is defined as:

[0020]

[0021] Wherein, f m 、 and a m are the frequency, initial phase angle and amplitude of the mth component of the excitation signal respectively, and M is the number of frequency components.

[0022] The peak factor of the wideband excitation signal is defined as the ratio of the signal peak value to the effective mean square value, and is expressed as:

[0023]

[0024] Wherein, u peak , u rmse are the signal peak value and effective mean square value respectively; the peak factor of the signal directly reflects the pros and cons of the signal in the time domain, and the size of the peak factor directly determines the input range of the subsequent input module of the signal; since whether the signal is distorted is determined by the peak value of the signal, if the input range is lower than the peak value of the signal, it will inevitably cause peak clipping distortion, precision loss, and even damage the module; in addition, the peak factor will also affect the signal-to-noise ratio obtained when the wideband excitation signal is measured; the multi-frequency excitation voltage signal maximizes the freedom of amplitude and phase corresponding to each excitation frequency, but there may be problems of system saturation distortion caused by excessive amplitude superposition, or safety hazards caused by excessive current injected into the biological tissue; in order to avoid adverse phenomena of amplitude, the peak factor is used to measure the uniformity of the signal amplitude and limit the maximum root mean square value to meet the safety current limit; since the form of the multi-frequency excitation voltage signal is very similar to the IFFT process in the OFDM system, the idea of minimizing the peak factor of OFDM orthogonal frequency division multiplexing is used to optimize the phase at each excitation frequency by using a grouping search algorithm, to reduce the peak factor and improve the signal-to-noise ratio.

[0025] The size of the peak factor of the multi-frequency excitation voltage signal directly reflects the quality of the multi-frequency excitation voltage signal and its performance in the time domain, and the peak factor of the multi-frequency excitation voltage signal is expressed as:

[0026]

[0027] Wherein, the numerator is the maximum value of the continuous signal u(t) in the range of [0, T], and the denominator is the root mean square value of the signal, i.e. the effective value of the signal.

[0028] In an embodiment of the present application, the adaptive dynamic synchronous sampling rate adjustment method combined with window function optimization is implemented as follows:

[0029] The corresponding discrete signal of formula (1) is:

[0030]

[0031] Wherein, f s is the sampling frequency; n = [0, 1, 2, … N], N is the number of discrete points corresponding to the signal in a period; M is the number of frequency components;

[0032] According to the analysis of the sine response, the corresponding steady-state response signal of U MS (t) in the impedance measurement of the response voltage signal after the current acts on the biological tissue is:

[0033]

[0034] Wherein, b m and ψ m are the amplitude and initial phase angle of the steady-state response signal corresponding to the frequency f m , respectively;

[0035] The corresponding discrete signal of formula (5) is defined as:

[0036]

[0037] Discrete Fourier transform (DFT) is performed on the signals u[n] and y[n], i.e. u MS [n] and y MS [n], respectively, to obtain:

[0038]

[0039]

[0040] Wherein, k is the index of the discrete frequency value in the discrete Fourier transform;

[0041] Substituting (4) into (7) obtains:

[0042]

[0043] Substituting formula (6) into formula (8) obtains:

[0044]

[0045] If the sampling frequency f s , the sampling point number N and each component frequency f m of the multi-frequency excitation voltage signal satisfy

[0046]

[0047] Wherein, f = [f1, f2, ···, f M ], p is one of the sampling point number N, p = [p1, p2, ···, p M ]; then, formula (9) and formula (11) are obtained:

[0048]

[0049] Formula (10) and formula (11) are obtained:

[0050]

[0051] Formula (12) and formula (13) are obtained, and the Ohm's law is obtained:

[0052]

[0053] And are the modulus value and phase of the measured impedance at the frequency f m , respectively.

[0054] Compared with the prior art, the present application has the following beneficial effects: the present application innovatively combines OFDM multi-frequency excitation with biological tissue impedance detection technology, can realize synchronous parallel measurement of biological impedance at different frequencies (1-300 kHz), meets the demand of 10-250 kHz frequency range for biological tissue impedance change, and overcomes the problems of insufficient information in single-frequency measurement, time-consuming in sweep frequency measurement, lack of time-domain dynamic information, loss of many important medical diagnosis information and the like. Further, the grouping search algorithm solves the problem of system saturation distortion and exceeding the safety limit of biological tissue caused by excessive amplitude of multi-frequency signal superposition, realizes crest factor optimization, reduces peak-to-average ratio, and improves signal-to-noise ratio. The adaptive dynamic synchronous sampling rate adjustment combined with the window function optimization method reduces the influence of spectral leakage and fence effect on measurement accuracy, makes the Fourier change spectrum resolution fall within the measurement frequency range, and improves the measurement accuracy. Therefore, the product is suitable for impedance measurement in dynamic scenes, such as body fatigue, body dynamic measurement after exercise training. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 It is a multi-frequency excitation biological tissue impedance steady-state response synchronous measurement block diagram.

[0056] Figure 2 It is a voltage-controlled constant current source schematic diagram.

[0057] Figure 3 It is a group search algorithm.

[0058] Figure 4 This is the schematic diagram of the hardware design of the system of the present invention. DETAILED DESCRIPTION

[0059] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

[0060] The present invention provides a frequency division multiplexing bioimpedance multi-frequency measurement system, comprising:

[0061] MCU central control unit, which includes:

[0062] A clock module is used to generate a clock signal;

[0063] a signal generator, generating a multi-frequency excitation voltage signal based on a clock signal;

[0064] ADC adaptive sampling module, which performs ADC sampling on the amplified and filtered response voltage signal;

[0065] The MCU digital signal processing module performs DSP processing on the ADC sampled signal to extract the impedance information of the biological tissue;

[0066] Also includes:

[0067] The voltage-controlled constant current source module outputs low-energy multi-frequency excitation current based on the multi-frequency excitation voltage signal;

[0068] The differential amplifier module amplifies and filters the response voltage signals generated by the biological tissue and the reference resistor;

[0069] Power module, used to supply power to the entire device;

[0070] The signal generator generates an excitation waveform based on DDS technology, and at the same time draws on the idea of ​​OFDM orthogonal frequency division multiplexing to minimize the crest factor, adopts a group search algorithm to optimize the phase at each excitation frequency, reduces the peak factor, and improves the signal-to-noise ratio.

[0071] It also includes a Bluetooth module for realizing communication between the MCU central control unit and the mobile terminal.

[0072] The present invention also provides a frequency-division multiplexed bioimpedance multi-frequency measurement method. Based on the above-mentioned system, a method of adaptive dynamic synchronous sampling rate adjustment combined with window function optimization is proposed. The MCU digital signal processing module dynamically adjusts the ADC sampling rate of the ADC adaptive sampling module by calculating the frequency of the measurement signal and the spectral resolution of the Fourier transform, achieving the optimal solution of full-cycle sampling and making the Fourier transform spectral resolution fall within the measurement frequency range, thereby improving measurement accuracy.

[0073] The following is a specific implementation process of the present invention.

[0074] The system of the present invention uses MCU as the main control chip. The overall technical solution generates the excitation waveform through on-chip DDS technology. At the same time, DDS draws on the idea of ​​OFDM orthogonal frequency division multiplexing to generate a superposition of sine waves in multiple frequency bands at the same time to realize multi-frequency excitation voltage signals. Then, a low-energy multi-frequency excitation current is output through a voltage-controlled constant current source circuit to act on biological tissue. The response voltage generated by the biological tissue is amplified and filtered by the differential amplifier circuit, and then transmitted to the MCU through AD sampling for DSP processing to extract the impedance information of the biological tissue. The overall hardware design schematic diagram is shown as follows: Figure 4 As shown, it is mainly divided into four parts:

[0075] 1. High-speed signal generation

[0076] The main task is to convert the digital multi-frequency excitation signal into an analog signal through a D / A converter. The built-in DAC of the MCU is used to configure the output of a multi-frequency excitation voltage signal with an amplitude of 0 to 3V and a frequency of 0 to 300kHz. In the OFDM system, after the IFFT operation, all subcarriers are accumulated. Since each subcarrier is modulated by a different independent data symbol, and these sequences can determine the phase of each subcarrier, once the phases of most subcarriers are consistent, the accumulation will result in a large peak signal, resulting in a high peak-to-average ratio. In the design of multi-frequency excitation signals, due to the accumulation of different excitation frequencies, there will also be a problem of a large peak factor. Based on the principle of partial transmission sequence technology commonly used in orthogonal frequency division multiplexing (OFDM) systems, the OFDM frequency division multiplexing idea is used to minimize the crest factor, and a packet search algorithm (such as Figure 3 (as shown) optimizes the phase at each excitation frequency, reduces the peak factor, and improves the signal-to-noise ratio.

[0077] The multi-frequency excitation voltage signal is defined as:

[0078]

[0079] Among them, f m 、 and a m are the frequency, initial phase angle and amplitude corresponding to the mth component contained in the excitation signal respectively;

[0080] The crest factor of a broadband excitation signal is defined as the ratio of the signal peak value to the effective mean square value, expressed as:

[0081]

[0082] Among them, u peak 、u rmse The peak factor of a signal directly reflects the quality of the signal in the time domain, and the size of the peak factor directly determines the input range of the signal's subsequent access module. Since signal distortion is determined by the peak value of the signal, if the input range is lower than the peak value of the signal, it will inevitably cause peak clipping distortion, loss of accuracy, and even damage to the module. In addition, the peak factor will also affect the signal-to-noise ratio obtained when measuring broadband excitation signals. The multi-frequency excitation voltage signal maximizes the freedom of amplitude and phase corresponding to each excitation frequency, but there may be problems such as system saturation distortion caused by excessive amplitude superposition, or excessive current injected into biological tissue, which may pose a safety hazard. To avoid adverse amplitude phenomena, the crest factor is used to measure the uniformity of the signal amplitude and limit its maximum root mean square value to meet the safe current limit. Since the form of the multi-frequency excitation voltage signal is very similar to the IFFT process in the OFDM system, the idea of ​​OFDM orthogonal frequency division multiplexing is borrowed to minimize the crest factor, and a group search algorithm is used to optimize the phase at each excitation frequency to reduce the peak factor and improve the signal-to-noise ratio.

[0083] The size of the peak factor of the multi-frequency excitation voltage signal directly reflects the quality of the multi-frequency excitation voltage signal and its performance in the time domain. The peak factor of the multi-frequency excitation voltage signal is expressed as:

[0084]

[0085] Among them, the numerator is the maximum value of the continuous signal u(t) in the range [0,T], and the denominator is the root mean square value of the signal, that is, the effective value of the signal.

[0086] 2. Constant current source design

[0087] Set the excitation current to 1mA. Design a voltage-controlled constant current source based on a differential amplifier (DDA). The basic single-ended constant current source circuit diagram based on DDA is shown in the figure below. Figure 2 The specific analysis is as follows: First, input signal V i When applied to the X port of DDA, an equal and opposite voltage will be generated at the Y port, that is, the voltage difference between the two sides of the sensitive resistor R3 is -V i Because of the "virtual disconnect" principle of the op amp, the current flowing through R3 is equal to the current flowing through the load R LThe current on.

[0088] like Figure 4 The DDA single-ended voltage-controlled constant current source uses the Analog Devices AD830. To eliminate the DC bias voltage generated by the load, a common-mode feedback circuit is designed. This common-mode feedback is implemented using a non-inverting integrator circuit consisting of an AD8066, a filter network (1MΩ, 1µF), and an integrator network (1MΩ, 1µF). The integration constant is 1s.

[0089] 3. Impedance measurement front end

[0090] like Figure 4 Differential amplifier module. The excitation current flows through the surface electrodes, through the biological tissue, and through a 100Ω reference resistor. The response voltage across the biological tissue and reference resistor is then fed through a DC-blocking capacitor (1µF) and a corresponding T-type resistor network (1MΩ, 1MΩ, 1MΩ) to the AD8066 for follower amplification. Finally, the signal is amplified 5x by a high-speed AD8130 differential amplifier through a proportional resistor (1kΩ, 200Ω) and fed to the MCU's built-in ADC (16-bit, 3.6MSPS) for synchronous acquisition.

[0091] 4. Digital Signal Processing

[0092] In order to avoid the influence of spectrum leakage and fence effect on the calculation, an adaptive dynamic synchronous sampling rate adjustment combined with window function optimization method is proposed in the sampling process. The peak factor definition of multi-frequency broadband excitation signal is the ratio of signal peak value to effective mean square value. The size of the signal peak factor directly reflects the quality of the multi-frequency excitation signal and its performance in time domain, and directly determines whether the signal is distorted and the input range of the subsequent access module. If the input range is lower than the peak value of the signal, it will inevitably cause peak clipping distortion, precision loss, and even damage the module. And the peak factor will also affect the signal-to-noise ratio obtained when measuring the broadband excitation signal. The multi-frequency sinusoidal signal will maximize the freedom of amplitude and phase corresponding to each excitation frequency, and there may be problems such as system saturation distortion caused by excessive amplitude superposition, or safety hazards caused by excessive injected current in biological tissue. In order to avoid adverse phenomena in amplitude, the crest factor is used to measure the uniformity of signal amplitude and limit the maximum root mean square value to meet the safety current limit. By measuring the frequency of the signal and the frequency spectrum resolution of the Fourier transform, the sampling rate of the ADC is dynamically adjusted to make it meet the whole cycle sampling as much as possible, and the frequency spectrum resolution falls within the excitation signal frequency range. In the case of unavoidable spectrum leakage and fence effect, the method of windowing and collecting energy near the frequency point is used to improve the measurement accuracy. On the basis of optimizing the multi-frequency excitation signal, the optimal scheme of whole cycle sampling and making the Fourier transform frequency spectrum resolution fall within the measurement frequency range is realized, and the measurement accuracy is improved. The multi-frequency excitation impedance steady-state response synchronous measurement block diagram is shown in Figure 1 The product is used in the following process or way: first, place a special medical electrode patch in the biological tissue area to be measured, connect the electrode patch with the detector (i.e. the system of the present application), and connect the detector with the self-developed APP through Bluetooth. The generation of multi-frequency excitation signal and related multi-frequency measurement parameters are set through the APP, and then the APP sends the set data to the detector through Bluetooth. After receiving the data instruction, the mobile phone calculates the impedance through digital signal processing, and the MCU can collect data in real time and send it to the APP to display the measurement results of biological impedance in real time.

[0093] The adaptive dynamic synchronous sampling rate adjustment combined with window function optimization method is implemented as follows:

[0094] The discrete signal corresponding to formula (1) is:

[0095]

[0096] Where, f s is the sampling frequency; n = [0, 1, 2, … N], N is the number of discrete points corresponding to the signal in a period; M is the number of frequency components;

[0097] According to the sine response analysis, U MS(t) The steady-state response signal corresponding to the response voltage signal after the current acts on the biological tissue in the impedance measurement is:

[0098]

[0099] Among them, b m and ψ m They are the steady-state response signals at frequency f m The corresponding amplitude and initial phase angle;

[0100] The discrete signal corresponding to formula (5) is defined as:

[0101]

[0102] For the signal u[n], that is, u MS [n] and y[n] means y MS [n] Perform discrete Fourier transform DFT respectively to get:

[0103]

[0104]

[0105] Where k is the index of the discrete frequency value in the discrete Fourier transform;

[0106] Substituting (4) into (7) we get:

[0107]

[0108] Substituting formula (6) into formula (8) yields:

[0109]

[0110] If the sampling frequency f s , the number of sampling points N and the frequency f of each component contained in the multi-frequency excitation voltage signal m satisfy

[0111]

[0112] Where, f=[f1,f2,···,f M ], p is a point in the number of sampling points N, p=[p1, p2, ···, p M ]; then, combining equations (9) and (11), we can get:

[0113]

[0114] Combining equations (10) and (11), we can get:

[0115]

[0116] From Ohm's law, by combining equation (12) and equation (13), we have:

[0117]

[0118] and are the modulus and phase of the measured impedance at frequency f m respectively.

[0119] The above is the preferred embodiment of the present application, any changes made in accordance with the technical solutions of the present application, the resulting functional effects do not exceed the scope of the technical solutions of the present application, all belong to the protection scope of the present application.

Claims

1. A frequency division multiplexing bioimpedance multi-frequency measurement method, characterized in that: The method includes the steps of adaptive dynamic synchronous sampling rate adjustment combined with window function optimization. The MCU digital signal processing module dynamically adjusts the ADC sampling rate of the ADC adaptive sampling module by calculating the frequency of the measurement signal and the spectrum resolution of the Fourier transform, so that the ADC sampling rate is as close to full-cycle sampling as possible and the spectrum resolution falls within the frequency range of the multi-frequency excitation voltage signal. Based on the optimization of the multi-frequency excitation voltage signal, the optimal solution for full-cycle sampling and making the Fourier transform spectrum resolution fall within the measurement frequency range is achieved, thereby improving measurement accuracy. The multi-frequency excitation voltage signal is defined as: Among them, f m 、 and a m are the frequency, initial phase angle and amplitude corresponding to the mth component contained in the excitation signal, and M is the number of frequency components; The crest factor of a broadband excitation signal is defined as the ratio of the signal peak value to the effective mean square value, expressed as: Among them, u peak 、u rmse The peak factor of a signal directly reflects the quality of the signal in the time domain, and the size of the peak factor directly determines the input range of the signal's subsequent access module. Since signal distortion is determined by the peak value of the signal, if the input range is lower than the peak value of the signal, it will inevitably cause peak clipping distortion, loss of accuracy, and even damage to the module. In addition, the peak factor will also affect the signal-to-noise ratio obtained when measuring broadband excitation signals. The multi-frequency excitation voltage signal maximizes the freedom of amplitude and phase corresponding to each excitation frequency, but there may also be problems such as system saturation distortion caused by excessive amplitude superposition, or excessive current injected into biological tissue, which may pose a safety hazard. To avoid adverse amplitude phenomena, the crest factor is used to measure the uniformity of the signal amplitude and limit its maximum root mean square value to meet the safe current limit. Since the form of the multi-frequency excitation voltage signal is very similar to the IFFT process in the OFDM system, the idea of ​​OFDM orthogonal frequency division multiplexing is borrowed to minimize the crest factor, and a group search algorithm is used to optimize the phase at each excitation frequency to reduce the peak factor and improve the signal-to-noise ratio. The peak factor of the multi-frequency excitation voltage signal directly reflects the quality of the multi-frequency excitation voltage signal and its performance in the time domain. The peak factor of the multi-frequency excitation voltage signal is expressed as: Among them, the numerator is the maximum value of the continuous signal u(t) in the range [0,T], and the denominator is the root mean square value of the signal, that is, the effective value of the signal; The specific implementation process of the step of adaptive dynamic synchronous sampling rate adjustment combined with window function optimization is as follows: The discrete signal corresponding to formula (1) is: Among them, f s is the sampling frequency; n=[0,1,2,…N], N is the number of discrete points corresponding to the signal in one cycle; M is the number of frequency components; From the sinusoidal response analysis, we know that U MS (t) The steady-state response signal corresponding to the response voltage signal after the current acts on the biological tissue in the impedance measurement is: Among them, b m and ψ m They are the steady-state response signals at frequency f m The corresponding amplitude and initial phase angle; The discrete signal corresponding to formula (5) is defined as: For the signal u[n], that is, u MS [n] and y[n] means y MS [n] Perform discrete Fourier transform DFT respectively to get: Where k is the index of the discrete frequency value in the discrete Fourier transform; Substituting (4) into (7) we get: Substituting formula (6) into formula (8) yields: If the sampling frequency f s , the number of sampling points N and the frequency f of each component contained in the multi-frequency excitation voltage signal m satisfy Where, f=[f1,f2,···,f M ], p is a point in the number of sampling points N, p=[p1, p2, ···, p M ]; Then, combining equations (9) and (11), we can get: Combining equations (10) and (11), we can get: Combining equations (12) and (13), we can obtain from Ohm's law: and The impedance is measured at frequency f m The corresponding magnitude and phase.

2. A frequency division multiplexing bioimpedance multi-frequency measurement system, using the frequency division multiplexing bioimpedance multi-frequency measurement method according to claim 1, characterized in that: include: MCU central control unit, which includes: A clock module is used to generate a clock signal; a signal generator, generating a multi-frequency excitation voltage signal based on a clock signal; ADC adaptive sampling module, which performs ADC sampling on the amplified and filtered response voltage signal; The MCU digital signal processing module performs DSP processing on the ADC sampled signal to extract the impedance information of the biological tissue; Also includes: The voltage-controlled constant current source module outputs low-energy multi-frequency excitation current based on the multi-frequency excitation voltage signal; The differential amplifier module amplifies and filters the response voltage signals generated by the biological tissue and the reference resistor; Power module, used to supply power to the entire device; The signal generator generates an excitation waveform based on DDS technology, and at the same time draws on the idea of ​​OFDM orthogonal frequency division multiplexing to minimize the crest factor, adopts a group search algorithm to optimize the phase at each excitation frequency, reduces the peak factor, and improves the signal-to-noise ratio.

3. The frequency division multiplexing bioimpedance multi-frequency measurement system according to claim 2, characterized in that: It also includes a Bluetooth module for realizing communication between the MCU central control unit and the mobile terminal.

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