WO2020210949A1 - 一种用于检测体内组织特征信息的非侵入性方法及其系统 - Google Patents

一种用于检测体内组织特征信息的非侵入性方法及其系统 Download PDF

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WO2020210949A1
WO2020210949A1 PCT/CN2019/082729 CN2019082729W WO2020210949A1 WO 2020210949 A1 WO2020210949 A1 WO 2020210949A1 CN 2019082729 W CN2019082729 W CN 2019082729W WO 2020210949 A1 WO2020210949 A1 WO 2020210949A1
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tissue
resistance
signal
frequency domain
ofdm
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PCT/CN2019/082729
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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/CN2019/082729 priority Critical patent/WO2020210949A1/zh
Priority to EP19924857.6A priority patent/EP3957240A4/en
Priority to JP2021549901A priority patent/JP7175052B2/ja
Publication of WO2020210949A1 publication Critical patent/WO2020210949A1/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
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/053—Measuring electrical impedance or conductance of a portion of the body
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7228—Signal modulation applied to the input signal sent to patient or subject; demodulation to recover the physiological signal

Definitions

  • the invention relates to a non-invasive method and system for detecting tissue characteristic information in the body.
  • Bioimpedance and bioreactor measurements have been widely explored as a non-invasive method for measuring 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. They can only indirectly represent cardiovascular status. Moreover, since they are frequency dependent, they will be affected by frequency selectivity. Secondly, the impedance of the connected tissue plays an important role in impedance measurement. Traditional bioimpedance and bioreactor measurements are the result of a mixture of surrounding tissue impedance and target tissue impedance; however, in some cases, it is difficult to determine which one is dominant. Therefore, mixed impedance varies among individuals; even for the same individual, it will vary with different organizational states. Therefore, bioimpedance and reactance are not good candidates for characterizing body fluids and cardiovascular circulation.
  • the characteristics of biological tissue are manifested in conductors and non-conductors.
  • Conductors are measured by conductivity (reciprocal resistance), and non-conductors can be measured by capacitance or dielectric constant.
  • the 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 AC voltage 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 tissue will basically lead to changes in its resistance (or conductance) and capacitance. Therefore, in order to present tissue changes, the measurement of tissue resistance and capacitance changes is more reliable than mixed bioimpedance and bioreactor, which includes the impedance and reactance of the connected tissue. Since the conductance and capacitance of the tissue are frequency dependent, 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. 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.
  • FFT/IFFT Fast (Inverse) Fourier Transform
  • OFDM Orthogonal Frequency Division Multiplexing
  • the present invention proposes a non-invasive method and system for detecting tissue characteristic information in the body, and its purpose is to capture changes in body fluids, blood flow and cardiovascular circulation to achieve target tissues Accurate detection of feature information to further know the state of the human body or organism.
  • the method is mainly used for the health monitoring of the organism, the elasticity measurement verification of the cardiovascular system, and the information detection for non-treatment purposes.
  • the present invention provides a technical solution:
  • a non-invasive method for detecting tissue characteristic information in the body is used to capture changes in body fluids, blood flow, and/or cardiovascular circulatory tissue.
  • the method includes: using inverse fast Fourier transform (IFFT) ) Generate multiple synchronous alternating currents of different frequencies with the characteristics of orthogonal frequency division multiplexing (OFDM) symbols and transmit them to the human body or animal body; receive the alternating current current modulated by the human body or animal body tissue and its changes; The modulated AC current is amplified and digitally converted into a digital signal; the digital signal is preprocessed, and the preprocessing includes segmenting the digital signal into an orthogonal frequency division multiplexing (OFDM) symbol sequence, using fast Fourier transform ( FFT) demodulates the orthogonal frequency division multiplexing (OFDM) symbol sequence to obtain a frequency domain signal; estimates the state of the target organization according to the frequency domain signal.
  • IFFT inverse fast Fourier transform
  • FFT fast Fourier transform
  • the use of inverse fast Fourier transform (IFFT) or orthogonal frequency division multiplexing (OFDM) to simultaneously generate multiple synchronized AC currents of different frequencies includes generating synchronized multiple of different frequencies from the frequency domain to the time domain.
  • the receiving the AC current modulated by the tissue changes in the human or animal body includes determining the cycle of the AC current, and synchronously receiving the modulated AC signal in each of the cycles.
  • the estimating the state of the target tissue according to the frequency domain signal includes: separating the frequency domain signal, and filtering the separated frequency domain signal; calculating the resistance and capacitance values according to the frequency domain signal ; Use the resistance and capacitance values to estimate the state of the target tissue.
  • the separation of the frequency domain signal includes, on the complex impedance of the frequency domain signal, calculating a human body system transfer function through a system identification and channel estimation method.
  • the calculating the resistance and capacitance of the target tissue and the peripheral tissue includes calculating the resistance and capacitance of the target tissue and the peripheral tissue according to the transfer function of the human body system.
  • the use of the resistance and capacitance values to estimate the state of the target tissue includes using the resistance and capacitance values to perform multi-chamber modeling, each chamber is composed of a resistance and capacitance connected in parallel, and between the chambers Connect in series, parallel or series-parallel.
  • the multi-chamber modeling may be a two-chamber modeling, in which the connecting tissue is between the electrode and the target tissue.
  • the range of the frequency is 10KHz to 1MHz.
  • the present invention also provides a technical solution:
  • the system includes a terminal and a processor, wherein the terminal includes: a generator for generating an orthogonal frequency division complex using an inverse fast Fourier transform (IFFT) Multiple synchronous alternating currents of different frequencies characterized by (OFDM) symbols; one or more sensors for transmitting the multiple alternating currents into the human body or animal body, and receiving the alternating current modulated by changes in the tissues of the human body or animal body Current; one or more amplifiers for amplifying and digitally converting the modulated AC current into a digital signal; and a preprocessing module, which uses the characteristics of the OFDM symbol to segment the input digital signal into an OFDM symbol sequence.
  • IFFT inverse fast Fourier transform
  • OFDM synchronous alternating currents of different frequencies characterized by
  • FFT Fast Fourier Transform
  • the generator is used to generate a plurality of the alternating currents of different frequencies from the frequency domain to the time domain, that is, OFDM symbols, wherein the alternating currents of different frequencies are periodic, that is, the OFDM symbols are repeatedly output.
  • the intensity, phase and/or frequency of the alternating current are adjustable.
  • the processor is configured to determine the cycle of the alternating current, that is, to determine the length of an OFDM symbol, and to synchronously receive the modulated alternating signal in each of the cycles.
  • the senor is used to collect single or multiple data from different parts.
  • the preprocessing module is also used to separate the frequency domain signal, and perform filtering processing on the separated frequency domain signal.
  • the system further includes an accelerator for calculating resistance and capacitance values according to the frequency domain signal, and the calculation includes using a system identification or channel estimation program.
  • the processor establishes an equivalent circuit of multiple chambers through the resistance and capacitance values, and each chamber includes a resistance and a capacitance connected in parallel, and the multiple chambers are connected in series, parallel, or series-parallel.
  • the system may include a database for storing processing results and data of the processor, and the processor may retrieve the database.
  • the processor may be remote, and the remote observation system may work in a real-time mode.
  • the terminal further includes a man-machine interface for controlling the system and/or displaying results.
  • the present invention relates to a non-invasive method and system for detecting tissue characteristic information in the body. Compared with the prior art, it applies multiple synchronous periodic alternating currents of different frequencies to the human body at the same time.
  • the modulated signal demodulate and extract information from the cardiovascular system and surrounding tissues from the specified frequency carrier.
  • the combined information of the cardiovascular system and surrounding tissues can be obtained.
  • Use the calculated resistance and capacitance to represent the state of body fluids and cardiovascular circulatory tissues. Therefore, the corresponding status information can be obtained accurately and reliably, and accurate measurement of the target organization can be achieved.
  • Figure 1 is a schematic diagram of a terminal system of a preferred embodiment of the present invention.
  • FIG. 2 is a schematic diagram of the function or structure of a terminal according to a preferred embodiment of the present invention.
  • Figure 3 is a schematic diagram of the system structure of the preferred embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a multi-chamber model measurement circuit of a preferred embodiment of the present invention.
  • FIG. 5 is a schematic diagram of the structure of the system test circuit of the preferred embodiment of the present invention.
  • 6a-6c are schematic diagrams of the time domain signal and frequency response results of the system test on the measurement resistor network of the preferred embodiment of the present invention.
  • Figures 7a-7b are waveform diagrams of 10 synchronous tones transmitted ideally in a preferred embodiment of the present invention.
  • FIG. 8 is a schematic diagram of the actual signal received by the system of the preferred embodiment of the present invention.
  • FIG. 9 is a schematic diagram of receiving external signals in a preferred embodiment of the present invention, that is, a schematic diagram of human body signals;
  • 10a-10b are schematic diagrams of amplitude and phase response of the internal resistance network of the preferred embodiment of the present invention.
  • Figures 11a-11b are schematic diagrams of measured amplitude and phase responses of the human body according to a preferred embodiment of the present invention.
  • 12a-12b are schematic diagrams of the amplitude and phase response of the corrected human body according to a preferred embodiment of the present invention.
  • FIG. 13 is a schematic diagram of the transfer function and the frequency response of the human body after system identification in the preferred embodiment of the present invention.
  • 14a-14c are schematic diagrams of arterial results of a dual-chamber model of aortic measurement in a preferred embodiment of the present invention.
  • 15a-15c are schematic diagrams of the peripheral results of a dual-chamber model of aortic measurement in a preferred embodiment of the present invention.
  • 16a-16c are schematic diagrams of ventricular results of a dual-chamber model of ventricular measurement in a preferred embodiment of the present invention.
  • 17a-17c are schematic diagrams of the peripheral results of a dual-chamber model of ventricular measurement in a preferred embodiment of the present invention.
  • 18a-18c are schematic diagrams of the arterial results of a dual-chamber model of upper chest measurement in a preferred embodiment of the present invention.
  • 19a-19c are schematic diagrams of the peripheral results of a dual-chamber model of upper chest measurement in a preferred embodiment of the present invention.
  • 20a-20c are schematic diagrams of the arterial/venous results of the dual-chamber model of the right lung measurement in a preferred embodiment of the present invention.
  • 21a-21c are schematic diagrams of the peripheral results of the double-chamber model of the right lung measurement in a preferred embodiment of the present invention.
  • 22a-22c are schematic diagrams of the arterial/venous results of the double-chamber model of left lung measurement according to a preferred embodiment of the present invention.
  • Figures 23a-23c are schematic diagrams of the peripheral results of a double-chamber model measured on the left lung of a preferred embodiment of the present invention.
  • the present invention relates to a non-invasive technology for detecting the electrical characteristics of tissues in a living body, such as the resistance and capacitance of the tissues and their change patterns. Its goal is to capture changes in body fluids, blood flow and cardiovascular circulatory tissues, which are used to monitor the health of organisms, to verify the elasticity of the cardiovascular system, and to detect information for non-therapeutic purposes.
  • the method provided by the present invention is used to detect the state of human or animal tissues, including the state of body fluids and blood flow, arteries, heart, and lungs. By extracting changes in the resistance and capacitance of the tissues, it can be used to obtain the cardiovascular circulation, body fluids and cardiovascular tissues ( Including the quantitative correlation between the state of the heart and lungs. Based on this, the measurement method provided by an embodiment of the present invention at least includes:
  • IFFT Inverse Fast Fourier Transform
  • this embodiment uses digital signal processing technology, such as inverse fast Fourier transform (IFFT) or orthogonal frequency division multiplexing (OFDM), to generate multiple different frequencies of communication from the frequency domain to the time domain.
  • Digital signal processing technology such as inverse fast Fourier transform (IFFT) or orthogonal frequency division multiplexing (OFDM)
  • IFFT inverse fast Fourier transform
  • OFDM orthogonal frequency division multiplexing
  • AC Current
  • OFDM Orthogonal Frequency Division Multiplexing
  • the multiple alternating currents of different frequencies are periodic, taking the OFDM symbol length as the period, and multiple alternating currents of different frequencies are simultaneously applied to the human body.
  • the intensity, phase and/or frequency of the alternating current are adjustable.
  • the cycle of the AC current that is, the length of the OFDM symbol
  • the modulated AC signal that is, the OFDM symbol modulated by the human body
  • multiple alternating currents of different frequencies are injected into the human body at the same time through the electrodes, and form a loop with some external electronic components.
  • currents propagate in the human body, they are regulated by body tissues and tissue changes in the loop; the receiving circuit partially overlaps the injection circuit, so that the signal modulated by the overlapped human tissue can be detected.
  • the received AC current modulated by the human or animal body may be a current signal or a converted voltage signal, which are collectively referred to as a modulated OFDM symbol sequence. After being amplified, it is converted into a digital signal.
  • the electrocardiogram (ECG) signal is also superimposed on the modulated signal, and the electrocardiogram (ECG) can be separated by low-pass filtering before digital conversion, amplified separately and converted into a digital format signal for further processing.
  • Preprocessing the digital signal includes segmenting the digital signal into an orthogonal frequency division multiplexing (OFDM) symbol sequence, and using fast Fourier transform (FFT) to demodulate the orthogonal frequency division multiplexing (OFDM) symbol sequence , Get the frequency domain signal.
  • OFDM orthogonal frequency division multiplexing
  • FFT fast Fourier transform
  • the segmented digital signal becomes a sequence of OFDM symbols, and the fast Fourier transform (FFT) is used to demodulate each OFDM symbol to obtain the frequency Domain signal.
  • FFT fast Fourier transform
  • the characteristics of the OFDM symbol are searched in the received digital signal, and the period is known. After finding the characteristic segment, the starting point of the OFDM symbol can be determined. The received signal at this time becomes a sequence in units of OFDM symbols.
  • FFT Fast Fourier Transform
  • the frequency domain signal is separated, and the separated frequency domain signal is filtered; the system transfer function of human tissue is calculated according to the frequency domain signal, and the tissue resistance and capacitance values are calculated from the system transfer function; the resistance and capacitance values are used Estimate the status of the target organization.
  • the real and imaginary parts, or changes in amplitude and phase of multiple AC voltages of different frequencies are detected at the same time.
  • the system transfer function of the human body is calculated from the amplitude and phase of multiple tones, and the resistance and capacitance of the tissues in the human body are calculated from the parameters of the system transfer function of the human body.
  • Each chamber is composed of a resistance and a capacitance connected in parallel, and the chambers are connected in series, parallel, or series-parallel.
  • a dual-chamber RC (resistance and capacitance) model is used to simulate the target tissue.
  • the human body can be simulated with multiple chambers.
  • a chamber represents the artery, and/or atria and ventricles, which are the main part of the cardiovascular circulatory system.
  • the other chamber represents the connecting tissue between the electrodes and the cardiovascular circulatory system.
  • Each chamber is represented by a parallel RC network composed of integrated resistors and capacitors.
  • the two chambers are connected in series because the heart or arterial system is not directly connected to the electrodes.
  • the connecting tissue is always between the measuring electrode and the heart artery.
  • R and C values are used to estimate body fluids, blood flow, and cardiovascular circulatory tissue.
  • the advantage of the dual-compartment model is to separate the cardiovascular circulatory system from the surrounding tissues.
  • the two-chamber model there is also a three-chamber model, a parallel RC network and two parallel RC networks connected in series, as shown in Figure 4.
  • the three-compartment model is more suitable for real human tissues, but the calculation is large and the stability is poor.
  • IFFT Inverse Fast Fourier Transform
  • this embodiment uses digital signal processing technology, for example, inverse fast Fourier transform (IFFT) is used to generate orthogonal frequency division multiplexing (OFDM) symbols, that is, multiple different signals are generated from frequency domain to time domain.
  • IFFT inverse fast Fourier transform
  • OFDM orthogonal frequency division multiplexing
  • AC Frequency alternating current
  • the multiple alternating currents of different frequencies are periodic, and the period is the length of the OFDM symbol.
  • the intensity, phase and/or frequency of the alternating current are adjustable.
  • a cycle (OFDM symbol) of the combination of these alternating currents is shown in Figure 7a and Figure 7b.
  • Fig. 7a is the result of the original timing diagram (OFDM symbol) through 1024-point inverse fast Fourier transform (IFFT). There are 10 orthogonal, synchronized sine waves.
  • Figure 7b is the result of 4 times the original timing diagram. In the time domain, this sequence repeats endlessly.
  • the cycle of the AC current that is, the length of the OFDM symbol
  • the AC signal of the OFDM symbol modulated by the human body is synchronously received in each cycle.
  • its period and starting point are found. Then demodulate each OFDM symbol to obtain a frequency domain signal.
  • multiple alternating currents of different frequencies are injected into the human body at the same time through the electrodes, and form a loop with some external electronic components.
  • currents when currents propagate in the human body, they are regulated by body tissues and tissue changes in the loop; the receiving circuit and the injection circuit partially overlap, so that the signal modulated by the overlapping part of the human tissue can be detected .
  • a sequence of millions of points obtained by sampling at the receiving end is shown in FIG. 8.
  • the small amplitude part at the front end is the internal resistance measurement sequence
  • the large amplitude sequence at the back is the external human body measurement sequence.
  • the internal frequency response is used for each measurement to correct the external frequency response to reduce the random error of the system.
  • the large pulses in the internal resistance are pseudo-ECG data, because the ECG signal is combined in the high-frequency signal.
  • the starting point of the received OFDM symbol is found, and the received signal is turned into an OFDM symbol sequence, that is, the receiving end is synchronized with the transmitting end.
  • the AC current modulated by the human or animal body may be a current signal or a voltage signal in the receiving loop.
  • the electrocardiogram (ECG) signal is also superimposed on the modulated signal, and the electrocardiogram (ECG) can be separated by low-pass filtering before digital conversion. According to different needs, different signals are sampled, and the sampled signal is modulated and amplified and converted into a digital format signal for further processing.
  • Preprocessing the digital signal includes segmenting the digital signal into an orthogonal frequency division multiplexing (OFDM) symbol sequence, and using fast Fourier transform (FFT) to demodulate the orthogonal frequency division multiplexing (OFDM) symbol sequence , Get the frequency domain signal.
  • OFDM orthogonal frequency division multiplexing
  • FFT fast Fourier transform
  • the segmented digital signal becomes a sequence of OFDM symbols, and the fast Fourier transform (FFT) is used to demodulate each OFDM symbol to obtain the frequency Domain signal.
  • FFT fast Fourier transform
  • the synchronized received signal is demodulated. Find the characteristics of the OFDM symbol in the received digital signal, and the period is known. After finding the characteristic segment, the starting point of the OFDM symbol can be determined. The received signal at this time is a sequence in units of OFDM symbols. Fast Fourier Transform (FFT) demodulation can be used for each OFDM symbol to convert the signal to the frequency domain.
  • FFT Fast Fourier Transform
  • this is an amplitude frequency response graph.
  • the system receives 10 tones and a few interferences, and the interference has no effect on those 10 tones. Extract the response of these 10 tones from this frequency response. A total of 10 internal and 10 external tones are obtained.
  • the response of the internal 10 tones is shown in Figure 10.
  • the response of the 10 external tones is shown in Figure 11a-11b. Among them, the external frequency response includes the internal frequency response.
  • FIG. 12a-12b a schematic diagram of removing the internal frequency response from the external frequency response is shown in Figures 12a-12b.
  • an external resistor network is required for correction to obtain the frequency response of the human body.
  • system identification is performed after obtaining the frequency response of the human body system. But it is also very sensitive to phase noise. So after getting the time series of phase and amplitude, filter them. Human heartbeat is basically at 1-2 Hz, so a 10 Hz low-pass filter can be used.
  • system identification is performed. If the system is identifiable, the positive coefficients of the system transfer function will be obtained, that is, the negative root of the system transfer function will be obtained. If you get a positive root or a complex root, it means that the model is wrong. The reason is that the interference of some tones has a greater impact. People's interference may appear on different frequencies. This requires that the frequency of the 10 tones is adjustable.
  • the process of system identification is to find the minimum error of the measurement point on the frequency response.
  • 10 points are used for measurement. If high accuracy is required, frequency points can be increased. But the total energy of the signal is restricted by the safety of the human body. Therefore, increasing the frequency point will reduce the signal-to-noise ratio on each tone.
  • the resistance and capacitance values of the target tissue and peripheral tissues are calculated according to the transfer function of the human body system. This can be derived directly from the resistor-capacitor network.
  • the tissue RC value changes relatively little with frequency between 10 KHz and 1 MHz.
  • ECG electrocardiogram
  • information is extracted from the response of the 10 tones shown in FIG. 9. This information comes from the cardiovascular system and surrounding tissues. Then, perform system identification or channel estimation procedures to calculate the system transfer function.
  • the system transfer function we get is:
  • the two-chamber model calculated from this function is (corrected by 20 ohm resistance):
  • ECG electrocardiogram
  • each chamber is composed of a resistance and a capacitance connected in parallel, and the chambers are connected in series, parallel, or series-parallel.
  • a dual-chamber RC (resistance and capacitance) model is used to simulate the target tissue.
  • the human body can be simulated with multiple chambers.
  • a chamber represents the arteries, atria and ventricles, which are the main part of the cardiovascular circulatory system.
  • the other chamber represents the connecting tissue between the electrodes and the cardiovascular circulatory system.
  • Each chamber is represented by a parallel RC network composed of integrated resistors and capacitors.
  • the two chambers are connected in series because the heart and arterial system are not directly connected to the electrodes.
  • the connecting tissue is always between the measuring electrode and the heart artery.
  • system identification or channel estimation techniques are used to calculate the integrated R (resistance) and C (capacitance) values.
  • R and C values are used to estimate body fluids, blood flow, and cardiovascular circulatory tissue.
  • the advantage of the dual-compartment model is to separate the cardiovascular circulatory system from the surrounding tissues.
  • the two-chamber model there is also a three-chamber model, a parallel RC network and two parallel RC networks connected in series, as shown in Figure 4.
  • the three-compartment model is more suitable for real human tissues, but the calculation is large and the stability is poor.
  • the phase measurement of the human body system is the most important in the estimation of the two-chamber or multi-chamber model. It requires hardware with sufficient bandwidth response and minimal distortion. Since any system will bring distortions, channel estimation is needed to detect and cancel these distortions. First of all, distortion will appear in the driving part, which is the synchronous multi-frequency periodic current generating circuit. Then there is the lead wire. The last is the receiving amplifier circuit.
  • the dual-chamber or multi-chamber model further includes a test platform for detecting distortion as shown in FIG. 5. The system is to measure a high-precision resistance network, and then get the received frequency response. Since the transmitted current at each frequency is zero phase, the measured phase response is the total distortion of the system. This distortion also includes amplitude distortion, which needs to be corrected.
  • the invention also provides a technique for measuring the R and C values of the dual cavity model. Multi-chamber models can be handled similarly.
  • 10 frequency responses are provided at a rate of 718 Hz to perform dual-chamber model measurements. These 10 frequency responses come from the demodulation of the received signal, and they are used to estimate the integrated R and C values. Therefore, the dual-chamber R and C values are estimated to be 718 times per second, which should be high enough to show cardiovascular changes. More frequency response can be used, which requires more calculations.
  • the resistance and capacitance of the target tissue changes with the cardiac cycle to prove the correctness of the dual-chamber model.
  • Some non-invasive experiments can also verify some necessary conditions.
  • Table 1 provides 4 sets of tests to verify the correctness of the two-chamber model. Among them, the first group of experiments are measurements under normal conditions; the second group of experiments adds a mixture of salt and water under the receiving electrode, extending 1.5 cm toward the emitter; the third group of experiments adds a layer under the emitter and receiving electrode Wet paper towels with dimension E, 0.4 mm thick; the fourth group of experiments replaced the wet paper towels in 3 with 4.5 mm thick fresh pigskin. All electrodes are attached to the same marking point. These experiments prove the additivity, that is, changing the peripheral resistance and capacitance, the organization should not change.
  • the system includes a terminal, an accelerator, and a processor, wherein the terminal includes:
  • OFDM orthogonal frequency division multiplexing
  • One or more sensors for transmitting multiple alternating currents generated in the human body or animals, and sensing and receiving alternating currents modulated by changes in the tissues of the human body or animals;
  • One or more amplifiers for amplifying and digitally converting the received AC current into a digital signal
  • the preprocessing module uses Orthogonal Frequency Division Multiplexing (OFDM) technology to segment the received digital signal into OFDM symbol sequences, and then uses Fast Fourier Transform (FFT) to demodulate and separate the digital signal; and then filter Signal after separation;
  • OFDM Orthogonal Frequency Division Multiplexing
  • FFT Fast Fourier Transform
  • the accelerator is used to calculate fast Fourier transform (FFT) or orthogonal frequency division multiplexing (OFDM);
  • the accelerator is used to calculate real-time channel estimation and system identification
  • the accelerator is used to calculate the relevant resistance and capacitance values according to the digital signal
  • the processor is configured to use the resistance and capacitance values to estimate the state of the tissue.
  • the processor can be a single computer or multiple computers or an array of math accelerators; the terminal also includes processing software and a man-machine interface that connects the human and the system.
  • the computer can be remote, and the person (doctor) can remotely observe the system working in real-time mode.
  • the present invention provides a system/method for examining the correlation between changes in body resistance and capacitance and body fluids and cardiovascular circulatory tissue characteristics.
  • the present invention provides a system/method for extracting characteristic information from the resistance and capacitance of tissues in the body to represent human hemodynamics and body fluid status, such as the slope value of the resistance and capacitance change curve, and the slope value of the first derivative , Time period, normalized amplitude change, integrated shape area, ratio of different states, but not limited to these.
  • the present invention provides a system/method for correlating the calculated resistance and capacitance changes of the target tissue with arterial elasticity.
  • the present invention provides a system/method for correlating the calculated resistance and capacitance changes of the target tissue with the myocardial problem state.
  • the present invention provides a system/method for changing the frequency and frequency value, timing and intensity of AC current.
  • the present invention provides a system/method for using all the above information to assess the health status of cardiovascular circulation, including body fluid status.
  • Fig. 1 is a schematic diagram of terminal system settings provided by an embodiment of the present invention.
  • “1” is the human body
  • “A”, “B”, “C”, “D” and “E” are electrodes or contacts connected to the human body or animal body (the schematic diagram uses the human body as an example)
  • 2" is a signal generator that generates a wideband signal composed of multi-frequency components.
  • the generated signal is connected to "A” and “D” by wires or cables "5" and “6". Select “A” and “D” so that the generated or stimulated signal can pass through the relevant arteries, lungs, and heart, so that in this case, pass through the thoracic cavity through several major arteries.
  • the signal flow follows the longitudinal direction of the blood flow or artery.
  • the generated signal passes through the human subject from "A” to "D” or “D” to "A”.
  • “3” is a signal detector, which collects from points “B” and “C", “B” and “E” and “E” and “C” through wires or cables "8", “9” and “10” Voltage signal.
  • Point “E” is a special point, which can be composed of a pair of electrodes, which can both output and receive.
  • "4" is the signal processor, which controls and coordinates "2" and "3”. "4" also processes the collected signals from “B”, “C” and “E” and extracts biological information from them.
  • FIG. 2 is a schematic diagram of the function or structure of a terminal system provided by another embodiment of the present invention.
  • the terminal can not only acquire signals, but also send excitation currents to the tissues of the human or animal body.
  • "25" is a signal generator that works in both time domain and frequency domain.
  • "25” generates a multi-frequency signal.
  • a multi-frequency signal is the sum of multiple sine or cosine waves.
  • a multi-frequency signal is the sum of multiple tones.
  • the signal generator "25” converts tones into multiple sinusoidal signals in the time domain.
  • the generated digital sinusoidal signal passes through the digital-to-analog converter "26" and becomes an analog signal, which is amplified by an analog amplifier "11” to drive a broadband current pump device “12” to output broadband current.
  • an analog amplifier "11” to drive a broadband current pump device "12” to output broadband current.
  • Low-power multi-frequency sine waves enter the human body through the contacts "A” and "D”.
  • the human or animal body as a complex medium will modulate the current. This modulated current and other bioelectric signals will be picked up from points "B” and “C", "B” and “E”, and "E” and "C”.
  • the signal after "27", the signal enters the impedance diagram ICG amplifier through one path, and enters the biological signal amplifier through another path.
  • Impedance ICG signals and biological signals require different gains and different filters. Specifically, the ICG signal enters the ICG amplifier group "14". The biological signal enters the biological signal amplifier group "28".
  • the ICG signal is digitally converted by the high-resolution ADC ("IGC Hi-RES ADC BANK”) "15”, which is a high-resolution and high-speed analog-to-digital converter group.
  • the biological signal is digitized by a lower resolution ADC ("Bio-ADC BANK”) "29”, which is a low resolution and low sampling rate analog-to-digital converter group.
  • the digital signal will be processed by the digital signal processor "16".
  • the digital signal processor "16" preprocesses the digital signal, such as demodulating, filtering, and extracting different biological signals.
  • Figure 3 is a schematic diagram of a system structure for implementing the method of the present invention provided by another embodiment of the present invention.
  • the terminal system “19” performs some preprocessing tasks, such as demodulation and filtering, and is not limited to these tasks.
  • the terminal system “19” can also have its own man-machine interface.
  • the terminal system "19" is connected to the math accelerator "21" through “24".
  • the math accelerator "21” is used to perform system identification or channel estimation calculations to obtain RC model values.
  • the intermediate result will be sent to the local computer "20".
  • the local computer "20" completes all final processing, such as parameter calculation, feature extraction, and data analysis.
  • the results and data of the local computer "20” may also be stored in the database server "22", and the database server "22" may be a cloud server. Therefore, the analysis results and data can be retrieved from the local computer "20" and/or the cloud server.
  • Figure 4 is a schematic diagram of a multi-chamber model measurement circuit provided by another embodiment of the present invention.
  • AC is a multi-frequency AC current source.
  • L1 and L4 are drive leads that contact the main body.
  • L2 and L3 are the receiving leads that also contact the main body.
  • Zo is the impedance of the connecting cable.
  • Cs is the skin capacitance of the subject.
  • Rs is the subject's skin resistance.
  • Cp, Rp, “Cs”, “Rs”, “Ci” and “Ri” constitute the organizational RC model.
  • Cp is the capacitance of the peripheral or connecting tissue
  • Rp is the resistance of the periphery or connecting tissue
  • Ci is the capacitance of the blood circulatory system or tissue of interest
  • Ri is the resistance of the blood circulatory system or target tissue
  • Cs is the capacitance of the connecting tissue between the receiving electrodes and the cardiovascular tissue in parallel
  • Rs is the resistance of the connecting tissue between the receiving electrodes and the cardiovascular tissue in parallel.
  • the multi-chamber model can be simplified into a two-chamber model by removing "Cs" and "Rs". Two chambers RC are connected in series. Using the three-chamber RC model can be closer to the real situation, but requires more calculations, and its stability becomes worse.
  • FIG. 5 is a schematic diagram of measuring a pure resistance response with an external resistance network provided by another embodiment of the present invention.
  • "40” is the system provided by the present invention
  • "41” is the resistance network under test
  • "42” is the lead wire.
  • the system response measured by this platform is the overall response from theoretical transmission to the final actual reception. It includes the transmitting and receiving characteristics of the system, and the characteristics of the lead wires.
  • Figures 6a-6c show the time-domain signal and frequency response of the system on the measurement resistor network provided by another embodiment of the present invention.
  • Figure 6a shows a period of time domain signal obtained after receiving separation, that is, an OFDM symbol.
  • Figure 6b is the amplitude frequency response, they show some system defects with different attenuation, which should be corrected before measuring the human body.
  • Figure 6c is the phase frequency response. Since only 10 tones are for determining the phase, the others are random. So the overall look is random.
  • Figures 7a-7b are waveforms of 10 synchronous tones of a theoretical transmission provided by another embodiment of the present invention.
  • the phase and amplitude of each tone are controllable and adjustable.
  • Fig. 7a is the result of 1024-point inverse fast Fourier transform (IFFT), that is, one OFDM symbol.
  • Figure 7b is a signal with a 4 times sampling rate of 1024 points. This signal is repeatedly sent to the digital-to-analog converter (DAC) to generate a periodic analog signal.
  • DAC digital-to-analog converter
  • Fig. 8 is a time domain signal actually received by a system provided by another embodiment of the present invention.
  • the small amplitude part of the front end is the internal resistance measurement signal
  • the subsequent large amplitude sequence is the external human body measurement signal.
  • the internal frequency response is used to correct the external frequency response to reduce the random error of the system.
  • the large pulses in the internal sequence are pseudo ECG data because the ECG signal is combined in a high-frequency signal.
  • Fig. 9 shows the amplitude frequency response of a human test provided by another embodiment of the present invention. Its attenuation at the high frequency end is greater than the resistance, indicating that the human body has capacitance.
  • Figures 10a-10b are respectively the amplitude and phase response of the frequency modulation of the internal resistor 10 provided by another embodiment of the present invention. Its phase clearly indicates that the system has phase distortion. This is due to the transmitter circuit. This is what we need to correct. There is a small high-frequency attenuation in the amplitude, which also needs correction.
  • Figures 11a-11b are respectively measuring the amplitude and phase response of 10 tones of the human body provided by another embodiment of the present invention. Its changes are greater than internal ones.
  • Figures 12a-12b are respectively the amplitude and phase responses of 10-tones corrected by internal and external resistors according to another embodiment of the present invention. This is the true frequency response of the human body. The amplitude response attenuates more at higher frequencies. The phase response shows more delay at higher frequencies. They show that the human body frequency response is more like an RC system.
  • FIG. 13 is a frequency response (point) of the human body 10 tones provided by another embodiment of the present invention and its system transfer function (line) after system identification. From this system transfer function, the multi-chamber resistance and capacitance model can be obtained. It shows the frequency response of the human body for the second-order RC human body model. The measured frequency response perfectly matches the 2nd order RC model. No Cole model behavior is observed here. The reason should be that blood is the main resistance. It may make the Cole center frequency higher. We model the target organization with a small segmental linear model.
  • Figures 14a-14c are the arterial chamber results of a dual-chamber model of aortic measurement provided by another embodiment of the present invention.
  • Ra is the resistance of the aortic chamber model
  • Ca is the capacitance of the aortic chamber model. They followed the heartbeat closely.
  • arteries Before the end of diastole, arteries have minimal blood reserves. The resistance is the highest. The lowest capacitance. At the end of systole, the artery has the largest volume. The resistance is the smallest and the capacitance is the largest.
  • Figures 15a-15c are the peripheral chamber results of a dual-chamber model of aortic measurement provided by another embodiment of the present invention.
  • Rp is the resistance of the peripheral tissue chamber model
  • Cp is the capacitance of the peripheral tissue chamber model. They do not show simple rhythmic changes in the heartbeat.
  • Figures 16a-16c are the heart chamber results of a dual-chamber model of ventricular measurement provided by another embodiment of the present invention.
  • Rh is the resistance of the heart chamber model
  • Ch is the capacitance of the heart chamber model. They strongly follow the heartbeat.
  • the heart At the end of diastole, the heart has the largest blood. The resistance is the smallest. The capacitance is the largest.
  • the heart At the end of systole, the heart has the smallest volume. The resistance is the largest and the capacitance is the smallest.
  • Figures 17a-17c are the peripheral chamber results of a dual-chamber model of ventricular measurement provided by another embodiment of the present invention.
  • Rp is the resistance of the peripheral tissue chamber model
  • Cp is the capacitance of the peripheral tissue chamber model. The heart beat has not changed significantly.
  • Figures 18a-18c are the arterial chamber results of a dual-chamber model of upper chest measurement provided by another embodiment of the present invention.
  • Ru is the resistance of the upper thoracic cavity model, which has the thoracic artery and heart
  • Cu is the capacitance of the upper thoracic cavity model. They strongly follow the heartbeat.
  • the arteries Before the ventricles are compressed, the arteries have minimal blood reserves. The resistance is the highest. The lowest capacitance.
  • 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 19a-19c are the peripheral chamber results of a dual-chamber model of upper chest measurement provided by another embodiment of the present invention.
  • Rp is the resistance of the peripheral tissue chamber model
  • Cp is the capacitance of the peripheral tissue chamber model. They did not change as clearly as the upper chest model.
  • Figures 20a-20c are the arterial/venous chamber results of a two-chamber model of right lung measurement provided by another embodiment of the present invention.
  • “Rright lung” is the resistance of the right pulmonary artery/venous chamber model
  • “Cright lung” is the capacitance of the right pulmonary artery/venous chamber model. They vary by heartbeat.
  • Figures 21a-21c are the peripheral chamber results of the dual-chamber model of the right lung measurement provided by another embodiment of the present invention.
  • Rp is the resistance of the right lung peripheral tissue chamber model
  • Cp is the capacitance of the right lung peripheral tissue chamber model. They also change with the heartbeat.
  • Figures 22a-22c are the arterial/venous chamber results of a dual-chamber model of left lung measurement provided by another embodiment of the present invention.
  • "RLeft Lung” is the resistance of the left pulmonary artery/venous chamber model
  • “CLeft Lung” is the capacitance of the left pulmonary artery/venous chamber model. They vary by heartbeat.
  • Figures 23a-23c are the results of the peripheral chamber of the dual-chamber model of the left lung measurement provided by another embodiment of the present invention.
  • Rp is the resistance of the left lung peripheral tissue chamber model
  • Cp is the capacitance of the left lung peripheral tissue chamber model. They also change with the heartbeat.
  • the present application proposes a non-invasive method and system for detecting tissue characteristic information in the body. It applies multiple alternating currents of different frequencies to the human body at the same time. After receiving the modulated voltage signal, it demodulates the received signal, Then, it extracts information from the cardiovascular system and surrounding tissues from the specified frequency carrier. By performing system recognition or channel estimation procedures, the information is separated from the cardiovascular system and surrounding tissues. Calculate the resistance and capacitance of the cardiovascular system and its surrounding tissues respectively, and use the calculated resistance and capacitance to represent the state of body fluids and cardiovascular circulation; thus, the corresponding state information can be accurately and reliably obtained, and the target tissue can be accurately measured. To get its health status.

Abstract

一种用于检测体内组织特征信息的非侵入性方法及系统，其将多个不同频率的同步交流电流应用于人体，这些交流电流通过逆快速傅里叶变换（IFFT）或正交频分复用（OFDM）的方法产生。接收到经体内调制电压信号后，利用快速傅里叶变换（FFT）或正交频分复用（OFDM）解调接收的信号，然后，从指定频率的载波中提取来自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，以将信息与心血管循环系统和周围组织分开。分别计算心血管系统及其周围组织的电阻和电容，利用计算的电阻和电容表示体液和心血管循环组织的状态。由此能够准确、可靠的获取相应的状态信息，实现对目标组织的准确测量。

Description

一种用于检测体内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检测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无创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。它们只能间接代表心血管状态。而且，由于它们是频率相关的，它们将受到频率选择性影响。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是周围组织阻抗和目标组织阻抗的混合结果；但有些情况难确定哪个占主导地位。因此，混合阻抗在个人间变化；即使是同一个人，它也会因不同的组织状态而异。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，生物组织的特征表现在导体和非导体。导体通过电导测量(电阻倒数)，非导体可以通过电容或介电常数测量。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，因此交流电压将具有相变。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。
任何组织的变化基本上都会导致其电阻(或导)和电容的变化。因此，为了呈现组织的变化，组织电阻和电容变化的测量比混合的生物阻抗和生物电抗更可靠，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。人们普遍认为组织的信息主要在10KHz到1MHz的频带内。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)。快速(逆)傅里叶变换(FFT/IFFT)或正交频分复用(OFDM)方法是产生和解调同步多频率的常用方法。各个频率相位可控，任意调整。这是它优于随机序列产生的准多频同步信号。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。
发明内容
本发明为解决现有技术中存在的问题，提出一种用于检测体内组织特征信息的非侵入性方法及其系统，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，以进一步获知人体或生物体的状态。所述方法主要用于生物体的健康状态监测，心血管系统的弹性力学测量验证，以及主要用于非治疗目的的信息检测。
为实现上述目的，本发明提供了一种技术方案：
一种用于检测体内组织特征信息的非侵入性方法，所述方法用于捕捉体液、血流、和/或心血管循环组织的变化，所述方法包括：利用逆快速傅里叶变换(IFFT)产生具有正交频分复用(OFDM)符号特征的不同频率的多个同步交流电流，并传输至人体或动物体内；接收由人体或动物体内组织及其变化调制的交流电流；将所述调制的交流电流放大并数字转换为数字信号；预处理所述数字信号，所述预处理包括分段所述数字信号成为正交频分复用(OFDM)符号序列，利用快速傅里叶变换(FFT)对所述正交频分复用(OFDM)符号序列解调，得到频域信号；根据所述频域信号估计目标组织的状态。
优选地，所述利用逆快速傅里叶变换(IFFT)或正交频分复用(OFDM) 同时产生不同频率的多个同步交流电流包括，从频域到时域产生同步的不同频率的多个所述交流电流，其中，不同频率的所述交流电流是周期性的，所述交流电流的强度、相位和/或频率是可调的。
优选地，所述接收由人体或动物体内组织变化调制的交流电流包括，确定所述交流电流的周期，并在每个所述周期上同步接收所述调制的交流信号。
优选地，所述根据所述频域信号估计目标组织的状态包括：分离所述频域信号，并对分离后的所述频域信号进行滤波处理；根据所述频域信号计算电阻和电容值；使用所述电阻和电容值估计所述目标组织的状态。
优选地，所述分离所述频域信号包括，在所述频域信号的复阻抗上，通过系统识别和信道估计方法计算人体系统传递函数。
优选地，所述计算目标组织和外围组织的电阻和电容值包括，根据所述人体系统传递函数计算所述目标组织和外围组织的电阻和电容值。
优选地，所述使用所述电阻和电容值估计所述目标组织的状态包括使用所述电阻和电容值进行多室建模，每个腔室由并联的电阻和电容组成，腔室之间采用串联、并联或串并联方式连接。
优选地，所述多室建模可以是双室建模，其中连接组织在电极和目标组织之间。
优选地，所述频率的范围为10KHz到1MHz。
为实现上述目的，本发明还提供了一种技术方案：
一种用于实现上述任一方法的系统，所述系统包括终端和处理器，其中，所述终端包括：发生器，用于利用逆快速傅里叶变换(IFFT)产生具有正交频分复用(OFDM)符号特征的不同频率的多个同步交流电流；一个或多个传感器，用于将多个所述交流电流传输至人体或动物体内，以及接收由人体或动物体内 组织变化调制的交流电流；一个或多个放大器，用于将所述调制的交流电流放大并数字转换为数字信号；以及预处理模块，利用OFDM符号的特性，分段输入数字信号成为OFDM符号序列。利用快速傅里叶变换(FFT)解调正交频分复用(OFDM)符号以得到频域信号；所述处理器，用于计算电阻和电容值和/或使用所述电阻和电容值估计目标组织的状态。
优选地，所述发生器用于从频域到时域产生不同频率的多个所述交流电流，即OFDM符号，其中，不同频率的所述交流电流是周期性的，即OFDM符号重复输出。所述交流电流的强度、相位和/或频率是可调的。
优选地，所述处理器用于确定所述交流电流的周期，即确定OFDM符号的长度，并在每个所述周期上同步接收所述调制的交流信号。
优选地，所述传感器用于从不同的部位采集单个或多个数据。
优选地，所述预处理模块还用于分离所述频域信号，并对分离后的所述频域信号进行滤波处理。
优选地，所述系统还包括加速器，所述加速器用于根据所述频域信号计算电阻和电容值，所述计算包括使用系统识别或信道估计程序。
优选地，所述处理器通过所述电阻和电容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、并联或串并联连接。
优选地，所述系统可以包括数据库，用于存储所述处理器的处理结果和数据，所述处理器可以检索所述数据库。
优选地，所述处理器可以是远程的，可以远程观察系统在实时模式下工作。
优选地，所述终端还包括人机界面，用于控制系统和/或显示结果。
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，与现有技术相比，其将多个不同频率的同步周期性交流电流同时应用于人体，在接 收到经体内组织调制的信号后，解调并从指定频率的载波中提取来自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，得到心血管循环系统和周围组织的组合信息。然后从系统传递函数中计算心血管系统及其周围组织的电阻和电容，这样就把心血管系统及其周围组织区分开。利用计算的电阻和电容以表示体液和心血管循环组织的状态。由此能够准确、可靠的获取相应的状态信息，实现对目标组织的准确测量。
附图说明
下面结合附图和实施例对本发明进一步说明。
图1是本发明的优选实施例的终端系统示意图；
图2是本发明的优选实施例的终端的功能或结构示意图；
图3是本发明的优选实施例的系统结构示意图；
图4是本发明的优选实施例的多室模型测量电路示意图；
图5是本发明的优选实施例的系统测试电路结构示意图；
图6a-6c是本发明的优选实施例的系统测试在测量电阻网络上的时域信号和频率响应结果的示意图；
图7a-7b是本发明的优选实施例的理想发射的10个同步频调的波形图；
图8是本发明的优选实施例的系统实际接收信号的示意图；
图9是本发明的优选实施例的接收外部信号的示意图，即人体信号示意图；
图10a-10b是本发明的优选实施例的内部电阻网络的幅度和相位响应示意图；
图11a-11b是本发明的优选实施例的实测的人体的幅度和相位响应示意图；
图12a-12b是本发明的优选实施例的矫正过的人体的幅度和相位响应示意 图；
图13是本发明的优选实施例的系统识别后的传递函数和人体的频率响应示意图；
图14a-14c是本发明的优选实施例的主动脉测量的双室模型的动脉结果示意图；
图15a-15c是本发明的优选实施例的主动脉测量的双室模型的外围结果示意图；
图16a-16c是本发明的优选实施例的心室测量的双室模型的心室结果示意图；
图17a-17c是本发明的优选实施例的心室测量的双室模型的外围结果示意图；
图18a-18c是本发明的优选实施例的上胸部测量的双室模型的动脉结果示意图；
图19a-19c是本发明的优选实施例的上胸部测量的双室模型的外围结果示意图；
图20a-20c是本发明的优选实施例的右肺测量的双腔模型的动脉/静脉结果示意图；
图21a-21c是本发明的优选实施例的右肺测量的双腔模型的外围结果示意图；
图22a-22c是本发明的优选实施例的左肺测量的双腔模型的动脉/静脉结果示意图；
图23a-23c是本发明的优选实施例的左肺测量的双腔模型的外围结果示意图。
具体实施方式
现在结合附图对本发明作进一步详细的说明。这些附图均为简化的示意图，仅以示意方式说明本发明的基本结构，因此其仅显示与本发明有关的构成。
本发明涉及检测生物体内组织的电特性的无创技术，例如组织的电阻和电容及其变化模式。其目标是捕捉体液变化、血液流动和心血管循环组织的变化，用于生物体的健康状态监测，心血管系统的弹性力学检测验证，也用于非治疗目的的信息检测。
本发明提供的方法用于检测人或动物的组织状态，包括体液和血流、动脉、心脏和肺的状态，通过提取组织的电阻和电容变化以获取与心血管循环、体液和心血管组织(包括心脏和肺)状态之间的定量相关性。基于此，本发明一个实施例提供的测量方法至少包括：
1.利用逆快速傅里叶变换(IFFT)产生具有正交频分复用(OFDM)符号特征的不同频率的多个同步交流电流，并传输至人体或动物体内。
具体的，在发射端，本实施例使用数字信号处理技术，例如逆快速傅里叶变换(IFFT)或正交频分复用(OFDM)，从频域到时域产生多个不同频率的交流电流(AC)，也称作正交频分复用(OFDM)符号序列。该多个不同频率的交流电流是周期性的，以OFDM符号长度为周期，并且将多个不同频率的交流电流同时应用于人体。其中，所述交流电流的强度、相位和/或频率是可调的。
2.接收由人体或动物体内组织变化调制的交流电流。
具体的，在接收端，确定交流电流的周期，即OFDM符号的长度，并在每个周期上同步接收调制的交流信号，即被人体调制过的OFDM符号。可选实施例中，根据OFDM符号的特征，找出它的周期和起始点。然后对每一个OFDM 符号进行解调，得到频域信号。
可选实施例中，不同频率的多个交流电流通过电极同时注入人体，并与一些外部电子部件形成环路。当电流在人体内传播时，它们受到在环路中的身体组织和组织变化的调节；接收回路与注入回路部分重叠，这样就能检测到被重叠部分人体组织调制的信号。
3.将调制的交流电流放大并数字转换为数字信号。
可选实施例中，接收经人体或动物体调制的交流电流可以是电流信号、或转化的电压信号，它们都统称调制过的OFDM符号序列。经放大后转换成数字信号。可选实施例中，心电图(ECG)信号也叠加在调制信号中，可以通过在数字转换前进行低通滤波将心电图(ECG)分离出来，单独放大并转换成数字格式信号，进行下一步处理。
4.预处理数字信号，预处理包括分段数字信号成为正交频分复用(OFDM)符号序列，利用快速傅里叶变换(FFT)对正交频分复用(OFDM)符号序列解调，得到频域信号。
具体的，根据发射信号的周期和信号特性，即OFDM符号的周期和特性，分段数字信号成为OFDM符号的序列，利用快速傅里叶变换(FFT)对每个OFDM符号进行解调，得到频域信号。
可选实施例中，在接收的数字信号中寻找OFDM符号的特征，周期是已知的。找到特征段后，就可以决定OFDM符号的起始点。这时的接收信号就变成以OFDM符号为单位的序列。可以对每个OFDM符号使用快速傅里叶变换(FFT)解调，把信号转换到频域。
5.根据频域信号估计目标组织的状态。
具体的，分离频域信号，并对分离后的频域信号进行滤波处理；根据频域 信号计算人体组织的系统传递函数，再从该系统传递函数计算组织电阻和电容值；使用电阻和电容值估计目标组织的状态。
可选实施例中，同时检测不同频率(也叫频调)的多个交流电压的实部和虚部，或幅度和相位的变化。由多个频调的幅度和相位计算人体的系统传递函数，再从人体的系统传递函数的参数中计算人体内组织的电阻和电容。
利用计算的电阻和电容以表示体液和心血管循环组织的状态。具体的，使用电阻和电容值进行多室建模，每个腔室由并联的电阻和电容组成，腔室之间采用串联、并联或串并联方式连接。
可选实施例中，双室RC(电阻和电容)模型用于模拟目标组织。可以用多腔室来模拟人体。如胸腔测量，一室代表动脉，和/或心房和心室，这是心血管循环系统的主要部分。另一个室代表电极和心血管循环系统之间的连接组织。每个腔室由集成的电阻电容组成的并联RC网络表示。两个腔室串联连接，因为心脏或动脉系统不直接连接在电极上。连接组织总是在测量电极和心脏动脉之间。然后，系统识别或信道估计技术用于计算整合的R(电阻)和C(电容)值。R和C值用于估计体液、血流和心血管循环组织。双室模型的优点是将心血管循环系统与周围组织分开。在双室模型的基础上，还有三室模型，一个并联RC网络再并联两个相串联的并联RC网络，如图4所示。可选实施例中，三室模型更适合真实的人体组织，但计算量大，而且稳定性差。
本发明另一个实施例提供的方法包括：
1.利用逆快速傅里叶变换(IFFT)产生具有正交频分复用(OFDM)符号特征的不同频率的多个同步交流电流，并传输至人体或动物体内。
具体的，在发射端，本实施例使用数字信号处理技术，例如用逆快速傅里叶变换(IFFT)产生正交频分复用(OFDM)符号，即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，周期是OFDM符号的长度。并且将多个不同频率的交流电流同时应用于人体。其中，所述交流电流的强度、相位和/或频率是可调的。
可选实施例中，这些交流电流合成的一个周期(OFDM符号)如图7a和图7b所示。其中，图7a是通过1024点的逆快速傅里叶变换(IFFT)的原始时序图的结果(OFDM符号)。这里面有10个正交的同步的正弦波。图7b是4倍原始时序图的结果。在时域上，这个序列无穷地重复。
2.接收由人体或动物体内组织变化调制的交流电流。
具体的，在接收端，确定交流电流的周期，即OFDM符号的长度，并在每个周期上同步接收被人体调制过的OFDM符号的交流信号。可选实施例中，根据OFDM符号的特征，找出它的周期和起始点。然后对每一个OFDM符号进行解调，得到频域信号。
可选实施例中，不同频率的多个交流电流通过电极同时注入人体，并与一些外部电子部件形成环路。可选实施例中，当电流在人体内传播时，它们受到在环路中的身体组织和组织变化的调节；接收回路与注入回路部分重叠，这样就能检测到被重叠部分人体组织调制的信号。
可选实施例中，在接收端采样得到的上百万点的序列，如图8所示。前端小幅度的部分是内部电阻的测量序列，后面大幅度的序列是外部测人体的序列。可选实施例中，每次测量都用内部的频响去矫正外部的频响，以减少系统的随机误差。内部电阻中大幅度的脉冲是伪心电数据，因为心电信号被组合在高频信号里了。可选实施例中，在接收到调制电压信号后，根据事先确定的系统延时，找出接收OFDM符号的起始点，把接收信号变成了OFDM符号序列，即接收端同步于发射端。
3.将调制的交流电流放大并转换为数字信号。
可选实施例中，接收经人体或动物体调制的交流电流在接收回路中可以是电流信号或电压信号。可选实施例中，心电图(ECG)信号也叠加在调制信号中，可以通过在数字转换前进行低通滤波将心电图(ECG)分离出来。根据不同的需求对不同的信号进行采样，将采样的信号调制放大并转换成数字格式信号，进行下一步处理。
4.预处理数字信号，预处理包括分段数字信号成为正交频分复用(OFDM)符号序列，利用快速傅里叶变换(FFT)对正交频分复用(OFDM)符号序列解调，得到频域信号。
具体的，根据发射信号的周期和信号特性，即OFDM符号的周期和特性，分段数字信号成为OFDM符号的序列，利用快速傅里叶变换(FFT)对每个OFDM符号进行解调，得到频域信号。
可选实施例中，解调同步的接收信号。在接收的数字信号中寻找OFDM符号的特征，周期是已知的。找到特征段后，就可以决定OFDM符号的起始点。这时的接收信号就是以OFDM符号为单位的序列。可以对每个OFDM符号使用快速傅里叶变换(FFT)解调，把信号转换到频域。
可选实施例中，如图9所示，这是一个幅度频响图。系统接收到10个频调和几个干扰，干扰对那10个频调没有影响。从这个频响中抽出这10个频调的响应。一共得到10个内部和10个外部的频调。内部10个频调的响应如图10所示。外部10个频调的响应如图11a-11b所示。其中，外部的频响中包含内部的频响。
可选实施例中，外部频响除去内部频响的示意图如图12a-12b所示。这里也需要外部电阻网络进行矫正，以此得到人体的频响。
可选实施例中，得到了人体系统的频率响应后进行系统识别。但它对相位噪声也很敏感。所以在得到相位和幅度的时间序列后，要对他们进行滤波处理。人的心跳基本在1-2赫兹，所以一个10赫兹的低通滤波器是可以用的。
5.分离频域信号，并对分离后的频域信号进行滤波处理。
具体的，在假设了人体多室模型之后，进行系统识别。如果系统是可识别的，就会得到系统传递函数的各个正系数，也就是得到系统传递函数的负根。如果得到正根或复数根，就说明模型不对。其原因在于一些音调的干扰影响较大。每个人的干扰可能出现在不同的频率上。这就需要10个频调的频率是可调的。
系统识别的过程就是求频率响应上的测量点的最小误差。可选实施例中，采用10点(频率)测量，如果要求精度高，可以增加频率点。但信号的总能量是受人体安全限制的。所以增加频率点会降低每个频调上的信噪比。
6.计算目标组织和外围组织的电阻和电容值。
具体的，根据人体系统传递函数计算目标组织和外围组织的电阻和电容值。这可以从电阻电容网络中直接推出。
可选实施例中，从窄频带角度看，在10KHz至1MHz之间，组织RC值随频率变化比较小。将两室电阻和电容的变化与心电图(ECG)定时参考相结合，可以估计心血管状态。
可选实施例中，根据图9所示的10个频调的响应中提取信息。该信息来自心血管系统和周围组织。然后，执行系统识别或信道估计程序，算出系统传递函数。在此例中，我们得到的系统传递函数是：
Figure PCTCN2019082729-appb-000001
由此函数算出的两室模型是(由20欧电阻矫正)：
60.83欧(ohms)并联6.06纳法(nF)和
10.37欧(ohms)并联4.23微法(μF)。
这里不能区分心血管循环系统和周围组织，还需要其他的信息来推断。可选实施例中，使用心电图(ECG)作为参考。同时结合外加电场的位置和分布。这些电阻和电容形成4个时间序列。它们和心电图组合，由此可把不同的信息从心血管循环系统和周围组织分开，得到心血管系统及其周围组织的电阻和电容。
7.使用电阻和电容值估计目标组织的状态。
具体的，使用所述电阻和电容值进行多室建模，每个腔室由并联的电阻和电容组成，腔室之间采用串联、并联或串并联方式连接。
可选实施例中，双室RC(电阻和电容)模型用于模拟目标组织。可以用多腔室来模拟人体。如胸腔测量，一室代表动脉、心房和心室，这是心血管循环系统的主要部分。另一个室代表电极和心血管循环系统之间的连接组织。每个腔室由集成的电阻电容组成的并联RC网络表示。两个腔室串联连接，因为心脏和动脉系统不直接连接在电极上。连接组织总是在测量电极和心脏动脉之间。然后，系统识别或信道估计技术用于计算整合的R(电阻)和C(电容)值。R和C值用于估计体液，血流和心血管循环组织。双室模型的优点是将心血管循环系统与周围组织分开。在双室模型的基础上，还有三室模型，一个并联RC网络再并联两个相串联的并联RC网络，如图4所示。可选实施例中，三室模型更适合真实的人体组织，但计算量大，而且稳定性差。
可选实施例中，在双室或多室模型估计中，人体系统的相位测量是最重要的。它要求硬件具有足够的带宽响应和极小的失真。由于任何系统都会带来失 真，因此需要信道估计来检测和抵消这些失真。首先失真会出现在驱动部分，就是同步多频周期性电流的产生电路里。然后是导联线。最后是接收放大电路。可选实施例中，双室或多室模型还包括如图5所示的检测失真的测试平台。该系统是测量一个高精度的电阻网络，然后得到接收的频率响应。由于发射的各个频率电流都是零相位，因此测得的相位响应就是系统的总失真。这个失真还包括幅度失真，需要进行矫正。
本发明还提供了测量双腔模型的R和C值的技术。可以类似地处理多室模型。
可选实施例中，以718Hz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，并且它们用于估计整合的R和C值。因此，双室R和C值估计为每秒718次，其应足够高以显示心血管变化。可以使用更多的频率响应，这需要更多的计算。
可选实施例中，除了波形观察目标组织的电阻电容随心动周期的变化来证明双室模型的正确性。一些无创的实验也可以验证一些必要条件。表1提供了4组测试用于验证双室模型的正确性。其中，第一组实验为正常状态下的测量；第二组实验的接收电极下方加盐和水的混合物，向发射极方向延伸1.5厘米；第三组实验在发射极和接收极下加一层有维E的湿纸巾，0.4毫米厚；第四组实验把3中的湿纸巾换成4.5毫米厚的去毛新鲜猪皮。所有的电极都贴在同样的标识点上。这些实验是证明相加性，即改变外周电阻电容，组织的不应变化。
第一组实验的正常测试给出参考值。第二组实验中，接收电极区域扩大并向发射极靠近，相当于接收回路的电流变大，因此接收的输入电压变大。由于接收电极导电面积增大，外围组织的电场分布也变了。这都会引起外围电阻电容的变化。器官的变化应该小。实验结果证明了这个推论。第三组实验中，相 当于加了一层电阻。电容变化不大。器官的电阻电容变化都应该不大。实验结果很好地证明这个推断。第四组实验中，相当于加了一层电阻和电容。其结果是总电阻增大，电容减小。由于接触面不能很好吻合，电场分布会改变，会很大地影响测量结果，所以第四的结果只有指导意义。器官的变化比例比外围的小很多，即使器官电容的绝对值比外围的小很多。这三组实验基本证明了双室模型的可加性。
Figure PCTCN2019082729-appb-000002
表1
本发明另一个实施例还提供了一种用于实现上述方法的系统，该系统包括终端、加速器、处理器，其中，所述终端包括：
从频域到时域产生多个不同频率的具有正交频分复用(OFDM)符号特性的同步周期性交流电流的发生器，具体的，利用逆快速傅里叶变换(IFFT)产生正交频分复用(OFDM)符号，以OFDM符号为时间序列同时产生不同频率的多个交流电流；
一个或多个传感器，用于将产生的多个交流电流传递到人体或动物体内，以及感知接收由人体或动物体内组织变化调制的交流电流；
一个或多个放大器，用于放大并数字转换接收到的交流电流为数字信号；
预处理模块，利用正交频分复用(OFDM)技术，把接收的数字信号分段成 OFDM符号序列，然后利用快速傅里叶变换(FFT)，解调、分离所述数字信号；再滤波分离后的信号；
所述加速器，用于计算快速傅里叶变换(FFT)或正交频分复用(OFDM)；
所述加速器，用于计算实时信道估计和系统识别；
所述加速器，用于根据所述数字信号计算相关的电阻和电容值；
所述处理器，用于使用所述电阻和电容值估计组织的状态。
其中，处理器可以是单个计算机或多个计算机或数学加速器阵列；终端还包括连接人和系统的处理软件和人机界面。计算机可以是远程的，人(医生)可以远程观察系统在实时模式下工作。
优选的，本发明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组织特征之间的相互关系的系统/方法。
本发明提供了一种系统/方法，用于从体内组织的电阻和电容中提取特征信息，以表示人体血液动力学和体液状态，例如电阻和电容变化曲线的斜率值，一阶导数的斜率值，时间段，归一化幅度变化，整合形状区域，不同状态的比率，但不限于这些。
本发明提供了一种系统/方法，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。
本发明提供了一种系统/方法，用于将计算的目标组织的电阻和电容变化与心肌问题状态相关联。
本发明提供了一种改变AC电流的频率和频率值，时序和强度的系统/方法。
本发明提供了一种系统/方法，用于使用所有上述信息来评估心血管循环的健康状态，包括体液状态。
通过使用上述方法及系统可以实现针对目标组织的准确检测，提高了检测 的准确性。
下面结合附图说明本发明实施例进行说明。
图1为本发明一个实施例提供的终端系统设置的示意图。
具体的，“1”是人类主体，“A”、“B”、“C”、“D”和“E”是连接到人体或动物体(示意图以人体为例)的电极或触点；“2”是产生由多频分量组成的宽带信号的信号发生器。产生的信号通过电线或电缆“5”和“6”连接到“A”和“D”。选择“A”和“D”使得产生的或刺激的信号可以通过相关的动脉，肺和心脏，以使得在这种情况下，通过几个主要动脉通过的胸腔。信号流遵循血流或动脉的纵向方向。所产生的信号通过人类对象内部从“A”到“D”或“D”到“A”。“3”是信号检测器，它通过电线或电缆“8”，“9”和“10”从点“B”和“C”，“B”和“E”以及“E”和“C”收集电压信号。“E”点是一个特殊点，它可以是一对电极组成，既能输出，也能接收。“4”是信号处理器，它控制并协调“2”和“3”。“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为本发明另一个实施例提供的终端系统的功能或结构示意图。
具体的，该终端不仅可以获取信号，还可以将激励电流发送到人体或动物体的组织中。其中，“25”是在时域和频域都工作的信号发生器。可选实施例中，“25”产生多频信号。在时域中，多频信号是多个正弦或余弦波的总和。在频域中，多频信号是多个频调的总和。信号发生器“25”将频调转换为时域中的多个正弦信号。
可选实施例中。生成的数字正弦信号通过数模转换器“26”，并成为模拟信号，通过一个模拟放大器“11”，被放大，以驱动一个宽带电流泵设备“12”输出宽带电流。从宽带电流泵设备“12”开始，小功率的多频正弦波通过触点“A” 和“D”进入人体。作为复杂介质的人体或动物体将调制该电流。该调制的电流和其他生物电信号将从点“B”和“C”、“B”和“E”以及“E”和“C”中拾取。
可选实施例中，由于所有这些信号都很弱，它们将首先被一个模拟预放大器组“27”放大，“27”主要功能是调节将高阻抗输入信号和低阻抗输入信号转换为低阻抗输入信号。
可选实施例中，在“27”之后，信号通过一条路径进入阻抗图ICG放大器，通过另一条路径进入生物信号放大器。阻抗ICG信号和生物信号需要不同的增益和不同的滤波器。具体的，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”。
可选实施例中，信号被放大后，ICG信号由高分辨率ADC(“IGC Hi-RES ADC BANK”)“15”进行数字转换，这是一种高分辨率和高速模数转换器组。生物信号通过较低分辨率ADC(“Bio-ADC BANK”)“29”进行数字化，ADC“29”是一种低分辨率和低采样率的模数转换器组。数字信号将由数字信号处理器“16”处理。可选实施例中，数字信号处理器“16”预处理数字信号，如解调、滤波和提取不同的生物信号等。
图3为本发明另一个实施例提供的实现本发明方法的系统结构示意图。
具体的，“17”是发出激励信号的路径。“18”是从人体获得调制信号和其他生物信号的途径。可选实施例中，终端系统“19”进行一些预处理工作，如解调和过滤，而不仅限于这些任务。终端系统“19”也可以拥有自己的人机界面。
可选实施例中，终端系统“19”通过“24”连接数学加速器“21”。数学加速器“21”用于执行系统识别或信道估计的计算以获得RC模型值。中间结果将被发送到本地计算机“20”。
可选实施例中，本地计算机“20”完成所有最终处理，如参数计算、特征提取和数据分析等。可选实施例中，本地计算机“20”的结果和数据也可以存储在数据库服务器“22”中，数据库服务器“22”可以是云服务器。因此，分析的结果和数据可以从本地计算机“20”和/或云服务器中检索。
图4为本发明另一个实施例提供的多室模型测量电路的示意图。
具体的，“AC”是多频AC电流源。L1和L4是与主体接触的驱动引线。L2和L3是也接触主体的接收引线。“Zo”是连接电缆的阻抗。“Cs”是受试者的皮肤电容。“Rs”是受试者的皮肤抵抗力。“Cp”、“Rp”、“Cs”、“Rs”、“Ci”和“Ri”组成组织RC模型。其中，“Cp”是外围或连接组织的电容；“Rp”是外周或连接组织的电阻；“Ci”是血液循环系统或感兴趣组织的电容；“Ri”是血液循环系统或目标组织的电阻；“Cs”是接收电极之间和心血管组织平行的连接组织的电容；“Rs”是接收电极之间和心血管组织平行的连接组织的电阻。
可选实施例中，多室模型可以去掉“Cs”和“Rs”简化成双室模型。由两个腔室RC串联连接。使用三室RC模型，可以更接近真实情况，但需要更多计算，并且其稳定性变差。
图5为本发明另一个实施例提供的用外部电阻网络测量纯电阻响应的示意图。其中，“40”是本发明提供的系统，“41”是被测电阻网络，“42”是导联线。这个平台测的系统响应是从理论发射到最后实际接收的整体响应。它包括了系统的发射特性和接收特性，以及导联线的特性。
图6a-6c为本发明另一个实施例提供的系统在测量电阻网络上的时域信号和频率响应。有10个不同频率的主要载波具有相同的功率，代表10个频调。它们分别是14.36KHz、33.03KHz、73.24KHz、96.21KHz、116.32KHz、136.42KHz、160.83KHz、203.91KHz、280.02KHz和348.95KHz。它们携带调制信息。图6a 是接收分离后得到的一个周期的时域信号，即OFDM符号。图6b是幅度频响，它们显示了一些不同衰减的系统缺陷，在测量人体之前应予以纠正。图6c是相位频响，由于只有10个频调是确定相位，其他的是随机的。所以整体看来是随机的。
图7a-7b为本发明另一个实施例提供的一个理论发射的10个同步频调的波形。每个频调的相位和幅度可控可调。其中，图7a是1024点的逆快速傅里叶变换(IFFT)的结果，即一个OFDM符号。图7b是1024点的4倍采样速率的信号。这个信号被重复送到数模转换器(DAC)，产生周期性的模拟信号。
图8为本发明另一个实施例提供的系统实际接收的时域信号。前端小幅度的部分是内部电阻的测量信号，后面大幅度的序列是外部测人体的信号。每次测量都用内部的频响去矫正外部的频响，以减少系统的随机误差。内部序列中大幅度的脉冲是伪心电数据，因为心电信号被组合在个高频信号里了。
图9为本发明另一个实施例提供的人体测试的幅度频响。它在高频端的衰减比电阻大，说明人体有电容存在。
图10a-10b分别为本发明另一个实施例提供的内部电阻10频调的幅度和相位响应。它的相位明显表示系统有相位失真。这是由于发射电路产生的。这是我们需要矫正的。幅度有微小的高频衰减，也需要矫正。
图11a-11b分别为本发明另一个实施例提供的测量人体的10频调的幅度和相位响应。它的变化比内部的更大。
图12a-12b分别为本发明另一个实施例提供的经内部和外部电阻矫正后的10频调的幅度和相位响应。这是人体的真正的频率响应。振幅响应在较高频率上衰减得更多。相位响应在较高频率上显示更多延迟。他们表明人体频率响应更像是RC系统。
图13为本发明另一个实施例提供的人体10频调的频率响应(点)和它的系统识别后的系统传递函数(线)。从这个系统传递函数，可以求出多室的电阻和电容模型。它显示了针对2阶RC人体模型的人体频率响应。测量的频率响应与2阶RC模型完美匹配。此处未观察到Cole模型行为。原因应该是血液是主要的电阻。它可能会使Cole中心频率更高。我们以小的节段线性模型对目标组织进行建模。
图14a-14c为本发明另一个实施例提供的主动脉测量的双室模型的动脉腔室结果。Ra是主动脉腔室模型的电阻，Ca是主动脉腔室模型的电容。他们紧跟随心跳。在心脏舒张末期之前，动脉具有最小的血液储备。电阻是最高的。电容最低。在心脏收缩末期，动脉的体积最大。电阻最小，电容最大。
图15a-15c为本发明另一个实施例提供的主动脉测量的双室模型的外围腔室结果。Rp是外围组织腔室模型的电阻，Cp是外围组织腔室模型的电容。它们并没有表现出心跳的简单节奏变化。
图16a-16c为本发明另一个实施例提供的心室测量的双室模型的心脏腔室结果。Rh是心腔模型的电阻，Ch是心腔室模型的电容。他们强烈跟随心跳。在心脏舒张末期，心脏有最大的血液。电阻最小。电容是最大的。在心脏收缩末期，心脏体积最小。电阻最大，电容最小。
图17a-17c为本发明另一个实施例提供的心室测量的双室模型的外围腔室结果。Rp是外周组织腔室模型的电阻，Cp是外围组织腔室模型的电容。心脏跳动并没有明显改变。
图18a-18c为本发明另一个实施例提供的上胸部测量的双室模型的动脉腔室结果。Ru是上胸腔室模型的电阻，其具有胸部动脉和心脏，Cu是上胸腔室模型的电容。他们强烈跟随心跳。在心室压缩之前，动脉具有最小的血液储备。 电阻是最高的。电容最低。在心脏收缩末期，动脉的体积最大。电阻最小，电容最大。
图19a-19c为本发明另一个实施例提供的上胸部测量的双室模型的外围腔室结果。Rp是外周组织腔室模型的电阻，Cp是外周组织腔室模型的电容。它们并没有像上胸腔模型那样清晰地改变。
图20a-20c为本发明另一个实施例提供的右肺测量的双室模型的动脉/静脉腔室结果。“R右肺”是右肺动脉/静脉腔室模型的电阻，“C右肺”是右肺动脉/静脉腔室模型的电容。它们因心跳而异。
图21a-21c为本发明另一个实施例提供的右肺测量的双室模型的外围腔室结果。Rp是右肺外周组织腔室模型的电阻，Cp是右肺外周组织腔室模型的电容。它们也随心跳而变化。
图22a-22c为本发明另一个实施例提供的左肺测量的双室模型的动脉/静脉腔室结果。“R左肺”是左肺动脉/静脉腔室模型的电阻，“C左肺”是左肺动脉/静脉腔室模型的电容。它们因心跳而异。
图23a-23c为本发明另一个实施例提供的左肺测量的双室模型的外围腔室结果。Rp是左肺外围组织腔室模型的电阻，Cp是左肺外围组织腔室模型的电容。它们也随心跳而变化。
本申请提出的一种用于检测体内组织特征信息的非侵入性方法及其系统，其将多个不同频率的交流电流同时应用于人体，在接收到调制电压信号后，它解调接收信号，然后，它从指定频率的载波中提取来自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，以将信息与心血管循环系统和周围组织分开。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以表示体液和心血管循环的状态；由此能够准确、可靠的获取相应的 状态信息，对目标组织进行准确测量，以获取其健康状态。
以上述依据本发明的理想实施例为启示，通过上述的说明内容，相关工作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。本项发明的技术性范围并不局限于说明书上的内容，必须要根据权利要求范围来确定其技术性范围。

Claims (19)

  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/或心血管循环组织的变化，所述方法包括：
    利用逆快速傅里叶变换(IFFT)产生具有正交频分复用(OFDM)符号特征的不同频率的多个同步交流电流，并传输至人体或动物体内；
    接收由人体或动物体内组织及其变化调制的交流电流；
    将所述调制的交流电流放大并数字转换为数字信号；
    预处理所述数字信号，所述预处理包括分段所述数字信号为正交频分复用(OFDM)符号序列，利用快速傅里叶变换(FFT)对所述正交频分复用(OFDM)符号序列解调，得到频域信号；
    根据所述频域信号估计目标组织的状态。
  2. 如权利要求1所述的用于检测体内组织特征信息的非侵入性方法，其特征在于，所述利用逆快速傅里叶变换(IFFT)或正交频分复用(OFDM)同时产生不同频率的多个同步交流电流包括，从频域到时域产生同步的不同频率的多个所述交流电流，其中，不同频率的所述交流电流是周期性的，所述交流电流的强度、相位和/或频率是可调的。
  3. 如权利要求1所述的用于检测体内组织特征信息的非侵入性方法，其特征在于，所述接收由人体或动物体内组织变化调制的交流电流包括，确定所述交流电流的周期，并在每个所述周期上同步接收所述调制的交流信号。
  4. 如权利要求1-3任一项所述的用于检测体内组织特征信息的非侵入性方法，其特征在于，所述根据所述频域信号估计目标组织的状态包括：
    分离所述频域信号，并对分离后的所述频域信号进行滤波处理；
    计算目标组织和外围组织的电阻和电容值；
    使用所述电阻和电容值估计所述目标组织的状态。
  5. 如权利要求4所述的用于检测体内组织特征信息的非侵入性方法，其特征在于，所述分离所述频域信号包括，在所述频域信号的复阻抗上，通过系统识别和信道估计方法计算人体系统传递函数。
  6. 如权利要求5所述的用于检测体内组织特征信息的非侵入性方法，其特征在于，所述计算目标组织和外围组织的电阻和电容值包括，根据所述人体系统传递函数计算所述目标组织和外围组织的电阻和电容值。
  7. 如权利要求4所述的用于检测体内组织特征信息的非侵入性方法，其特征在于，所述使用所述电阻和电容值估计所述目标组织的状态包括使用所述电阻和电容值进行多室建模，每个腔室由并联的电阻和电容组成，腔室之间采用串联、并联或串并联方式连接。
  8. 如权利要求7所述的用于检测体内组织特征信息的非侵入性方法，其特征在于，所述多室建模可以是双室建模，其中连接组织在电极和目标组织之间。
  9. 如权利要求1所述的任一用于检测体内组织特征信息的非侵入性方法，其特征在于，所述频率的范围为10KHz到1MHz。
  10. 一种用于实现上述任一方法的系统，其特征在于，所述系统包括终端和处理器，其中，所述终端包括：
    发生器，用于利用逆快速傅里叶变换(IFFT)产生具有正交频分复用(OFDM)符号特征的不同频率的多个同步交流电流；
    一个或多个传感器，用于将多个所述交流电流传输至人体或动物体内，以及接收由人体或动物体内组织变化调制的交流电流；
    一个或多个放大器，用于将所述调制的交流电流放大并数字转换为数字信号；以及
    预处理模块，用于分段所述数字信号为正交频分复用(OFDM)符号序列， 利用快速傅里叶变换(FFT)对所述正交频分复用(OFDM)符号序列解调，得到频域信号；
    所述处理器，用于计算电阻和电容值和/或使用所述电阻和电容值估计目标组织的状态。
  11. 如权利要求10所述的系统，其特征在于，所述发生器用于从频域到时域产生不同频率的多个所述交流电流，其中，不同频率的所述交流电流是周期性的，所述交流电流的强度、相位和/或频率是可调的。
  12. 如权利要求10所述的系统，其特征在于，所述处理器用于确定所述交流电流的周期，并在每个所述周期上同步接收所述调制的交流信号。
  13. 如权利要求11所述的系统，其特征在于，所述传感器用于从不同的部位采集单个或多个数据。
  14. 如权利要求12所述的系统，其特征在于，所述预处理模块还用于分离所述频域信号，并对分离后的所述频域信号进行滤波处理；所述分离包括在所述频域信号的复阻抗上，通过系统识别和信道估计方法计算人体系统传递函数。
  15. 如权利要求14所述的系统，其特征在于，所述系统还包括加速器，所述加速器用于计算目标组织和外围组织的电阻和电容值，所述计算包括根据所述人体系统传递函数计算。
  16. 如权利要求15所述的系统，其特征在于，所述处理器通过所述电阻和电容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、并联或串并联连接。
  17. 如权利要求10-16所述的系统，其特征在于，所述系统可以包括数据库，用于存储所述处理器的处理结果和数据，所述处理器可以检索所述数据库。
  18. 如权利要求17所述的系统，其特征在于，所述处理器可以是远程的， 可以远程观察系统在实时模式下工作。
  19. 如权利要求10-18任一所述的系统，其特征在于，所述终端还包括人机界面，用于控制系统和/或显示结果。
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