CN113598778A - Human body data detection and analysis method based on quantum resonance - Google Patents
Human body data detection and analysis method based on quantum resonance Download PDFInfo
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
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Abstract
The invention discloses a human body data detection and analysis method based on quantum resonance, which comprises the following steps: collecting electromagnetic waves of a detector and carrying out standardization processing on the electromagnetic waves; performing wavelet transformation on the collected electromagnetic waves; the magnetic field signal after wavelet transformation is transmitted into a giant magnetoresistance sensing circuit, and the magnetic field signal is converted into a voltage signal to be output; the voltage signal output by the giant magnetic sensing circuit and the standard detection waveform code of the standard magnetic field wave corresponding to the detection item are subjected to resonance action, if the output accurate magnetic field signal and the stored standard detection waveform code are similar wave spectrums, a resonance signal is generated, and otherwise, a non-resonance signal is generated; after the resonance signal is generated, analyzing and processing the resonance signal based on three vectors of an electric field, a magnetic field and a force field and Fourier mathematical transformation to obtain a quantitative value corresponding to a detection item; and inputting the quantitative value into an evaluation model to obtain a final evaluation result.
Description
Technical Field
The invention relates to the technical field of quantum resonance, in particular to a human body data detection and analysis method based on quantum resonance.
Background
In recent 20 years, with the continuous development of society, the problems of the continuous change of disease spectrum, the continuous increase of drug-induced diseases and the like emerge endlessly. Health issues have attracted attention, and quantum resonance detection technology has entered the field of vision of people with its advantages of being simple, accurate, non-invasive, and wide in detection target. Therefore, the research of the quantum resonance technology for human health detection becomes urgent, and the quantum resonance technology has important research significance and wide application prospect.
Quantum medicine is formed by the combination and evolution of modern physics and modern life science, and provides a theoretical basis for developing quantum resonance detectors. In quantum physics, the basic units of a substance such as a neutron, a proton, or an electron are collectively called a basic particle or a quantum, and the motion of the basic particle forms a magnetic field (electromagnetic wave) carried by the substance. By using the resonance characteristics of the waves, whether the two waves are the same can be judged through the resonance phenomenon. The magnetic field waves of different tissues and organs are different, a quantum resonance detector is used for collecting a weak magnetic field in an organism and analyzing the weak magnetic field, then the weak magnetic field is subjected to resonance comparison with a corresponding standard magnetic field, a difference value is calculated, the health condition of the organism is judged, and then a medical expert is combined to analyze the result, so that disease diagnosis and treatment can be carried out. The method for performing biological measurement by analyzing weak magnetic field energy is called quantum analysis method, which is established on quantum science and life science, so that the method is called quantum medicine in medical development and application.
At present, the time for introducing the quantum resonance technology in China is too short, the technology is not mature, related research works are continuously carried out, but the popularization rate is low, one of main reasons is that body detection data is about life health and safety, doctors and patients pay more attention to the accuracy of the data, and both sides are difficult to accept serious consequences caused by detection errors, so a set of reliable human quantum resonance signal detection and analysis method is needed, the accuracy, stability and definition of the detection data are further improved, and a good and reliable detection result is provided for a detected person.
Disclosure of Invention
The invention can solve the defects of the prior art and provides a human body data detection and analysis method based on quantum resonance. The method comprises the following steps:
1) collecting electromagnetic waves of a detector and carrying out standardization processing on the electromagnetic waves;
2) performing wavelet transformation on the collected electromagnetic waves;
3) the magnetic field signal after wavelet transformation is transmitted into a giant magnetoresistance sensing circuit, and the magnetic field signal is converted into a voltage signal to be output;
4) the voltage signal output by the giant magnetic sensing circuit and the standard detection waveform code of the standard magnetic field wave corresponding to the detection item are subjected to resonance action, if the output accurate magnetic field signal and the stored standard detection waveform code are similar wave spectrums, a resonance signal is generated, and otherwise, a non-resonance signal is generated;
5) after the resonance signal is generated, analyzing and processing the resonance signal based on three vectors of an electric field, a magnetic field and a force field and Fourier mathematical transformation to obtain a quantitative value corresponding to a detection item;
6) and inputting the quantitative value into an evaluation model to obtain a final evaluation result.
Further, the wavelet transform is defined as:
wherein:
is a wavelet basis function; a is a scale factor; b is a translation factor, and x (t) is an acquired electromagnetic wave signal;
order:
a0≠1，b0> 0, j and n are integers, a is taken02, and b is used for t axis0Normalization:
then the discrete wavelet transform of x (t) is:
the calculation of discrete wavelet transform is usually performed by using Mallat algorithm, and its recurrence formula is as follows:
in the formula: dj，kAnd cj，kLow-frequency coefficients and high-frequency coefficients of the j-th layer decomposition are respectively;
and
low pass filter and high pass filter parameters for wavelet decomposition.
Further, the establishing process of the evaluation model comprises the following steps:
(1) establishing an evaluation object factor set U ═ U1,u2,...,un}；
(2) Establishing a quantization value set V ═ V1,v2,...,vn}；
(3) Establishing a fuzzy mapping U → F (V) from the factor set to the quantization value set:
deriving a fuzzy relation from the fuzzy mapping and obtaining a fuzzy matrix R:
the evaluation model is composed of U, V and R;
(4) and inputting U and V into a fuzzy matrix R for comprehensive evaluation.
Furthermore, the giant magnetic sensing circuit is a Wheatstone bridge formed by 4 giant magnetic resistors.
Drawings
FIG. 1 is a flow chart of the human body data detection and analysis method based on quantum resonance in the invention;
FIG. 2 is a flow chart of the human body data detection and analysis method based on quantum resonance in accordance with the present invention;
FIG. 3 is a flow chart of the human body data detection and analysis method based on quantum resonance in accordance with the present invention;
FIG. 4 is a flow chart of the human body data detection and analysis method based on quantum resonance in accordance with the present invention;
FIG. 5 is a schematic diagram of the internal structure of the giant magnetoresistance sensing circuit of the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Quantum medicine is a medical method established on the basis of quantum science, and an instrument for researching human body life activities by applying the quantum medical method is mainly a quantum resonance detector (QRS). QRS studies human life phenomena by capturing and analyzing electromagnetic waves emitted from human organs, can judge the state of human life activities, marks the electromagnetic waves of normal organs, pathogenic factors (bacteria, viruses, few sensitizing substances and the like) and various diseases of human bodies with codes respectively, and stores the electromagnetic waves in a computer. When a human body suffers from diseases, electronic motion of atoms in organs is abnormal, and further signal transmission of the atoms and cells is disordered, so that an abnormal physiological state is caused, and at the moment, a magnetic field in the human body is disordered. Through QRS, it can be detected whether the magnetic field in human body is disordered, and the signal is output in the form of sound.
A method for detecting and analyzing human body data based on quantum resonance is shown in figure 1, and comprises the following steps:
firstly, the electromagnetic wave of a detector is collected and standardized, the influence of the physical condition of the detector on the detected person is eliminated, and because the collected electromagnetic wave belongs to a weak magnetic field signal, the weak magnetic field signal needs to be subjected to wavelet transformation.
The wavelet transform has good time-frequency localization characteristics, and the signals are expanded according to different scales through wavelet multi-resolution analysis, so that the signals can be analyzed and processed under different resolutions. 3-layer wavelet decomposition is carried out on weak magnetic field signals x (t), and a schematic diagram is shown in figure 2
The continuous wavelet transform of signal x (t) is defined as:
wherein:
is a wavelet basis function; a is a scale factor; b is a translation factor.
In practical applications, it is usually necessary to calculate the discrete wavelet transform of a signal, i.e. let:
if a is taken02, and b is used for t axis0Normalization, there are:
the discrete wavelet transform of signal x (t) is:
the calculation of discrete wavelet transform is usually performed by using Mallat algorithm, and its recurrence formula is as follows:
in the formula: dj，kAnd cj，kLow-frequency coefficients and high-frequency coefficients of the j-th layer decomposition are respectively;
and
low pass filter and high pass filter parameters for wavelet decomposition.
As can be seen from the time-frequency characteristics of the wavelet transform, when the number of decomposition layers is sufficiently large, the wavelet transform has the property of a band-pass filter, and can be regarded as a narrow-band filtering system. The weak magnetic field signal belongs to an extremely low frequency signal, so the actual measured weak magnetic field signal is pre-filtered by adopting wavelet transformation: and performing J-layer wavelet decomposition on the weak magnetic field signal, and extracting the low-frequency component of the J-th layer. By selecting the appropriate number J of decomposition layers, the information of the target signal can be kept as much as possible while the high-frequency magnetic noise is filtered.
The magnetic field signal after wavelet transformation is transmitted into a giant magnetoresistance sensing circuit, the magnetic field signal of the circuit after giant magnetoresistance sensing can be accurately detected, the giant magnetoresistance sensing circuit is a circuit structure formed by using magnetic nano metal multilayer thin film materials with giant magnetoresistance effect and being compatible with an integrated circuit through a semiconductor integration process, and in the process of measuring a weak magnetic field, the output of the sensor can be changed due to the weak change of current on the giant magnetoresistance sensing circuit, so that when the weak magnetic field is accurately measured, the output characteristic of the sensor is stable due to the adoption of constant current power supply, the linear characteristic is obvious in the measuring range of the weak magnetic field, and the weak magnetic field signal can be conveniently detected.
The standard detection waveform code of the standard magnetic field wave corresponding to the detection item and the voltage signal output by the giant magnetic sensing circuit are subjected to resonance action, the standard detection waveform code of the standard magnetic field wave is information stored in a standard quantization magnetic field library, and the standard quantization magnetic field library converts a large number of standard biological magnetic field waves of each part of a human body into the standard detection waveform code for storage, namely a standard detection waveform code database of the standard magnetic field wave of the human body is formed; the signal output by the giant magnetic sensing circuit has resonance effect with the standard detection waveform code pre-stored in the singlechip processing module, if the output precise magnetic field signal and the stored standard detection waveform code have similar wave spectrum, a resonance signal is generated, otherwise a non-resonance signal is generated.
And when a resonance signal is generated, analyzing and processing the resonance signal, and performing Fourier mathematical transformation on the signal after the resonance action based on three vectors of an electric field, a magnetic field and a force field to obtain a quantitative value corresponding to a detection item.
Inputting the quantified values into an evaluation model to obtain a final evaluation result, wherein the establishment flow of the evaluation model is shown in fig. 3 and comprises the following steps:
(1) establishing an evaluation object factor set U ═ U1,u2,...,un}. The factors refer to various parameters related to the final evaluation result, such as quantum resonance detection parameters of the hair or blood of the tested person, vitamin content, physical examination historical results and other parameters related to the evaluation;
(2)establishing a quantization value set V ═ V1,v2,...,vn}. The quantization values are a set of final result levels;
(3) establishing a single attribute evaluation relationship, namely establishing a fuzzy mapping F from a factor set to a quantization value set, namely U → F (V):
deriving a fuzzy relation from the fuzzy mapping F, and obtaining a fuzzy matrix:
wherein R is a single attribute evaluation matrix, and the evaluation model is composed of U, V and R.
(4) And inputting U and V into a fuzzy matrix R for comprehensive evaluation. Apparently, the result of the object is limited by a plurality of parameters, but actually, each parameter has its own influence degree on the result, so the evaluation model obtains the membership weight of each parameter.
As shown in fig. 4, a system for implementing the detection analysis method of the present invention includes:
the quantum resonance electrode data acquisition module acquires a human body weak magnetic field signal by a contact method.
And the signal preprocessing module is used for performing wavelet transformation processing on the acquired weak magnetic field signals.
Giant magnetoresistance sense circuit: a Wheatstone bridge is formed by 4 giant magneto-resistors, and the internal structure is shown in FIG. 5:
wherein R2 and R3 are used as sensing resistors R1 and R4 are used as reference resistors. D1 denotes the length of the separation between the two magnetic field concentration zones D2 denotes the length of the magnetic field concentration zone. Two giant magnetic induction resistors R2, R3 are placed in the middle of the gap between the two magnetic field concentration regions, and reference resistors R1, R4 are sealed in the magnetic field concentration regions, so that the resistance of the reference resistors isolated from the external magnetic field does not change due to the change of the external magnetic field. Since the 4 giant magnetoresistance are made of the same material, the temperature drift is small because the characteristics such as temperature coefficient are the same. When an external magnetic field is applied, the resistance values of the two GMR sensing resistors R2 and R3 change along with the change of the external magnetic field, while the resistance values of the reference resistors R1 and R4 do not change, so that the bridge imbalance is caused to convert the magnetic field signal into a voltage signal for output.
And the single chip microcomputer processing module is used for comparing the signal output by the giant magnetic sensing circuit with the standard biological wave corresponding to the detection item, analyzing the resonance signal, and obtaining a quantitative value corresponding to the detection item and a quantitative value corresponding to the detection item based on the electric field, the magnetic field and the force field three-vector and Fourier mathematical transformation.
An evaluation model module: and the system is used for inputting the quantitative values into the evaluation model to obtain a final evaluation result.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (4)
1. A human body data detection and analysis method based on quantum resonance is characterized by comprising the following steps:
1) collecting electromagnetic waves of a detector and carrying out standardization processing on the electromagnetic waves;
2) performing wavelet transformation on the collected electromagnetic waves;
3) the magnetic field signal after wavelet transformation is transmitted into a giant magnetoresistance sensing circuit, and the magnetic field signal is converted into a voltage signal to be output;
4) the voltage signal output by the giant magnetic sensing circuit and the standard detection waveform code of the standard magnetic field wave corresponding to the detection item are subjected to resonance action, if the output accurate magnetic field signal and the stored standard detection waveform code are similar wave spectrums, a resonance signal is generated, and otherwise, a non-resonance signal is generated;
5) after the resonance signal is generated, analyzing and processing the resonance signal based on three vectors of an electric field, a magnetic field and a force field and Fourier mathematical transformation to obtain a quantitative value corresponding to a detection item;
6) and inputting the quantitative value into an evaluation model to obtain a final evaluation result.
2. The method for human body data detection and analysis based on quantum resonance as claimed in claim 1, wherein the wavelet transform is defined as:
wherein:
is a wavelet basis function; a is a scale factor; b is a translation factor, and x (t) is an acquired electromagnetic wave signal;
order:
a0≠1，b0> 1, j and n are integers, take a02, and b is used for t axis0Normalization:
then the discrete wavelet transform of x (t) is:
the calculation of discrete wavelet transform is usually performed by using Mallat algorithm, and its recurrence formula is as follows:
in the formula: dj，kAnd cj，kLow-frequency coefficients and high-frequency coefficients of the j-th layer decomposition are respectively;
and
low pass filter and high pass filter parameters for wavelet decomposition.
3. The method for detecting and analyzing human body data based on quantum resonance as claimed in claim 1, wherein the establishing process of the evaluation model comprises:
(1) establishing an evaluation object factor set U ═ U1,u2,...,un}；
(2) Establishing a quantization value set V ═ V1,v2,...,vn}；
(3) Establishing a fuzzy mapping U → F (V) from the factor set to the quantization value set:
deriving a fuzzy relation from the fuzzy mapping and obtaining a fuzzy matrix R:
the evaluation model is composed of U, V and R;
(4) and inputting U and V into a fuzzy matrix R for comprehensive evaluation.
4. The method as claimed in claim 1, wherein the giant magnetic sensing circuit is a wheatstone bridge composed of 4 giant magnetic resistors.
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