WO2020237652A1 - 一种用于提取生物组织特征信息的非侵入性方法及其系统 - Google Patents

一种用于提取生物组织特征信息的非侵入性方法及其系统 Download PDF

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Publication number
WO2020237652A1
WO2020237652A1 PCT/CN2019/089603 CN2019089603W WO2020237652A1 WO 2020237652 A1 WO2020237652 A1 WO 2020237652A1 CN 2019089603 W CN2019089603 W CN 2019089603W WO 2020237652 A1 WO2020237652 A1 WO 2020237652A1
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signal
capacitance
resistance
tissue
signals
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PCT/CN2019/089603
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English (en)
French (fr)
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易成
王翎
何碧霞
谢鹏
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麦层移动健康管理有限公司
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Priority to PCT/CN2019/089603 priority Critical patent/WO2020237652A1/zh
Publication of WO2020237652A1 publication Critical patent/WO2020237652A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons

Definitions

  • the invention relates to a non-invasive method and system for extracting tissue characteristic information in the body.
  • Bioimpedance and bioreactor measurements have been widely explored as a non-invasive method to measure blood flow and body fluid levels. These techniques are widely accepted in the medical field. But they have some drawbacks. First, all calculated parameters are based on impedance, which is related to frequency. These parameters can only indirectly indicate the cardiovascular status. Moreover, since these parameters are frequency dependent, they will suffer from frequency selective impairments. Secondly, the impedance of the connected tissue plays an important role in impedance measurement. Traditional bioimpedance and bioreactor measurement are affected by the mixture of surrounding tissue impedance and target tissue impedance. Sometimes it is difficult to determine which impedance is dominant. Therefore, the mixed impedance varies from person to person; even if it is the same person, the mixed impedance will be different due to different organizational states. Therefore, bioimpedance and reactance are not good candidates for characterizing body fluids and cardiovascular circulation.
  • Electrodes are characterized by conductors and non-conductors. Conductor is measured by conductivity (resistance reverse), and non-conductor can be measured by capacitance or dielectric constant.
  • a widely recognized human tissue model is the Cole model. Basically, AC current is mainly conducted by extracellular liquid, and extracellular liquid is mainly low-frequency resistance, such as 1KHz. As the frequency of the alternating current increases, the alternating current passes through the extracellular fluid and cells. Since the cell has a membrane that functions similarly to a capacitor, the alternating current will have a phase change. As the frequency continues to increase, beyond 1MHz, the membrane effect of the cell in the total impedance becomes negligible, and the total impedance becomes pure resistance again. The Cole model describes this behavior.
  • any change in biological tissue will basically lead to changes in its conductance and capacitance. Therefore, in order to show tissue changes, the measurement of tissue conductance and capacitance changes is more reliable than the measurement of bioimpedance mixed bioreactor, which includes the impedance and reactance of the connected tissue. Since the conductance and capacitance of the tissue are frequency dependent, the range of the frequency band must be selected. It is generally believed that the information of the organization is mainly in the frequency band of 10KHz to 1MHz. Therefore, in order to measure the conductance and capacitance of the tissue, a multi-frequency alternating excitation (current) in the 10KHz to 1MHz frequency band is used. According to Ohm's law, the conductance and capacitance of tissues can be calculated from multi-frequency alternating currents.
  • the present invention proposes a non-invasive method for detecting the electrical characteristics of biological tissues. Its purpose is to capture changes in body fluids, blood flow and cardiovascular circulation to achieve accurate detection of target tissue feature information , And further know the status of the human body or organism.
  • the method is mainly used for information detection for non-treatment purposes.
  • the present invention provides a non-invasive method and system for detecting tissue characteristic information in the body and capturing changes in body fluids, blood flow and/or cardiovascular circulation.
  • the method includes:
  • the generated multiple AC currents are transmitted to the human body or animal body to generate multiple AC voltage signals, wherein the amplitude and phase of the multiple AC currents are programmable; preferably, the programming of the amplitude and phase is based on transmission and reception
  • the system's nonlinearity and environmental noise are adjusted to achieve the best measurement results at the receiving end.
  • Receiving the AC voltage signal modulated by the tissue changes in the human body or animal to obtain a modulated signal, and the tissue includes a target tissue and a peripheral tissue;
  • Preprocessing the digital signal further includes demodulating and filtering the digital signal to obtain a frequency domain digital signal;
  • the generating multiple alternating currents with different frequencies includes simultaneously generating multiple alternating currents with different frequencies from the frequency domain to the time domain using digital signal processing technology, wherein the multiple alternating currents with different frequencies It is periodic, and the digital signal processing technology includes Orthogonal Frequency Division Multiplexing (OFDM) technology.
  • OFDM Orthogonal Frequency Division Multiplexing
  • the transmitting the generated multiple alternating currents to the human body or animal body to generate multiple alternating voltage signals includes adjusting the amplitude and phase of the alternating current according to the nonlinear distortion of the system and environmental noise.
  • the adjusting the amplitude and phase of the alternating current includes presetting the amplitude and phase of the alternating current as anti-distortion, so as to offset the nonlinear distortion of the system.
  • the adjusting the amplitude and phase of the alternating current further includes: transmitting first signals of different frequencies with the same amplitude and phase to the human or animal body; receiving the first signal, and estimating the signal The noise floor; modify the amplitude of the first signal according to the distribution of the noise floor to obtain a second signal, so that the amplitude distribution of the second signal is the same as the amplitude distribution of the noise floor, and the second signal It is transmitted as the alternating current.
  • the receiving the AC voltage signal modulated by the tissue changes in the human body or animal includes determining the period of the AC current, and synchronizing each period of the AC voltage signal.
  • the processing of the frequency domain digital signal includes calculating the resistance and capacitance of the target tissue through complex impedances of multiple frequencies to separate the resistance and capacitance of the peripheral tissue from the resistance and capacitance of the target tissue .
  • the calculation of the resistance and capacitance of the target tissue includes calculating the resistance and capacitance of the target tissue and the peripheral tissue respectively through a system recognition or channel estimation program.
  • the system identification or channel estimation program includes using the resistance and capacitance values to perform multi-chamber modeling, wherein each chamber is modeled by parallel resistance and capacitance, and multiple chambers are connected in series or in parallel. connection.
  • the multi-chamber modeling includes two-chamber modeling, where peripheral tissue is between the electrode and the target tissue.
  • the frequency range of the alternating current is 10KHz to 1MHz.
  • the system includes a terminal, at least one sensor and at least one processor, wherein the terminal includes:
  • a generating module used to generate a plurality of alternating current signals of different frequencies, the alternating current signal will be transmitted to the human body or animal body to generate a plurality of alternating voltage signals, wherein the amplitude and phase of the alternating current signal are programmable;
  • a receiving module for amplifying an AC voltage signal and digitizing the AC voltage signal into a digital signal
  • a preprocessing module for preprocessing the digital signal through demodulation and filtering
  • At least one sensor for transmitting the generated alternating current signal to the human body or animal body, and receiving the alternating voltage signal modulated by the change of the human body or animal body tissue;
  • At least one processor is used to process the digital signal obtained by the preprocessing module to estimate the state of the target tissue.
  • system further includes at least one mathematical accelerator for system identification and channel estimation to calculate the model value of the resistance and capacitance.
  • the generation module is configured to use digital signal processing technology to simultaneously generate multiple alternating current signals of different frequencies from the frequency domain to the time domain, wherein the alternating current signals of different frequencies are periodic, and the digital
  • the signal processing technology includes Orthogonal Frequency Division Multiplexing (OFDM) technology.
  • the preprocessing module is configured to determine the period of the transmitted AC current signal and synchronize each period of the AC voltage signal.
  • At least one sensor is configured to sequentially or simultaneously sample multiple signals from different parts of the human or animal body.
  • the preprocessing module is configured to calculate resistance and capacitance through complex impedances of multiple frequencies to separate the resistance and capacitance of the peripheral tissue from the resistance and capacitance of the target tissue.
  • the at least one math accelerator is configured to calculate the resistance and capacitance values of the target tissue and the peripheral tissue through a system recognition or channel estimation program, respectively.
  • the processor is further configured to establish an equivalent circuit of multiple chambers through the values of the resistance and capacitance, and each chamber includes a resistance and capacitance connected in parallel, and multiple chambers are connected in series or in parallel.
  • system further includes a database for storing results from the at least one processor, the at least one processor being configured to retrieve the results.
  • the database keeps the monitoring of the system in real-time or offline.
  • the invention relates to a method and system for detecting characteristics of biological tissues. It applies multiple alternating currents of different frequencies to the human or animal body at the same time. After receiving the voltage signal modulated by the human or animal body, the received signal is demodulated. Extract information from the target tissue and surrounding tissues from the carrier of the specified frequency. Separate the information of the target tissue and surrounding tissues by performing system identification or channel estimation procedures. Calculate the resistance and capacitance of the target tissue and its surrounding tissues, and use the calculated resistance and capacitance to indicate the state of body fluids and target tissues. Therefore, corresponding information can be obtained accurately and reliably, so as to accurately measure the target organization.
  • Figure 1 is an overall frame diagram of some systems provided by an embodiment of the present invention.
  • Figure 2 is a specific structure diagram of a part of the system provided by another embodiment of the present invention.
  • Figure 3 is an overall frame diagram of some systems provided by another embodiment of the present invention.
  • FIG. 4 is a circuit diagram of a dual-chamber model measurement circuit provided by another embodiment of the present invention.
  • 5A is a schematic diagram of the frequency response of the system to the resistance provided by another embodiment of the present invention.
  • FIG. 5B is a schematic diagram of the expected frequency response of the system after the correction of the resistance provided by another embodiment of the present invention.
  • FIG. 6 is a schematic diagram of the actual frequency response of the system after the correction of the resistance provided by another embodiment of the present invention.
  • FIGS. 7A and 7B are schematic diagrams of human or animal frequency response for a second-order RC human or animal model provided by another embodiment of the present invention.
  • FIGS. 8A-8C are schematic diagrams of arterial results of the aorta measured by the dual-chamber model provided by another embodiment of the present invention.
  • FIGS. 9A-9C are schematic diagrams of the peripheral results of the aortic measurement of the dual-chamber model provided by another embodiment of the present invention.
  • 10A-10C are schematic diagrams of ventricular results measured by a dual-chamber model provided by another embodiment of the present invention.
  • 11A-11C are schematic diagrams of the peripheral results of the dual-chamber model provided by another embodiment of the present invention for measuring the ventricles;
  • 12A-12C are schematic diagrams of arterial results measured on the chest by a dual-chamber model provided by another embodiment of the present invention.
  • FIGS. 13A-13C are schematic diagrams of the peripheral results of the chest measurement of the dual-chamber model provided by another embodiment of the present invention.
  • 14A-14C are schematic diagrams of arterial/venous results of the right lung measured by a dual-chamber model provided by another embodiment of the present invention.
  • 15A-15C are schematic diagrams of the peripheral results of the right lung measurement of the dual-chamber model provided by another embodiment of the present invention.
  • 16A-16C are schematic diagrams of the arterial/venous results of the left lung measured by the dual-chamber model provided by another embodiment of the present invention.
  • Figures 17A-17C are schematic diagrams of the peripheral results of the left lung measurement of the dual-chamber model provided by another embodiment of the present invention.
  • the present invention relates to a non-invasive technique for detecting the electrical properties of biological tissues, such as the resistance and capacitance of the tissues and their change patterns.
  • the purpose of the embodiments of the present invention is to capture changes in body fluids, blood flow, and cardiovascular circulation for monitoring and information detection for non-therapeutic purposes.
  • the multiple alternating current signals of different frequencies generated by the transmission are simultaneously applied to the human or animal body to generate multiple alternating voltage signals.
  • a digital signal processing technique is used to simultaneously generate a plurality of alternating current signals of different frequencies, wherein the alternating current signals of a plurality of different frequencies are periodic, and the digital signal processing technique may be orthogonal frequency division Multiplexing (OFDM) technology.
  • OFDM orthogonal frequency division Multiplexing
  • the cycle of the alternating current signal is determined, and each cycle of the received alternating voltage signal is synchronized.
  • Preprocessing the digital signal further includes demodulating and filtering the digital signal to obtain a frequency domain digital signal.
  • the frequency domain digital signal to obtain the resistance and capacitance of the human tissue, and estimate the state of the target tissue.
  • the information of the cardiovascular system and surrounding tissues is extracted from the carrier of the specified frequency. Perform system identification or channel estimation procedures to separate different information about the cardiovascular system and surrounding tissues. Calculate the resistance and capacitance of the cardiovascular system and surrounding tissues, and use the calculated resistance and capacitance to indicate the state of body fluids and cardiovascular circulation.
  • Orthogonal Frequency Division Multiplexing (OFDM) technology is the core technology of modern digital communications. It can generate multiple orthogonal sine or cosine signals of different frequencies in one frequency band. A segment of such a signal in the time domain is called an Orthogonal Frequency Division Multiplexing (OFDM) symbol. It is characterized in that signals of all frequencies have their own complete period in the OFDM symbol. OFDM symbols can have their own cyclic prefix (cyclic prefix). Orthogonal frequency division multiplexing (OFDM) symbols are repeated continuously to form an orthogonal frequency division multiplexing signal or sequence.
  • OFDM Orthogonal Frequency Division Multiplexing
  • system identification In a linear system, the method of deriving the transfer function of the system from the frequency response of the system is called system identification.
  • System identification generally requires multiple frequency parameters, namely amplitude and phase to calculate. The higher the signal-to-noise ratio of these frequency signals, the more accurate and reliable the system function obtained. If the signal-to-noise ratio of some of the frequency signals is poor, it will affect the accuracy and reliability of the system function. Therefore, keeping the signal-to-noise ratio of all frequencies consistent or close can improve the reliability and accuracy of system identification. If there are interferences on certain frequencies, they should be eliminated or avoided.
  • the signal energy of different frequencies at the transmitting end can be adjusted according to the noise floor of the receiving end.
  • This adjustment varies with people and the environment.
  • the parameters (amplitude and phase) of signals of different frequencies will be used for calculation, and signals with a large signal-to-noise ratio will bring higher calculation accuracy and reliability.
  • the ideal situation is that all frequency signals have the same signal-to-noise ratio. This requires that the spectral distribution of the transmitted signal and the distribution of the noise floor at the receiving end are the same.
  • one aspect of the present invention provides a detection method that can overcome system nonlinear distortion and environmental noise.
  • the amplitude and phase of the AC voltage signal can be adjusted according to the nonlinear distortion and environmental noise of the system, including: first, transmitting different frequency signals with the same energy (amplitude) and phase to the human or animal body; The signal spectrum is processed at the receiving end and the floor noise is estimated; the energy (amplitude) of the different frequency signals at the transmission end is modified according to the distribution of the floor noise, so that the signal energy (amplitude) distribution at the transmission end and the floor noise distribution are the same.
  • the received multi-frequency signal basically remains the same.
  • the noise ratio is equal.
  • the cycle of the alternating current signal is determined, and each cycle of the received alternating voltage signal is synchronized.
  • Preprocessing the digital signal further includes demodulating and filtering the digital signal to obtain a frequency domain digital signal.
  • the frequency domain digital signal to obtain the resistance and capacitance of the human tissue, and estimate the state of the target tissue.
  • the information of the cardiovascular system and surrounding tissues is extracted from the carrier of the specified frequency. Perform system identification or channel estimation procedures to separate different information about the cardiovascular system and surrounding tissues. Calculate the resistance and capacitance of the cardiovascular system and surrounding tissues, and use the calculated resistance and capacitance to indicate the state of body fluids and cardiovascular circulation.
  • One aspect of the present invention provides human or animal hemodynamic monitoring, including body fluids and blood flow, as well as the state of arteries, heart, and lungs.
  • the cardiovascular circulation, body fluids and cardiovascular tissues are obtained by extracting changes in tissue resistance and capacitance ( Including the quantitative correlation between the state of the heart and lungs.
  • AC alternating currents
  • Another aspect of the present invention provides a method that can simultaneously detect the amplitude and phase of a plurality of alternating voltages of different frequencies, or the changes of the real and imaginary parts of the complex voltage. Converts changes in the amplitude and phase of multiple alternating voltages into the resistance and capacitance of tissues in the body.
  • the demodulated signal is filtered and processed to perform multi-chamber modeling, and the multi-chamber model is used to achieve information separation between the cardiovascular system and surrounding tissues.
  • alternating currents of different frequencies are simultaneously injected into the human or animal body through the electrodes, and form a loop with some external electrical components.
  • electric currents propagate in humans or animals, their electric fields are modulated by body tissue and changes in the loop.
  • the sampled modulated signal and electrocardiogram (ECG) signal will be amplified by computer processing and digitized into a digital format.
  • ECG electrocardiogram
  • the demodulated data from the multi-frequency signal is filtered and processed to perform multi-chamber modeling. Estimate the state of the target organization based on the multi-chamber model.
  • the received phase should be equal to the transmitted phase.
  • the energy of the received signals of different frequencies is equal. If the energy or amplitude of the signal is not equal, it indicates that the transmission or reception amplification system has phase or amplitude distortion, which is preferably corrected. This correction can occur at the transmitting end or the receiving end.
  • the amplitude and phase of the frequency of the transmission signal are set to the same amount of inverse change, that is, anti-distortion, to offset the nonlinear distortion of the system.
  • a dual-chamber RC (resistance and capacitance) model is used to model the target tissue.
  • Multiple chambers can be used to simulate human or animal bodies.
  • a chamber can represent arteries, atria and ventricles, which are the main part of the cardiovascular circulatory system.
  • the other chamber may represent the connecting tissue (peripheral tissue) between the electrode and the cardiovascular circulatory system.
  • Each chamber is represented by a parallel RC network including integrated resistors and capacitors.
  • the two chambers can be connected in series because the arterial system is not directly connected to the electrodes.
  • the connecting tissue (peripheral tissue) is always between the measuring electrode and the artery.
  • the present invention also includes a three-chamber model based on a two-chamber model.
  • the three-chamber model is a parallel RC network (Rc and Cc) connected in parallel with another parallel RC network, as shown in Figure 4, where the other parallel RC network is connected in series by two
  • the parallel RC network is composed of (the parallel RC network Rp and Cp are connected in series to the parallel RC network Ri and Ci).
  • the three-compartment model is more suitable for human or animal body tissues, but requires more calculations and has lower stability.
  • the tissue RC value is independent of frequency, for example, 10KHz to 1MHz.
  • ECG electrocardiogram
  • the invention provides a technique for measuring the integrated R and C values of the dual-chamber model.
  • the multi-chamber model can be processed similarly.
  • the embodiment of the present invention provides 10 frequency responses at a rate of 751 Hz to perform dual-chamber model measurements. These 10 frequency responses come from the demodulation of the received signal and are used to estimate the integrated R and C values. Therefore, the dual-chamber R and C values are estimated 751 times per second, and the estimated times should be high enough to show cardiovascular changes. More frequency response can be used, but this requires more calculations.
  • An aspect of the present invention provides a system for implementing any of the above methods.
  • the system includes a terminal, at least one math accelerator, and at least one processor, wherein the terminal includes:
  • One or more sensors used to transmit the generated alternating current to the human body or animal body, and to receive the alternating voltage signal modulated by the change of the human body or animal body tissue to obtain the modulated signal;
  • One or more receiving amplifiers for amplifying AC voltage signals into amplified signals are One or more receiving amplifiers for amplifying AC voltage signals into amplified signals
  • At least one analog-to-digital converter for digitizing the amplified signal into a digital signal
  • At least one preprocessing module for preprocessing digital signals the preprocessing further includes demodulating and filtering the digital signals;
  • At least one math accelerator is configured to calculate resistance and capacitance values through digital signals
  • At least one processor is configured to estimate the state of the target tissue.
  • the processor can be a single computer or multiple computers, with or without a math accelerator array.
  • the math accelerator may be a dedicated circuit for processing calculations and used to offload calculation tasks from a processor that needs to process multiple tasks in a terminal or system.
  • the terminal also includes a man-machine interface that connects people to the system.
  • the computer can be remote, so that a person (doctor) can remotely observe the system in real time.
  • the embodiments of the present invention provide a method and system for checking the correlation between changes in body resistance and capacitance and body fluids and cardiovascular circulation.
  • One aspect of the present invention provides a method and system for extracting characteristic information from the resistance and capacitance of tissues in the body to represent the hemodynamics and body fluid status of humans or animals, including but not limited to resistance and capacitance curves
  • the slope value of the slope value, the slope value of the first derivative of the slope value, the time period, the normalized amplitude change, the delay of the R wave relative to the ECG, the integrated shape area, the ratio of different states (such as the contraction and relaxation of the heart) including but not limited to resistance and capacitance curves The slope value of the slope value, the slope value of the first derivative of the slope value, the time period, the normalized amplitude change, the delay of the R wave relative to the ECG, the integrated shape area, the ratio of different states (such as the contraction and relaxation of the heart) .
  • An aspect of the present invention provides a method and system for correlating the calculated resistance and capacitance changes of the target tissue with arterial elasticity. Therefore, the calculated human or animal arterial model can match the measured RC feature model.
  • One aspect of the present invention provides a method and system for correlating the calculated resistance and capacitance changes of the target tissue with the work state and elasticity of the myocardial tissue. Therefore, the calculated human or animal heart elastic structure model can match the measured RC feature model.
  • One aspect of the present invention provides a method and system for changing the frequency and frequency value, timing or phase of alternating current, and the amount of intensity.
  • One aspect of the present invention provides a method and system for using some or all of the above information to estimate the health status of cardiovascular circulation, including body fluid status.
  • Fig. 1 shows the settings of the terminal system.
  • the human or animal body 1 has electrodes or contacts A, B, C, D, E, and F connecting the system.
  • the signal generator 2 generates a broadband signal, which is composed of multiple frequency components from 10KHz to 1MHz.
  • the signal generator 2 is connected to electrodes or contacts A and D, or F and D through wires or cables 5 and 6.
  • the electrodes or contacts A and D are selected so that the generated signal or excitation signal (current) can pass through the relevant arteries, lungs, and heart, and in this embodiment, through the thoracic cavity, in which several main arteries pass.
  • the signal flow follows the longitudinal direction of the blood flow or artery.
  • the signal generated goes from A to D or from D to A in humans or animals.
  • the electrodes or contacts F and D are selected so that the generated signal or excitation signal (current) can pass through related arteries and lungs closer to the heart, and the heart.
  • the signal flow follows the direction of blood flow.
  • the signal generated goes from F to D or from D to F in humans or animals.
  • the signal detector 3 collects voltage signals from points B and C, and E and C through wires or cables 8, 9 and 10.
  • the signal processor 4 controls and coordinates the signal generator 2 and the signal detector 3.
  • the signal processor 4 also processes the collected signals from B, C, and E, and extracts biological information from them.
  • Figure 2 shows a functional or structural view of the terminal system, which is also called an acquisition system.
  • the system can not only acquire signals, but also send excitation signals (current) to the human or animal body and its tissues.
  • the signal generator 25 can work in the time domain and the frequency domain and generate multi-frequency signals. In the time domain, these signals are the sum of multiple sine or cosine waves. In the frequency domain, these signals are the sum of multiple frequency tones. The energy (amplitude) and phase of these multiple frequency tones are programmable.
  • the signal generator 25 can convert frequency tones into multiple sinusoidal signals in the time domain. The generated digital sinusoidal signal passes through the digital-to-analog converter 26 to generate an analog signal.
  • analog signals sequentially pass through the analog amplifier 11 and are amplified to drive a broadband current pump device 12 to output broadband current.
  • a broadband current pump device 12 Starting from the current pump device 12, small currents of multi-frequency sine waves enter the human body or animal body through the contacts or electrodes A and D, or F and D at the same time.
  • the human or animal body will modulate the traveling signal voltage.
  • This modulated voltage and other bioelectric signals will be picked up from points B and C, or E and C. Since all these signals are very weak, they will first be amplified by the analog pre-amplifier group 27.
  • the main function of the analog pre-amplifier group 27 is to convert a high impedance input signal into a low impedance input signal.
  • Each pre-amplifier in the analog pre-amplifier group 27 has two signal paths. One of the signal paths enters one of a set of impedance cardiogram (ICG) amplifiers. The other signal path enters one of a set of biological signal amplifiers. ICG signals and biological signals require different gains and different filters. In general, the ICG signal enters the ICG amplifier group 14. After the biological signal enters the biological signal amplifier group 28, it is digitized by the analog-to-digital converter group 29. After the ICG signal is amplified, it is digitized by the IGC high-resolution analog-to-digital converter group ("IGC Hi-RES ADC BANK”) 15, which is a high-resolution and high-speed analog-to-digital converter group. The digitized signal will be processed by the digital signal processor 16, including various pre-processing such as demodulation, filtering, and extraction of different biological signals.
  • ICG Hi-RES ADC BANK IGC high-resolution analog-to-digital converter group
  • FIG. 3 shows how the computer system works according to an embodiment.
  • the excitation signal is sent out through path 17.
  • the modulation signal of the human or animal body and other biological signals enter through the path 18.
  • the terminal system 19 includes a generating module, a receiving module, and a preprocessing module.
  • the generating module generates the current signal that needs to be transmitted;
  • the receiving module receives and digitizes the amplified analog signal, and separates the ECG data;
  • the preprocessing module includes digital demodulation and filtering.
  • the preprocessing module includes a mathematical accelerator to perform System identification and channel estimation to calculate resistance and capacitance model values.
  • the math accelerator may also be independent of the terminal system 19.
  • the terminal system 19 also has its own man-machine interface.
  • the terminal system 19 sends the obtained RC model value and electrocardiogram (ECG) data to the local computer 20, and the local computer 20 completes all final processing, such as parameter calculation, feature extraction, and data analysis.
  • the database server 22 is used to store results and data. It can be a local computer storage server or a remote computer storage server, such as a cloud-based computer storage server.
  • the database server 22 may also be a mixture of local and remote computer storage servers. Among them, 23 is the communication between the local host 20 and the terminal system 19.
  • Figure 4 shows the circuit diagram of the multi-chamber model.
  • Three chambers are shown in Figure 4, represented by Rc and Cc, Rp and Cp, and Ri and Ci.
  • Fig. 4 includes a current source of multi-frequency alternating current with intensity I, driving leads L1 and L4 in contact with the main body, and receiving leads L2 and L3 in contact with the main body.
  • Cs represents the skin capacitance of the subject
  • Rs represents the skin resistance of the subject.
  • the resistance-capacitance (RC) pair Cp-Rp (representing the peripheral or connected tissue), Cc-Rc (representing the direct tissue connection between the two receiving leads in parallel with the cardiovascular system), and Ci-Ri (representing the blood circulation system or target Tissue) together to form a human or animal tissue RC model.
  • Rc and Cc can be discarded.
  • two parallel RC pairs, Rp-Cp and Ri-Ci are connected in series.
  • a more realistic three-chamber RC model requires more calculations and lacks stability.
  • Figure 5A shows the frequency response of the system to the resistance as a model of the human body.
  • 10 main carriers with the same power and different frequencies, representing 10 frequency tones, which are 13.6KHz, 32.3KHz, 72.5KHz, 95.5KHz, 115.6KHz, 135.7KHz, 160.1KHz, 203.2KHz, 279.3KHz and 348.2 KHz.
  • Due to the nonlinearity of the system there are different signal losses at different frequencies. These signal losses or distortions will affect the calculation of the RC model. More importantly, due to the combination of environmental interference and the human body, the noise floor is not evenly distributed.
  • each frequency signal received has the same signal-to-noise ratio.
  • Figure 5B shows the corrected expected frequency response in Figure 5A.
  • First estimate the floor noise distribution as shown by the solid line in the figure.
  • This distribution needs to be evaluated as described before each time the human body is tested. That is, before the test, transmit multiple tone signals with the same energy and phase to the human body, measure the noise floor distribution, and then adjust the energy (amplitude) of the multiple tones transmitted to the noise floor distribution. System correction is added on the basis of evaluation.
  • Figure 6 shows the actual frequency response after correction in Figure 5A.
  • the amplitude of different tones does not completely correspond to the expected value in Figure 5B, because the noise floor varies greatly here. If they match completely, the energy (amplitude) of the high-frequency signal is very small, which will affect the overall signal-to-noise ratio. Actually, only the difference of 10dB is corrected for different tones. From the actual measurement, it can be seen that the signal-to-noise ratio of each frequency is about 50dB. This is an optimal state.
  • Figures 7A-7B show the human or animal frequency response for the second order RC human or animal model.
  • the measured frequency response matches the 2nd order RC model.
  • the behavior of the Cole model is not observed here because blood is the main resistance, which causes the Cole center frequency to be much higher.
  • the target tissue is modeled as a nearly linear system on a relatively narrow frequency band, such as 10KHz to 1MHz, or on an even narrower frequency band.
  • Figures 8A-8C show the results of a two-chamber model measured on the aorta.
  • the ECG shown in Figure 8A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Ra is the resistance of the aortic chamber model.
  • Ca is the capacitance of the aortic chamber model.
  • Figures 8B and 8C closely follow the heartbeat changes shown in Figure 8A.
  • arteries At the end of diastole, arteries have the smallest blood reserves and the highest electrical resistance, while the capacitance is the lowest.
  • the artery At the end of systole, the artery has the largest volume. The resistance is the smallest and the capacitance is the largest.
  • Figures 9A-9C show the results of a two-chamber model measured on the aorta.
  • the ECG shown in Figure 9A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Rp is the resistance of the peripheral tissue chamber model.
  • Cp is the capacitance of the peripheral tissue chamber model.
  • Figures 9B and 9C do not show simple changes according to the heartbeat rhythm. Therefore, these figures show examples of data that interfere with accurate modeling, which will be removed.
  • Figures 10A-10C show the results of a dual-chamber model measured on the heart.
  • the ECG shown in Figure 10A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Rh is the resistance of the heart chamber model.
  • Ch is the capacitance of the heart chamber model.
  • Figures 10B and 10C closely follow heartbeat changes. At the end of diastole, the heart has the most blood and the least resistance, while the capacitance is the greatest. At the end of systole, the heart has the smallest size. The resistance is the largest and the capacitance is the smallest.
  • FIGs 11A-11C show the results of the dual-chamber model measured on the heart.
  • the ECG shown in Figure 11A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Rp is the resistance of the peripheral tissue chamber model.
  • Cp is the capacitance of the peripheral tissue chamber model.
  • Figures 11B and 11C do not show significant changes according to the heartbeat rhythm.
  • Figures 12A-12C show the results of a dual-compartment model measured on the upper chest (thorax).
  • the ECG shown in Figure 12A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Ru is the resistance of the upper chest chamber model, which includes the arteries of the thoracic cavity and the heart.
  • Cu is the capacitance of the upper chest chamber model.
  • Figures 12B and 12C closely follow heartbeat changes. Before the ventricles contract, the arteries have the smallest blood reserves and the highest electrical resistance, while the capacitance is the lowest. At the end of systole, the artery has the largest volume. The resistance is the smallest and the capacitance is the largest.
  • Figures 13A-13C show the results of a dual-compartment model measured on the upper chest.
  • the ECG shown in Figure 13A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Rp is the resistance of the peripheral tissue chamber model.
  • Cp is the capacitance of the peripheral tissue chamber model.
  • Figures 13B and 13C do not follow the heartbeat changes as clearly as the upper chest chamber model.
  • Figures 14A-14C show the results of a two-compartment model measured on the right lung.
  • the ECG shown in Figure 14A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • R Right Lung is the resistance of the arterial/venous chamber model of the right lung.
  • C right lung is the capacitance of the arterial/venous chamber model of the right lung.
  • Figures 14B and 14C closely follow heartbeat changes.
  • Figures 15A-15C show the results of a two-compartment model measured on the right lung.
  • the ECG shown in Figure 15A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Rp is the resistance of the peripheral tissue chamber model of the right lung.
  • Cp is the capacitance of the peripheral tissue chamber model of the right lung.
  • Figures 15B and 15C also closely follow heartbeat changes.
  • Figures 16A-16C show the results of a two-compartment model measured on the left lung.
  • the ECG shown in Figure 16A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Rleft lung is the resistance of the arterial/venous chamber model of the left lung.
  • CLeft Lung is the capacitance of the arterial/venous chamber model of the left lung. Since the left lung has arteries, veins, and heart, its model is more complicated than a simple two-chamber model.
  • the drawings are different from the others, but Figures 16B and 16C still show changes following the heartbeat to a certain extent.
  • Figures 17A-17C show the results of a two-compartment model measured on the left lung.
  • the ECG shown in Figure 17A is not a traditional 12-lead ECG. This is enough to show the timing of the heart cycle, which can be accepted for use under the condition that the R wave is recognized.
  • Rp is the resistance of the peripheral tissue chamber model of the left lung.
  • Cp is the capacitance of the peripheral tissue chamber model of the left lung.
  • Figures 17B and 17C show that heartbeat changes closely follow, and this result is different from that shown in other figures.
  • the embodiments of the present invention provide a method and system for detecting human or animal tissue characteristic information by simultaneously applying multiple alternating currents of different frequencies to the human or animal body. After receiving the modulated voltage signal, demodulate the received signal. Then extract the information of the cardiovascular system and surrounding tissues from the sub-carriers of the specified frequency. Separate the information of the cardiovascular system and surrounding tissues by performing system identification or channel estimation procedures. Calculate the resistance and capacitance of the cardiovascular system and its surrounding tissues, and use the calculated resistance and capacitance to represent the state of body fluids and cardiovascular circulation. Therefore, the corresponding status information can be accurately and reliably obtained, and the measurement of the target tissue is convenient to obtain the health status.

Abstract

本发明涉及一种用于检测体内组织特征信息的非侵入性方法及系统，其传输生成的多个交流电流至人体或动物体内以产生多个交流电压信号，其中所述多个交流电流信号的振幅和相位是可编程的；接收由所述人体或动物体内组织变化调制的所述交流电压信号，得到调制信号；放大并将所述调制信号数字化为数字信号；预处理所述数字信号，所述预处理进一步包括解调和滤波所述数字信号以得到频域数字信号；处理所述频域数字信号得到所述组织的电阻和电容，以及估计目标组织的状态。由此能够准确、可靠的获取相应的状态信息，便于对目标组织的准确测量以获得健康状态。

Description

一种用于提取生物组织特征信息的非侵入性方法及其系统 技术领域
本发明涉及一种用于提取体内组织特征信息的非侵入性方法及其系统。
背景技术
生物阻抗和生物电抗测量作为一种测量血流量和体液水平的非侵入性方法已被广泛探索。这些技术在医学领域中被广泛接受。但它们存在一些弊端。首先，所有计算的参数都基于阻抗，该阻抗与频率有关。这些参数只能间接表示心血管状态。而且，由于这些参数是频率相关的，它们将遭受频率选择性的损伤。其次，连接组织的阻抗在阻抗测量中起着重要作用。传统的生物阻抗和生物电抗测量受周围组织阻抗和目标组织阻抗的混合影响。有时很难确定哪个阻抗占主导地位。因此，混合阻抗因人而异；即使是同一个人，混合阻抗也会因不同的组织状态而不同。因此，生物阻抗和电抗不是表示体液和心血管循环特征的良好候选者。
从电学角度来看，生物组织的特征在于导体和非导体。导体通过电导测量(电阻反向)，非导体可以通过电容或介电常数测量。一个广泛认可的人体组织模型是Cole模型。基本上，交流电流主要由细胞外液体传导，细胞外液体主要是低频电阻，例如1KHz。随着交流电流频率的增加，交流电流通过细胞外液体和细胞。由于细胞具有与电容器功能类似的膜，因此交流电流将具有相变。随着频率不断增加，超过1MHz，细胞在总阻抗中的膜效应变得微不足道，总阻抗再次变为纯电阻。Cole模型描述了这种行为。
任何生物组织的变化基本上都将导致其电导和电容的变化。因此，为了呈 现组织的变化，组织电导和电容变化的测量比生物阻抗混合生物电抗的测量更加可靠，其中包括连接组织的阻抗和电抗。由于组织的电导和电容是频率相关的，因此必须选择频带的范围。人们普遍认为组织的信息主要在10KHz到1MHz的频带内。因此，为了测量组织的电导和电容，使用10KHz到1MHz频带的多频交替激励(电流)。根据欧姆定律，可以从多频交变电流计算组织的电导和电容。
由于人体或动物体的个体差异、状态差异以及测量时的环境差异，将造成身体组织的导电性、电磁场变化和基底噪声等方面的差异。这些差异可以影响载波的信噪比，进而影响测量的精确度。目前亟待开发一种具有更高的计算准确性和可靠性的非侵入性方法用于提取生物组织特征信息进而辅助判断生物体的健康状态。
发明内容
本发明为解决现有技术中存在的问题，提出一种检测生物组织电特性的非侵入性方法，其目的在于捕捉体液变化、血液流动和心血管循环的变化以实现目标组织特征信息的准确检测，并进一步获知人体或生物体的状态。所述方法主要用于非治疗目的信息检测。
本发明提供了一种用于检测体内组织特征信息，以及捕捉体液、血液流动和/或心血管循环的变化的非侵入性方法及其系统，所述方法包括：
传输生成的多个交流电流至人体或动物体内以产生多个交流电压信号，其中所述多个交流电流的振幅和相位是可编程的；优选的，这个振幅和相位的编程是根据传输、接收系统的非线性和环境噪声调整的，目的是在接收端达到最 好测量效果。
接收由所述人体或动物体内组织变化调制的所述交流电压信号，得到调制信号，所述组织包括目标组织和外围组织；
放大并将所述调制信号数字化为数字信号；
预处理所述数字信号，所述预处理进一步包括解调和滤波所述数字信号以得到频域数字信号；
处理所述频域数字信号得到所述组织的电阻和电容，以及
估计目标组织的状态。
一方面，所述生成多个具有不同频率的交流电流包括，使用数字信号处理技术从频域到时域同时产生多个不同频率的所述交流电流，其中，多个不同频率的所述交流电流是周期性的，所述数字信号处理技术包括正交频分复用(OFDM)技术。
一方面，所述传输生成的多个交流电流至人体或动物体内以产生多个交流电压信号包括，根据系统的非线性失真和环境噪声，调整所述交流电流的振幅和相位。
一方面，所述调整所述交流电流的振幅和相位包括，将所述交流电流的振幅和相位预先设置为反失真，以抵消所述系统的非线性失真。
一方面，所述调整所述交流电流的振幅和相位还包括：传输具有相同振幅和相位的不同频率的第一信号至所述人体或动物体；接收所述第一信号，并估算所述信号的基底噪声；根据所述基底噪声的分布修改所述第一信号的振幅， 得到第二信号，使得所述第二信号的振幅分布与所述基底噪声的振幅分布相同，以所述第二信号作为所述交流电流进行传输。
一方面，所述接收由所述人体或动物体内组织变化调制的所述交流电压信号包括，确定所述交流电流的周期，并同步所述交流电压信号的每个周期。
一方面，所述处理所述频域数字信号包括，通过多个频率的复阻抗计算所述目标组织的电阻和电容以将所述外围组织的电阻和电容与所述目标组织的电阻和电容分离。
一方面，所述计算目标组织的电阻和电容包括通过系统识别或信道估计程序分别计算目标组织和外围组织的电阻和电容的值。
一方面，所述系统识别或信道估计程序包括使用所述电阻和电容的值进行多室建模，其中，每个腔室通过并联的电阻和电容建模，多个腔室之间串联或并联连接。
一方面，所述多室建模包括双室建模，其中外围组织在电极和所述目标组织之间。
一方面，所述交流电流的频率范围为10KHz到1MHz。
一种用于实现上述方法的系统，该系统包括终端、至少一个传感器和至少一个处理器，其中，所述终端包括：
发生模块，用于生成多个不同频率的交流电流信号，该交流电流信号将传输至人体或动物体内以产生多个交流电压信号，其中所述交流电流信号的振幅和相位是可编程的；
接收模块，用于放大交流电压信号并将所述交流电压信号数字化为数字信号；
预处理模块，用于通过解调和滤波来预处理所述数字信号；
至少一个传感器，用于将产生的所述交流电流信号传输到人体或动物体，以及接收由人体或动物体内组织变化调制的交流电压信号；
和，至少一个处理器用于处理预处理模块得到的数字信号以估计目标组织的状态。
一方面，所述系统还包括至少一个数学加速器，用于进行系统识别和信道估计，以计算电阻电容的模型值。
一方面，所述发生模块被配置为使用数字信号处理技术从频域到时域同时产生多个不同频率的交流电流信号，其中，所述不同频率的交流电流信号是周期性的，所述数字信号处理技术包括正交频分复用(OFDM)技术。
一方面，所述预处理模块被配置为确定所述传输的交流电流信号的周期，以及同步所述交流电压信号的每个周期。
一方面，至少一个传感器被配置为从人体或动物体的不同部位依次或同时采样多个信号。
一方面，所述预处理模块被配置为通过多个频率的复阻抗计算电阻和电容以将外围组织的电阻和电容与目标组织的电阻和电容分离。
一方面，所述至少一个数学加速器被配置为通过系统识别或信道估计程序分别计算目标组织和外围组织的电阻和电容的值。
一方面，所述处理器进一步被配置为通过所述电阻和电容的值建立多腔室的等效电路，并且每个腔室包括并联连接的电阻和电容，多个腔室串联或并联连接。
一方面，所述系统还包括数据库，用于存储来自所述至少一个处理器的结果，所述至少一个处理器被配置为检索所述结果。
一方面，所述数据库使得所述系统的监测保持实时或离线状态。
本发明涉及一种用于检测生物组织特征的方法及系统。其将多个不同频率的交流电流同时应用于人体或动物体。在接收到经人体或动物体调制的电压信号后，解调接收的信号。从指定频率的载波中提取来自目标组织和周围组织的信息。通过执行系统识别或信道估计程序将目标组织和周围组织的信息分开。分别计算目标组织及其周围组织的电阻和电容，使用计算的电阻和电容表示体液和目标组织的状态。由此能够准确、可靠地获取相应的信息，以便于对目标组织准确测量。
附图说明
下面将结合附图对本发明的实施例进一步说明。
图1是本发明一个实施例提供的部分系统的总体框架图；
图2是本发明另一个实施例提供的部分系统的具体结构图；
图3是本发明另一个实施例提供的部分系统的总体框架图；
图4是本发明另一个实施例提供的双室模型测量电路图；
图5A是本发明另一个实施例提供的系统对电阻的频率响应示意图；
图5B是本发明另一个实施例提供的系统对电阻的矫正后的预期频率响应示意图；
图6是本发明另一个实施例提供的系统对电阻的矫正后的实际频率响应示意图；
图7A和7B是本发明另一个实施例提供的针对2阶RC人或动物模型的人或动物频率响应示意图；
图8A-8C是本发明另一个实施例提供的双室模型对主动脉测量的动脉结果示意图；
图9A-9C是本发明另一个实施例提供的双室模型对主动脉测量的外围结果示意图；
图10A-10C是本发明另一个实施例提供的双室模型对心室测量的心室结果示意图；
图11A-11C是本发明另一个实施例提供的双室模型对心室测量的外围结果示意图；
图12A-12C是本发明另一个实施例提供的双室模型对胸部测量的动脉结果示意图；
图13A-13C是本发明另一个实施例提供的双室模型对胸部测量的外围结果示意图；
图14A-14C是本发明另一个实施例提供的双室模型对右肺测量的动脉/静脉结果示意图；
图15A-15C是本发明另一个实施例提供的双室模型对右肺测量的外围结果示意图；
图16A-16C是本发明另一个实施例提供的双室模型对左肺测量的动脉/静脉结果示意图；
图17A-17C是本发明另一个实施例提供的双室模型对左肺测量的外围结果示意图。
具体实施方式
现在结合附图对本发明实施例作进一步详细的说明。
本发明涉及检测生物组织的电特性的非侵入性技术，例如组织的电阻和电容及其变化模式。本发明实施例的目的是捕捉体液变化、血液流动和心血管循环的变化，用于非治疗目的的监测和信息检测。传输生成的多个不同频率的交流电流信号同时应用于人体或动物体以产生多个交流电压信号。可选实施例中，使用数字信号处理技术同时产生多个不同频率的交流电流信号，其中，多个不同频率的所述交流电流信号是周期性的，数字信号处理技术可选为正交频分复用(OFDM)技术。
接收由人体或动物体内组织变化调制的交流电压信号。可选实施例中，确定交流电流信号的周期，并同步接收的交流电压信号的每个周期。
放大并将接收的交流电压信号数字化为数字信号。
预处理数字信号，预处理进一步包括解调和滤波数字信号以得到频域数字信号。
处理频域数字信号得到人体组织的电阻和电容，以及估计目标组织的状态。可选实施例中，从指定频率的载波中提取心血管系统和周围组织的信息。执行系统识别或信道估计程序，以将心血管循环系统和周围组织的不同信息分开。分别计算心血管系统及周围组织的电阻和电容，使用计算的电阻和电容表示体液和心血管循环的状态。
正交频分复用(OFDM)技术是现代数字通信的核心技术。它在一个频段中能产生多个正交的不同频率的正弦或余弦信号。在时域中一段这样的信号被称作正交频分复用(OFDM)符号。其特征在于，所有频率的信号在OFDM符号中都有自己的完整周期。OFDM符号可以有自己的循环前缀(cyclic prefix)。正交频分复用(OFDM)符号不断重复，形成正交频分复用信号或序列。
在线性系统中，由系统的频率响应导出系统的传递函数的方法称作系统识别。系统识别一般需要多个频率的参数，即振幅和相位来计算。这些频率信号的信噪比越高，得到的系统函数就越精确，也越可靠。如果其中某些频率信号的信噪比差，就会影响到系统函数的精确度和可靠性。因此保持所有频率的信噪比一致或接近，可以提高系统识别的可靠性和精确度。如果某些频率存在干扰，就应该消除或避开它们。
由于人体或动物体的个体差异、状态差异以及测量时的环境差异，将造成身体组织的导电性、电磁场变化和基底噪声等方面的差异。这些差异可以大于10dB，并且影响载波的信噪比，接收端的电流信号信噪比也会因不同的频率而产生大于10dB的差异。同样的载波能量，在基底噪声大的频段，它的信噪比就小，在基底噪声小的频段，它的信噪比就大。因此保持传输的不同频率信号的信噪比在接收端相同，传输端的不同频率的信号能量就可以根据接收端的基底 噪声进行调整。这个调整是随人和环境变化的。系统识别的计算中，不同频率的信号的参数(振幅和相位)都会被用于计算，信噪比大的信号会带来更高的计算准确性和可靠性。理想的情况是所有频率信号都具有相同的信噪比。这就要求传输信号的频谱分布和接收端基底噪声的分布是一样的。
为得到更加精确的计算结果，本发明一方面提供的可以克服系统的非线性失真和环境噪声的检测方法。
可选实施例中，由于人体或动物体的个体差异、状态差异以及测量时的环境差异，测量结果将会受到其他非线性因素的干扰。在进行系统识别前可以根据系统的非线性失真和环境噪声，调整交流电压信号的振幅和相位，具体包括，第一、传输具有相同能量(振幅)和相位的不同频率信号至人体或动物体；在接收端处理得到的信号频谱，并估算基底噪声；根据该基底噪声的分布修改传输端的不同频率信号的能量(振幅)，使得传输端的信号能量(振幅)分布和基底噪声分布相同。第二、传输能量(振幅)改变后的不同频率的信号至同一个人体或动物体，所传输信号的同步性和周期性都不变，在接收端，接收到的多频信号基本上保持信噪比相等。每次测量前对所要测量的对象进行上述操作，可以使得计算结果更加精确和可靠。
接收由人体或动物体内组织变化调制的交流电压信号。可选实施例中，确定交流电流信号的周期，并同步接收的交流电压信号的每个周期。
放大并将接收的交流电压信号数字化为数字信号。
预处理数字信号，预处理进一步包括解调和滤波数字信号以得到频域数字信号。
处理频域数字信号得到人体组织的电阻和电容，以及估计目标组织的状态。可选实施例中，从指定频率的载波中提取心血管系统和周围组织的信息。执行系统识别或信道估计程序，以将心血管循环系统和周围组织的不同信息分开。分别计算心血管系统及周围组织的电阻和电容，使用计算的电阻和电容表示体液和心血管循环的状态。
本发明的一个方面提供人或动物的血液动力学监测，包括体液和血流，以及动脉、心脏和肺的状态，通过提取组织的电阻和电容变化来获取心血管循环、体液和心血管组织(包括心脏和肺)状态之间的定量相关性。
使用数字信号处理技术从频域到时域产生多个不同频率的交流电流(AC)。该多个不同频率的交流电流是周期性的。
在多个频率的复阻抗上将外围组织的电阻和电容与目标心血管组织的电阻和电容分离。
从指定频率的载波中提取来自心血管组织和周围组织的信息，通过系统识别或信道估计程序实现心血管组织和周围组织的信息分离。
本发明的另一个方面提供可以同时检测多个不同频率的交流电压的振幅和相位，或复电压的实部和虚部的变化的方法。将多个交变电压的振幅和相位的变化转换成体内组织的电阻和电容。
处理信号后，滤波并处理该解调的信号以执行多室建模，利用多室模型实现心血管系统和周围组织的信息分离。
多个不同频率的交流电流通过电极同时注入人体或动物体，并与一些外部电气部件形成环路。当电流在人体或动物体内传播时，它们的电场受到身体组 织和组织在环路中的变化的调制。存在与注入回路部分重叠的接收回路，其中可以检测和采样调制的交流电压。采样的调制信号和心电图(ECG)信号将通过计算机处理放大并数字化为数字格式。在信号处理之后，对来自多频信号的解调数据进行滤波和处理以执行多室建模。根据多室模型估计目标组织的状态。
可选实施例中，在RC建模之前，必须确定从多个频率收集的调制信息是正确的。对一个纯电阻的线性调制系统来讲，接收的相位应该和传输的相位是等同的。接收的不同频率的信号能量是相等的。如果信号的能量或振幅不相等，说明传输或接收放大系统具有相位或振幅失真，优选加以矫正。这个矫正可以发生在传输端或接收端。可选实施例中，根据纯电阻网络的相位或振幅的频率响应，将传输信号的频率的振幅和相位设置同量的反变化，即反失真，以抵消系统的非线性失真。这也就要求不同频率信号的振幅和相位可编程。所以在组织电阻和电容的测量中，在传输端可以包括两种矫正，其一为系统矫正，用于排除系统的非线性干扰，得到近似线性的系统，其二为人体和环境(环境噪声)矫正，使得不同频率的信号具有相等的信噪比。
可选实施例中，双室RC(电阻和电容)模型用于对目标组织建模。多腔室可以用于模拟人体或动物体。例如，用于胸腔测量，一个腔室可以表示动脉、心房和心室，这是心血管循环系统的主要部分。另一个腔室可以表示电极和心血管循环系统之间的连接组织(外围组织)。每个腔室由包括集成电阻和电容的并联RC网络表示。两个腔室可以串联连接，因为动脉系统不直接连接在电极上。连接组织(外围组织)总是在测量电极和动脉之间。系统识别或信道估计技术用于计算集成R(电阻)和C(电容)值。该R和C值用于估计体液、血流和心血管循环。双室模型的优点是其能够使心血管循环系统从周围组织中分离。 本发明也包括基于双室模型的三室模型，该三室模型是并联RC网络(Rc和Cc)与另一个并联RC网络并联连接，如图4所示，其中另一个并联RC网络由两个串联连接的并联RC网络组成(并联RC网络Rp和Cp串联连接于并联RC网络Ri和Ci)。三室模型更加适用于人体或动物体组织，但是需要更多的计算，以及具有较低的稳定性。
从窄频带角度看，组织RC值与频率无关，例如10KHz至1MHz。将双室电阻和电容的变化与心电图(ECG)时序参考相结合，可以估计心血管状态。本发明提供了测量该双室模型的集成R和C值的技术。多室模型可以进行类似的处理。本发明的实施例以751Hz的速率提供10个频率响应，以执行双室模型测量。这10个频率响应来自接收信号的解调，并且用于估计集成R和C值。因此，双室R和C值每秒估算751次，估算次数应足够高以显示心血管变化。可以使用更多的频率响应，但这需要更多的计算。
本发明的一方面提供一种用于实现上述任何方法的系统，该系统包括终端、至少一个数学加速器和至少一个处理器，其中，该终端包括：
发生器，用于产生多个不同频率的交流电流信号；
一个或多个传感器，用于将产生的交流电流传输至人体或动物体，以及接收由人体或动物体内组织变化调制的交流电压信号，得到调制信号；
一个或多个接收放大器，用于放大交流电压信号为放大信号；
至少一个模数转换器，用于将放大信号数字化为数字信号；
至少一个预处理模块，用于预处理数字信号，该预处理进一步包括解调和滤波数字信号；
和，至少一个数学加速器被配置为通过数字信号计算电阻和电容值；以及
至少一个处理器被配置为估计目标组织的状态。
该处理器可以是单个计算机或多个计算机，可以具备或不具备数学加速器阵列。本领域普通技术人员可以理解，数学加速器可以是处理计算的专用电路，用于将计算任务从需要处理终端或系统多项任务的处理器中卸载。
终端还包括连接人和系统的人机界面。计算机可以是远程的，从而使得人(医生)可以远程实时观察系统。
一方面，本发明的实施例提供了一种检查体内电阻和电容的变化，与体液和心血管循环之间的相关性的方法和系统。
本发明的一方面提供了一种方法和系统，其用于从体内组织的电阻和电容中提取特征信息，以表示人或动物的血液动力学和体液状态，使用包括但不限于电阻和电容曲线的斜率值、该斜率值的一阶导数的斜率值、时间段、归一化振幅变化、相对于心电图的R波的延时、整合形状区域、不同状态的比率(例如心脏的收缩和舒张)。
本发明的一方面提供了一种方法和系统，用于将计算的目标组织的电阻和电容变化与动脉弹性相关联。因此，计算的人或动物的动脉模型可以匹配测量的RC特征模型。
本发明的一方面提供了一种方法和系统，用于将计算的目标组织的电阻和电容变化与心肌组织的做功状态和弹性相关联。因此，计算的人或动物的心脏弹性结构模型可以匹配测量的RC特征模型。
本发明的一方面提供了一种方法和系统，用于改变交流电流的频率和频率 值、时序或相位，以及强度的数量。
本发明的一方面提供了一种方法和系统，用于使用一些或所有上述信息来估计心血管循环的健康状态，包括体液状态。
上述方法及系统将在下文具体阐述，其可以实现针对目标组织的准确检测，并且具有更佳的检测准确性。
根据实施例，图1显示了终端系统的设置。人或动物体1具有连接系统的电极或触点A、B、C、D、E和F。信号发生器2产生宽频带信号，该信号由10KHz到1MHz的多频成分组成。信号发生器2通过电线或电缆5和6连接至电极或触点A和D，或F和D。选择电极或触点A和D可以使得产生的信号或激励信号(电流)能够通过相关的动脉、肺部和心脏，以及在本实施例中通过胸腔，该胸腔中有若干主要动脉通过。信号流遵循血流或动脉的纵向方向。产生的信号在人或动物体内从A到D或从D到A。选择电极或触点F和D可以使得产生的信号或激励信号(电流)能够通过更靠近心脏的相关动脉和肺部，以及心脏。信号流遵循血流方向。产生的信号在人或动物体内从F到D或从D到F。
信号检测器3通过电线或电缆8、9和10从点B和C、以及E和C收集电压信号。信号处理器4控制并协调信号发生器2和信号检测器3。信号处理器4还处理来自B、C和E的收集信号，并从中提取生物信息。
图2显示了终端系统的功能或结构视图，其也被称为采集系统。本实施例中，该系统不仅可以获取信号，还可以将激励信号(电流)发送至人体或动物体及其组织中。信号发生器25可以在时域和频域工作，并产生多频信号。在时 域中，这些信号是多个正弦或余弦波的总和。在频域中，这些信号是多个频率音调的总和。这些多个频率音调的能量(振幅)和相位是可编程的。信号发生器25可以在时域上将频率音调转换为多个正弦信号。生成的数字正弦信号通过数模转换器26生成模拟信号。这些模拟信号依次通过模拟放大器11并被放大，以驱动一个宽频带的电流泵设备12输出宽带电流。从电流泵设备12开始，多频正弦波的小电流通过触点或电极A和D、或F和D非同时进入人体或动物体。作为复杂介质的人体或动物体将调制行进的信号电压。该调制的电压和其他生物电信号将从点B和C，或E和C中拾取。由于所有这些信号都很弱，它们将首先被模拟预放大器组27放大，模拟预放大器组27主要功能是将高阻抗输入信号转换为低阻抗输入信号。
模拟预放大器组27中的每一个预放大器有两个信号路径。其中一条信号路径进入一组阻抗心动图(ICG)放大器中的一个。另一条信号路径进入一组生物信号放大器中的一个。ICG信号和生物信号需要不同的增益和不同的滤波器。总的来说，ICG信号进入ICG放大器组14。生物信号进入生物信号放大器组28后，由模数转换器组29进行数字化。ICG信号放大后，由IGC高分辨率模数转换器组(“IGC Hi-RES ADC BANK”)15进行数字化，这是一组高分辨率和高速模数转换器组。数字化的信号将由数字信号处理器16处理，包括诸如解调、滤波、提取不同的生物信号等的多种预处理。
图3根据实施例示出了计算机系统如何工作。激励信号通过路径17发出。人体或动物体的调制信号和其他生物信号通过路径18进入。终端系统19包括发生模块、接收模块和预处理模块。发生模块产生需要传输的电流信号；接收模块接收放大模拟信号并数字化，并将ECG数据分离出来；预处理模块包括数 字解调和滤波，可选实施例中，预处理模块包括一个数学加速器来进行系统识别和信道估计，以计算电阻电容模型值。可选实施例中，数学加速器也可以独立于终端系统19。终端系统19也拥有自己的人机界面。
在一个实施例中，终端系统19将获得的RC模型值，和心电图(ECG)数据发送至本地计算机20，本地计算机20完成所有的最终处理，例如参数计算、特征提取和数据分析。数据库服务器22用于存储结果和数据，其既可以是本地计算机存储服务器，也可以是远程计算机存储服务器，例如基于云端的计算机存储服务器。数据库服务器22也可以是本地和远程计算机存储服务器的混合。其中，23是本地主机20和终端系统19之间的通信。
图4显示了多室模型的电路示意图。图4中显示了三个腔室，分别由Rc和Cc、Rp和Cp，以及Ri和Ci表示。图4包括具备强度I的多频交流电流的电流源，与主体接触的驱动引线L1和L4，以及与主体接触的接收引线L2和L3。Cs表示主体的皮肤电容，Rs表示主体的皮肤电阻。电阻-电容(RC)对Cp-Rp(表示外围或连接组织)、Cc-Rc(表示与心血管系统并联的两个接收引线间的直接组织连接)和Ci-Ri(表示血液循环系统或目标组织)一起组成人或动物组织RC模型。对于简化的双室模型，可以丢弃Rc和Cc。对于双室模型，两个并联RC对，Rp-Cp和Ri-Ci，串联连接。更加实际的三腔室RC模型需要更多的计算并且缺少稳定性。
图5A显示了系统作为人体的模型，对电阻的频率响应。其中有10个具有相同功率的不同频率的主要载波，表示10个频率音调，分别是13.6KHz、32.3KHz、72.5KHz、95.5KHz、115.6KHz、135.7KHz、160.1KHz、203.2KHz、279.3KHz和348.2KHz。由于系统的非线性，在不同频率上存在不同的信号损失。这些信 号损失或失真会影响到RC模型的计算。更重要的，由于环境干扰和人体的结合，基底噪声不是均匀分布的。其结果就是虽然在不同频率上传输具有同样能量的信号，接收端的不同频率信号的信噪比是不一样的。这会影响到系统识别的结果。优选接收的每个频率信号都有相同的信噪比。
图5B显示了图5A中的矫正后的预期频率响应。首先估计基底噪声分布，如图中实线所示。然后保持预期的接收频调的载波信噪比相等，且叠加在基底噪声上。这就是需要传输的频调的能量(振幅)分布。这个分布需要每次测试人体前，做一次如前所述的评估。即在测试前，传输具有相同能量和相位的多个频调信号到人体，测得基底噪声分布，然后再把传输的多个频调的能量(振幅)调成基底噪声的分布。在评估的基础上再加上系统矫正。
图6显示了图5A中的矫正后的实际频率响应。不同频调的振幅没有完全对应图5B的预期值，因为这里的基底噪声变化很大。如果完全吻合，高频信号的能量(振幅)就很小，会影响到整体的信噪比。实际对不同的频调只矫正10dB的差别。从实际测量中，可以看出每个频率的信噪比都是50dB左右。这是一个最优状态。
图7A-7B显示了针对2阶RC人或动物模型的人或动物频率响应。测量的频率响应与2阶RC模型匹配。此处未观察到Cole模型行为，原因是血液是主要的电阻，其导致Cole中心频率高得多。将目标组织在诸如10KHz到1MHz相对窄的频带上建模为接近线性的系统，或在甚至更窄的频带上建模。
图8A-8C显示了对主动脉测量的双室模型的结果。图8A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图8B中，Ra是主动脉腔室模型的电阻。在图8C中，Ca 是主动脉腔室模型的电容。图8B和8C紧密地跟随图8A中显示的心跳变化。在心脏舒张末期，动脉具有最小的血液储备和最高的电阻，而电容是最低的。在心脏收缩末期，动脉的体积最大。电阻最小，电容最大。
图9A-9C显示了对主动脉测量的双室模型的结果。图9A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图9B中，Rp是外围组织腔室模型的电阻。在图9C中，Cp是外围组织腔室模型的电容。图9B和9C没有显示出根据心跳节奏的简单变化。因此，这些附图显示了干扰准确建模的数据示例，其将会被去除。
图10A-10C显示了对心脏测量的双室模型的结果。图10A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图10B中，Rh是心脏腔室模型的电阻。在图10C中，Ch是心脏腔室模型的电容。图10B和10C紧密地跟随心跳变化。在心脏舒张末期，心脏具有最多的血液和最小的电阻，而电容是最大的。在心脏收缩末期，心脏的体积最小。电阻最大，电容最小。
图11A-11C显示了对心脏测量的双室模型的结果。图11A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图11B中，Rp是外围组织腔室模型的电阻。在图11C中，Cp是外围组织腔室模型的电容。图11B和11C没有显示出根据心跳节奏的明显变化。
图12A-12C显示了对上胸部(胸腔)测量的双室模型的结果。图12A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图12B中，Ru是上胸部腔室模型的电阻，其 包括胸腔的动脉和心脏。在图12C中，Cu是上胸部腔室模型的电容。图12B和12C紧密地跟随心跳变化。在心室收缩前，动脉具有最小的血液储备和最高的电阻，而电容是最低的。在心脏收缩末期，动脉的体积最大。电阻最小，电容最大。
图13A-13C显示了对上胸部测量的双室模型的结果。图13A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图13B中，Rp是外围组织腔室模型的电阻。在图13C中，Cp是外围组织腔室模型的电容。图13B和13C没有如上胸部腔室模型一样明显地跟随心跳变化。
图14A-14C显示了对右肺测量的双室模型的结果。图14A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图14B中，“R右肺”是右肺的动脉/静脉腔室模型的电阻。在图14C中，“C右肺”是右肺的动脉/静脉腔室模型的电容。图14B和14C紧密地跟随心跳变化。
图15A-15C显示了对右肺测量的双室模型的结果。图15A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图15B中，Rp是右肺的外围组织腔室模型的电阻。在图15C中，Cp是右肺的外围组织腔室模型的电容。图15B和15C也紧密地跟随心跳变化。
图16A-16C显示了对左肺测量的双室模型的结果。图16A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图16B中，“R左肺”是左肺的动脉/静脉腔室模型的电阻。 在图16C中，“C左肺”是左肺的动脉/静脉腔室模型的电容。由于左肺具有动脉、静脉和心脏，其模型比简单的双室模型更复杂。附图与其他的有所不同，但是图16B和16C仍然显示出一定程度上跟随心跳变化。
图17A-17C显示了对左肺测量的双室模型的结果。图17A显示的ECG不是传统的12导联ECG。这足以显示心搏周期的时序，在R波被识别的条件下，其可以被接受使用。在图17B中，Rp是左肺的外围组织腔室模型的电阻。在图17C中，Cp是左肺的外围组织腔室模型的电容。图17B和17C显示出紧密地跟随心跳变化，该结果与其他附图中显示的不一样。
如上所示，本发明的实施例提供了一种用于通过将多个不同频率的交流电流同时应用与人体或动物体以检测人或动物组织特征信息的方法及系统。在接收到调制电压信号后，解调接收的信号。然后从指定频率的子载波中提取心血管系统和周围组织的信息。通过执行系统识别或信道估计程序将心血管循环系统和周围组织的信息分开。分别计算心血管系统及其周围组织的电阻和电容，使用计算的电阻和电容表示体液和心血管循环的状态。由此能够准确、可靠地获取相应的状态信息，便于对目标组织的测量，以获取健康状态。
上述说明描述了具体实施方式，本领域普通技术人员完全可以在不偏离本项发明技术思想的范围内，进行多样的变更以及修改。本项发明的范围并不局限于说明书上的内容，须根据权利要求的范围来确定。

Claims (21)

  1. 一种用于检测体内组织特征信息的非侵入性方法，其特征在于，所述方法用于捕捉体液、血流、和心血管循环的变化，所述方法包括：
    传输生成的多个交流电流至人体或动物体内以产生多个交流电压信号，其中所述多个交流电流的振幅和相位是可编程的；
    接收由所述人体或动物体内组织变化调制的所述交流电压信号，得到调制信号，所述组织包括目标组织和外围组织；
    放大并将所述调制信号数字化为数字信号；
    预处理所述数字信号，所述预处理进一步包括解调和滤波所述数字信号以得到频域数字信号；
    处理所述频域数字信号得到所述组织的电阻和电容，以及
    估计目标组织的状态。
  2. 根据权利要求1所述的方法，其特征在于，所述传输生成的多个交流电流至人体或动物体内以产生多个交流电压信号包括，使用数字信号处理技术同时产生多个不同频率的所述交流电流，其中，所述多个不同频率的交流电流是周期性的，所述数字信号处理技术包括正交频分复用(OFDM)技术。
  3. 根据权利要求2所述的方法，其特征在于，所述传输生成的多个交流电流至人体或动物体内以产生多个交流电压信号进一步包括，根据系统的非线性失真和环境噪声，调整所述交流电流的振幅和相位。
  4. 根据权利要求3所述的方法，其特征在于，所述调整所述交流电流的振幅和相位包括，将所述交流电流的振幅和相位预先设置为反失真，以抵消所述 系统的非线性失真。
  5. 根据权利要求3所述的方法，其特征在于，所述调整所述交流电流的振幅和相位包括：
    传输具有相同振幅和相位的不同频率的第一信号至所述人体或动物体；
    接收所述第一信号，并估算所述信号的基底噪声；
    根据所述基底噪声的分布修改所述第一信号的振幅，得到第二信号，使得所述第二信号的振幅分布与所述基底噪声的振幅分布相同，以所述第二信号作为所述交流电流进行传输。
  6. 根据权利要求1～5任一项所述的方法，其特征在于，所述接收由所述人体或动物体内组织变化调制的所述交流电压信号包括，确定所述交流电流的周期，并同步所述交流电压信号的每个周期。
  7. 根据权利要求1～5任一项所述的方法，其特征在于，所述处理所述频域数字信号包括，通过多个频率的复阻抗计算所述目标组织的电阻和电容以将所述外围组织的电阻和电容与所述目标组织的电阻和电容分离。
  8. 根据权利要求7所述的方法，其特征在于，所述计算所述目标组织的电阻和电容包括通过系统识别或信道估计程序分别计算所述目标组织和所述外围组织的电阻和电容的值。
  9. 根据权利要求8所述的方法，其特征在于，所述系统识别或信道估计程序包括使用所述电阻和电容的值进行多室建模，其中，每个腔室通过并联的电阻和电容建模，多个腔室之间串联或并联连接。
  10. 根据权利要求9所述的方法，其特征在于，所述多室建模包括双室建模，其中所述外围组织在电极和所述目标组织之间。
  11. 根据权利要求1所述的方法，其特征在于，所述交流电流的频率的范围为10KHz到1MHz。
  12. 一种用于实现权利要求1～11所述方法的系统，其特征在于，所述系统包括终端、至少一个传感器和至少一个处理器，其中，所述终端包括：
    发生模块，用于生成多个不同频率的交流电流信号；
    接收模块，用于放大交流电压信号并将所述交流电压信号数字化为数字信号；
    预处理模块，用于通过解调和滤波来预处理所述数字信号；
    所述至少一个传感器，用于将生成的所述交流电流信号传输至人体或动物体，以及接收由所述人体或动物体内组织变化调制的交流电压信号；
    和，至少一个处理器用于处理所述预处理模块得到的数字信号以估计目标组织的状态。
  13. 根据权利要求12所述的系统，其特征在于，所述系统还包括至少一个数学加速器，用于进行系统识别和信道估计，以计算电阻电容的模型值。
  14. 根据权利要求13所述的系统，其特征在于，所述发生模块被配置为使用数字信号处理技术从频域到时域同时产生多个不同频率的交流电流信号，其中，所述不同频率的交流电流信号是周期性的，所述数字信号处理技术包括正交频分复用(OFDM)技术。
  15. 根据权利要求12～14任一项所述的系统，其特征在于，所述预处理模块被配置为确定所述交流电流信号的周期，以及同步所述交流电压信号的每个周期。
  16. 根据权利要求12～14任一项所述的系统，其特征在于，至少一个传感器被配置为从人体或动物体的不同部位依次或同时采样多个信号。
  17. 根据权利要求12～14任一项所述的系统，其特征在于，所述处理器被配置为通过多个频率的复阻抗计算电阻和电容以将外围组织的电阻和电容与目标组织的电阻和电容分离。
  18. 根据权利要求13～14任一项所述的系统，其特征在于，所述至少一个数学加速器被配置为通过系统识别或信道估计程序分别计算目标组织和外围组织的电阻和电容的值。
  19. 根据权利要求18所述的系统，其特征在于，所述处理器进一步被配置为通过所述电阻和电容的值建立多腔室的等效电路，并且每个腔室包括并联连接的电阻和电容，多个腔室之间串联或并联连接。
  20. 根据权利要求12～14任一项所述的系统，其特征在于，所述系统还包括数据库，用于存储来自所述至少一个处理器的结果，所述至少一个处理器被配置为检索所述结果。
  21. 根据权利要求20所述的系统，其特征在于，所述数据库使得所述系统的监测保持实时或离线状态。
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1319376A (zh) * 2000-03-30 2001-10-31 株式会社百利达 生物电流阻抗测量仪
CN101827554A (zh) * 2007-09-07 2010-09-08 英戈·弗洛尔 用于生物电阻抗测量的医学测量装置
CN101926647A (zh) * 2003-09-12 2010-12-29 肾脏研究所有限公司 生物阻抗方法和仪器
WO2014128237A1 (de) * 2013-02-22 2014-08-28 Falko Skrabal Ekg-gerät
CN206603770U (zh) * 2016-09-27 2017-11-03 常熟理工学院 一种基于单片机的生理阻抗测试仪
CN108055823A (zh) * 2015-07-16 2018-05-18 伊派迪迈德公司 流体水平确定
CN108670253A (zh) * 2018-01-30 2018-10-19 重庆求谷科技有限公司 基于生物电阻抗检测终端的物联网智慧美容系统及方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1319376A (zh) * 2000-03-30 2001-10-31 株式会社百利达 生物电流阻抗测量仪
CN101926647A (zh) * 2003-09-12 2010-12-29 肾脏研究所有限公司 生物阻抗方法和仪器
CN101827554A (zh) * 2007-09-07 2010-09-08 英戈·弗洛尔 用于生物电阻抗测量的医学测量装置
WO2014128237A1 (de) * 2013-02-22 2014-08-28 Falko Skrabal Ekg-gerät
CN108055823A (zh) * 2015-07-16 2018-05-18 伊派迪迈德公司 流体水平确定
CN206603770U (zh) * 2016-09-27 2017-11-03 常熟理工学院 一种基于单片机的生理阻抗测试仪
CN108670253A (zh) * 2018-01-30 2018-10-19 重庆求谷科技有限公司 基于生物电阻抗检测终端的物联网智慧美容系统及方法

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