A handheld electrocardiogram and electroencephalogram (EEG) testing instrument

Abstract

The invention relates to a handheld electrocardioencephalogram (ECG) calibrator. According to calibration requirements, multiple waveform types are selected, a mathematical function model is established for each waveform, and a relationship between amplitude and time is defined; a clock signal is substituted into the relationship between amplitude and time to obtain an expression of real-time amplitude change; the expression of real-time amplitude change is converted into binary code and an analog signal is output through a DAC; the analog signal is attenuated through a Π-type symmetrical resistance attenuation network to obtain an output signal; a superposition circuit or an output circuit is selected by an analog switch; the analog signal of the selected path is output to the signal output circuit of the calibrator through an output interface to realize real-time output and superposition of the signal; the invention effectively simulates the complex dynamic changes of real physiological signals by selecting multiple waveform types and establishing accurate mathematical function models for them, and adopts a Π-type symmetrical resistance attenuation network to realize high-precision signal attenuation, thereby significantly reducing signal distortion and noise interference.

Description

Technical Field

[0001] The invention belongs to the technical field of calibrators, in particular to a handheld electrocardioencephalogram (ECG) calibrator. Background Art

[0002] With the rapid development of modern medical technology, electroencephalogram (EEG), as an important neuroelectrophysiological detection method, plays an indispensable role in clinical diagnosis and research. The calibration accuracy of the electroencephalogram is directly related to the reliability of the test results and the accuracy of clinical diagnosis. In recent years, with the continuous advancement of electronic technology and signal processing technology, the performance of the electroencephalogram has been significantly improved. However, the existing technology still has many deficiencies in signal generation, conversion, attenuation and output, which limits the further improvement of the calibration accuracy. For example, traditional signal generation methods often rely on fixed waveforms, lack the ability to adapt to a variety of complex waveforms, and it is difficult to fully simulate the dynamic changes of real physiological signals. In addition, the existing signal attenuation network design is highly complex, and it is difficult to achieve high-precision and low-distortion signal attenuation, resulting in large errors and noise interference when outputting microvolt or millivolt signals. These problems are particularly prominent in the process of multi-signal superposition output and real-time signal processing, which seriously affects the overall calibration performance and measurement accuracy of the electroencephalogram.

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention proposes an innovative calibration method for improving the calibration accuracy of an electrocardioencephalogram machine. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the following technical problems in the prior art: the existing signal attenuation network has high design complexity and is difficult to achieve high-precision and low-distortion signal attenuation, resulting in large errors and noise interference in microvolt or millivolt signal output.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a handheld electrocardioencephalogram (ECG) calibrator, comprising the following steps to achieve calibration:

[0007] S1. According to the test requirements, select multiple waveform types, establish a mathematical function model for each waveform, and define the relationship between amplitude and time;

[0008] S2. Substituting the clock signal into the relationship between amplitude change and time, to obtain an expression for real-time amplitude change;

[0009] S3, converting the expression of the real-time amplitude change into binary code and outputting an analog signal through a DAC;

[0010] S4, performing signal attenuation on the analog signal through a Π-type symmetrical resistance attenuation network to obtain an output signal;

[0011] S5. Use the analog switch to select the superposition circuit or the output circuit, where:

[0012] If multiple signals need to be superimposed and output, the analog switch connects the attenuated analog signal to the superposition circuit, and the multiple signals are superimposed using an operational amplifier or a mixer;

[0013] If only a single signal output is required, the analog switch will directly connect the attenuated analog signal to the output interface;

[0014] S6. The analog signal of the selected path is output to the signal output circuit of the calibrator through the output interface to realize the real-time output and superposition of the signal.

[0015] As a preferred technical solution for a handheld electrocardioencephalogram (ECG) calibrator,

[0016] The electrocardiograph calibration requirements include linear response calibration, frequency response calibration, transient response calibration, signal-to-noise ratio calibration and multi-signal superposition calibration.

[0017] As a preferred technical solution for a handheld electrocardioencephalogram (ECG) calibrator,

[0018] According to the test requirements, select the waveform type that can effectively simulate the characteristics of real physiological signals, including:

[0019] Sine wave: used for linear response and frequency response verification;

[0020] Square wave: used for frequency response and transient response verification;

[0021] Heart rate signal: used for signal-to-noise ratio and transient response verification, simulating the pulse characteristics of real ECG signals; Differential signal: used for transient response and frequency response verification, simulating the rate of change of signals;

[0022] ECG simulation signal: used for multi-signal superposition and signal-to-noise ratio verification, simulating the complex waveforms of P wave, QRS complex wave and T wave in the real electrocardiogram.

[0023] As a preferred technical solution for a handheld electrocardioencephalogram (ECG) calibrator,

[0024] The clock signal T(t) is represented as a square wave, and its mathematical expression is:

[0025] T(t)=sign(sin(2πF T t))

[0026] Where T(t) is the clock signal value at time t, which can be +1 or -1; F T The frequency of the clock signal, measured in Hertz (Hz), determines the period of the clock signal t is the time variable, in seconds (s);

[0027] sign(·) is the sign function, defined as:

[0028]

[0029] This function converts the output of the sine function into the high and low levels of a standard square wave.

[0030] As a preferred technical solution for a handheld electrocardioencephalogram (ECG) calibrator,

[0031] Step S3 includes:

[0032] The expression A(t) of real-time amplitude change is converted into binary code B[n] through sampling, quantization and encoding;

[0033] Transmit the binary code B[n] to the DAC module through the digital interface;

[0034] The DAC generates the corresponding analog voltage V according to the received binary code B[n]. out (n);

[0035] V out (n) Output through the analog output port of the DAC for subsequent signal attenuation and processing.

[0036] 6. The handheld electrocardioencephalogram tester according to claim 5, characterized in that:

[0037] The π-type symmetrical resistor attenuation network includes three resistors R1, R2, and R3;

[0038] The attenuation ratio calculation formula is:

[0039]

[0040] Among them, α is the attenuation ratio.

[0041] As a preferred technical solution for a handheld electrocardioencephalogram (ECG) calibrator,

[0042] Determine whether multiple signal superposition outputs are required according to the verification requirements and set the value of the control signal C;

[0043] Superposition output: If superposition output is required, set C = 1, connect the analog switch to the superposition circuit, and generate the superposition signal V through the operational amplifier. sum ;

[0044] Single output: If only a single signal output is required, set C = 0, the analog switch is directly connected to the output interface, and the output signal V is output through the buffer operational amplifier buffered ;

[0045] The final output signal V final =V sum or V final =V buffered The signal is transmitted to the signal input circuit of the calibrator to achieve real-time output or superimposed output.

[0046] As a preferred technical solution for a handheld electrocardioencephalogram (ECG) calibrator,

[0047] The selected signal is input to the buffer operational amplifier; after buffering, the signal is electrically isolated through an optical isolator, and is output to the detector after synchronization to obtain an output signal.

[0048] As a preferred technical solution for a handheld electrocardioencephalogram (ECG) calibrator,

[0049] Specifically, the selected signal path output signal V final (t), the signal after buffering and isolation is V buffered (t), the synchronized signal is V synced (t), the final output signal to the calibration instrument is V output (t);

[0050] V output (t) = V synced (t) = V buffered (t)·Sync(f sync , t)

[0051] Among them, V output (t): The final signal output to the tester, in volts (V); V synced (t): synchronized signal, in volts (V); V buffered (t): buffered signal, in volts (V); Sync (f sync , t): synchronization function, according to the synchronization frequency f sync Adjust the phase and timing of the signal.

[0052] Beneficial effects of the present invention: By selecting a variety of waveform types and establishing accurate mathematical function models for them, the present invention can comprehensively cover the signal characteristics under different testing requirements and effectively simulate the complex dynamic changes of real physiological signals. At the same time, a Π-type symmetrical resistance attenuation network is used to achieve high-precision signal attenuation, ensuring high-precision transmission of amplitude information during digital-to-analog conversion, and significantly reducing signal distortion and noise interference. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0054] Figure 1 It is a schematic diagram of the structure of the method flow of the present invention;

[0055] Figure 2 It is a schematic diagram of experimental comparison of the present invention. DETAILED DESCRIPTION

[0056] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0057] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0058] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0059] Secondly, the present invention is described in detail with reference to the schematic diagram. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0060] Reference Figure 1-2This embodiment provides a handheld electrocardiograph (ECG) tester, which implements the test through the following steps, and can test the ECG by effectively simulating the characteristics of real physiological signals through the generated waveform types. Specifically:

[0061] S1. According to the requirements of electrocardioencephalogram (ECG) machine calibration, select multiple waveform types, establish a mathematical function model for each waveform, and define the relationship between amplitude and time. Among them, the following should be explained in this step:

[0062] The electrocardioencephalogram (ECG) machine calibration requirements include at least linear response calibration, frequency response calibration, transient response calibration, signal-to-noise ratio calibration, and multi-signal superposition calibration;

[0063] Specifically, according to the test requirements, select the waveform type that can effectively simulate the characteristics of real physiological signals, including:

[0064] Sine wave: used for linear response and frequency response verification;

[0065] Square wave: used for frequency response and transient response verification;

[0066] Heart rate signal: used for signal-to-noise ratio and transient response verification, simulating the pulse characteristics of real ECG signals; Differential signal: used for transient response and frequency response verification, simulating the rate of change of signals;

[0067] ECG simulation signal: used for multi-signal superposition and signal-to-noise ratio verification, simulating the complex waveforms of P wave, QRS complex wave and T wave in the real electrocardiogram;

[0068] Exemplarily, waveform selection at least includes demand classification and waveform matching, waveform characteristic analysis, parameter optimization and adjustment, and waveform characteristic analysis, wherein parameter optimization and adjustment include: optimizing the parameters (such as frequency, amplitude, and phase) of each waveform according to the verification requirements to ensure that the waveform can give full play to its testing capabilities during the verification process;

[0069] For example, in frequency response testing, the frequency of the sine wave covers the entire operating frequency range to fully evaluate the performance of the device; in signal-to-noise ratio testing, the amplitude of the heart rate signal and ECG simulation signal is set at the microvolt level to test the performance of the device under low signal-to-noise ratio conditions;

[0070] In an optional implementation, multiple waveform types (such as sine wave, square wave, heart rate signal, differential signal and ECG simulation signal) are selected to ensure that the calibration instrument can maintain high-precision measurement in various complex signal environments. Through diversified waveform selection, a variety of calibration scenarios from simple to complex, multi-band and transient signals are covered, thereby improving the application scope and flexibility of the calibration instrument.

[0071] As an example, a corresponding mathematical function model is established for each waveform, and the relationship between its amplitude and time is defined, for example:

[0072] Square wave:

[0073] A 方波 (t) = M sign (sin (2πFt))

[0074] Among them, A 方波 (t) is the square wave amplitude at time t, M is the peak amplitude of the square wave, which determines the high and low level amplitudes of the square wave; F is the frequency of the square wave, which determines the period and rate of change of the square wave; t is the time variable, sign(·) is the sign function, defined as

[0075]

[0076] This function is used to convert the output of the sine function into the high and low levels of a square wave;

[0077] Sine wave:

[0078] A 正弦波 (t) = M sin(2πFt+φ)

[0079] Among them, A 正弦波 (t) is the amplitude of the sine wave at time t, M is the peak amplitude of the sine wave, which determines the maximum amplitude of the waveform, F is the frequency of the sine wave, which determines the period and rate of change of the waveform; t is the time variable, φ is the phase angle, which determines the starting position of the sine wave on the time axis.

[0080] Heart rate signal:

[0081] A 心率 (t) = M·(1-+sin(2πFt))·e -λt ·pulse(t)

[0082] Among them, A 心率 (t) is the amplitude of the heart rate signal at time t, M is the peak amplitude of the heart rate signal, which determines the maximum amplitude of the signal; F is the fundamental frequency of the heart rate signal, which is usually related to the heart rate frequency; t is the time variable, and λ is the attenuation coefficient, which is used to simulate the gradual attenuation of the heart rate signal;

[0083] pulse(t) is a pulse function used to simulate the pulse characteristics of a heartbeat signal and is defined as:

[0084]

[0085] in, is the heartbeat cycle, Represents the set of natural numbers.

[0086] Differential signal:

[0087]

[0088] Among them, A 微分 (t) is the differential signal amplitude at time t, M is the amplitude coefficient of the differential signal, which determines the amplification factor of the signal; F is the fundamental frequency corresponding to the differential signal, and t is the time variable.

[0089] ECG simulation signal:

[0090]

[0091] Among them, A ECG (t) is the amplitude of the ECG simulation signal at time t, M is the peak amplitude of the ECG signal, which determines the overall amplitude of the signal; t p , t q , t r is the time position of the P wave, QRS complex wave and T wave in the ECG signal, indicating the center time of each band respectively; σ p , σ q , σ r is the standard deviation of each band, which determines the width and shape of the waveform; exp(·) is an exponential function used to simulate the Gaussian shape of each band in the ECG signal.

[0092] Based on the above mathematical model, an accurate function model is established for each waveform type, and the parameter settings are optimized according to the specific verification requirements. For example, in the frequency response verification, the frequency of the sine wave covers the entire operating frequency range to comprehensively evaluate the device performance; in the signal-to-noise ratio verification, the amplitude of the heart rate signal and the ECG simulation signal is set at the microvolt level to test the performance of the device under low signal-to-noise ratio conditions.

[0093] As an example, the sine wave parameters are set to an amplitude of 2V and a frequency of 50Hz; the square wave parameters are set to an amplitude of 5V and a frequency of 1000Hz; the heart rate signal parameters are set to an amplitude of 1V and a base frequency of 1Hz, corresponding to a heart rate of 60 beats / minute, and an attenuation coefficient of 0.1s. -1 ; The differential signal parameters are set to amplitude 1V·s, base frequency 100Hz; the ECG simulation signal parameters are set to amplitude M=1V, P wave time position t p =0.2s, standard deviation σ p =0.05s; QRS complex wave time position t q =0.4s, standard deviation σ q =0.02s; T wave time position t r =0.6s, standard deviation σ r =0.05s.

[0094] Preferably, by implementing the above-mentioned step S1, the present invention can accurately generate various types of test signals to meet the high-precision measurement requirements of the calibration instrument in different application scenarios. The precise relationship between amplitude and time ensures the high fidelity and stability of signal generation, and provides a solid foundation for subsequent signal conversion, attenuation and output, thereby significantly improving the accuracy and reliability of the entire calibration method.

[0095] Step S2: Substitute the clock signal into the relationship between amplitude and time to obtain an expression for real-time amplitude change. What needs to be explained in this step is:

[0096] The clock signal T(t) is represented as a square wave, and its mathematical expression is:

[0097] T(t)=sign(sin(2πF T t))

[0098] Where T(t) is the clock signal value at time t, which can be +1 or -1; F T The frequency of the clock signal, measured in Hertz (Hz), determines the period of the clock signal t is the time variable, in seconds (s);

[0099] sign(·) is the sign function, defined as:

[0100]

[0101] This function converts the output of the sine function into the high and low levels of a standard square wave;

[0102] The standard square wave is used as the mathematical model of the clock signal T(t), and the frequency of the clock signal F T It can be adjusted according to actual verification requirements to ensure the real-time and accuracy of signal sampling, and is not a sole limiting requirement in this embodiment.

[0103] According to the five waveform types (square wave, sine wave, heart rate signal, differential signal, ECG simulation signal) established in step S1, the clock signal T(t) is substituted into the relationship between the amplitude and time, and the corresponding real-time amplitude change expression A(T) is obtained, where:

[0104] Substituting the clock signal T(t) into the square wave amplitude versus time relationship, we get:

[0105] A 方波 (T)=M·T(t)=M·sign(sin(2πFt))

[0106] Among them, A 方波(T) is the square wave amplitude at time T(t); M is the peak amplitude of the square wave, which determines the high and low level amplitudes of the square wave; F is the frequency of the square wave, which determines the period and rate of change of the square wave;

[0107] By directly substituting the clock signal into the square wave function model, real-time signal switching can be achieved, which is suitable for verification scenarios that require clear timing control, such as digital signal conversion and timing response testing;

[0108] Substituting the clock signal T(t) into the relationship between the amplitude of the sine wave and time, we get:

[0109]

[0110] Among them, A 正弦波 (T) is the amplitude of the sine wave at time T(t), M is the peak amplitude of the sine wave, which determines the maximum amplitude of the waveform; F is the frequency of the sine wave, which determines the period and rate of change of the waveform; φ is the phase angle, which determines the starting position of the sine wave on the time axis;

[0111] By substituting the clock signal into the sine wave model, clock-based sine wave sampling can be achieved, which is suitable for verification scenarios that require continuous waveform and frequency response testing, such as AC signal analysis and filter performance evaluation;

[0112] Substituting the clock signal T(t) into the relationship between the amplitude of the heart rate signal and time, we get:

[0113]

[0114] Among them, A 心率 (T) is the amplitude of the heart rate signal at time T(t), M is the peak amplitude of the heart rate signal, which determines the maximum amplitude of the signal; F is the fundamental frequency of the heart rate signal, which is usually related to the heart rate frequency; λ is the attenuation coefficient, which is used to simulate the gradual attenuation of the heart rate signal; T(t) is the time variable of the clock signal;

[0115] is a pulse function used to simulate the pulse characteristics of a heartbeat signal and is defined as:

[0116]

[0117] in, is the heartbeat cycle;

[0118] The heart rate signal simulates the pulse changes of biological bodies and is suitable for the application scenarios of the calibration instrument in medical equipment. By substituting the clock signal into the heart rate signal model, a heart rate signal with pulse and attenuation characteristics can be generated in real time to test the response ability of the calibration instrument when processing transient signals and gradual signals.

[0119] Substituting the clock signal T(t) into the relationship between the amplitude of the differential signal and time, we get:

[0120]

[0121] Among them, A 微分 (T) is the differential signal amplitude at time T(t), M is the amplitude coefficient of the differential signal, which determines the amplification factor of the signal; F is the fundamental frequency corresponding to the differential signal, which determines the rate of change of the signal; T(t) is the time variable of the clock signal;

[0122] Differential signals are used for edge detection and rate of change measurement in analog signal processing. By substituting the clock signal into the differential signal model, a signal with obvious rate of change and high-frequency components can be generated in real time. This is suitable for testing the accuracy and response speed of the calibration instrument when processing fast-changing signals.

[0123] Substituting the clock signal T(t) into the relationship between the amplitude and time of the ECG simulation signal, we get:

[0124]

[0125] Among them, A ECG (T) is the amplitude of the ECG simulation signal at time T(t); M is the peak amplitude of the ECG signal, which determines the overall amplitude of the signal; t p , t q , t r is the time position of the P wave, QRS complex wave and T wave in the ECG signal, indicating the center time of each band respectively; σ p , σ g , σ r is the standard deviation of each band, which determines the width and shape of the waveform; T(t) is the time variable of the clock signal, F T is the frequency of the clock signal, which determines the time resolution of the clock signal;

[0126] ECG simulation signal is used to simulate the complex waveform structure in the electrocardiogram, which is suitable for the application of the tester in medical equipment. By substituting the clock signal into the ECG signal model, a multi-peak complex signal including P wave, QRS complex wave and T wave can be generated in real time, which is used to test the resolution and accuracy of the tester when processing multi-peak complex signals;

[0127] By substituting the clock signal into a variety of waveform function models, the real-time amplitude change expression provided by the present invention can accurately reflect the dynamic characteristics of various test signals, ensuring the high fidelity and stability of signal generation. Combined with high-frequency clock signals and precise mathematical models, the calibration instrument can achieve high-precision signal sampling and real-time output, significantly improving the measurement accuracy and reliability of the entire calibration method. In addition, the diversified signal generation capability expands the application scope of the calibration instrument, meets a variety of complex signal processing and measurement requirements, and enhances its market competitiveness and technological advancement.

[0128] Step S3: Convert the expression of real-time amplitude change into binary code and output analog signal through DAC. Among them, what needs to be explained in this step is:

[0129] Transmit the binary code B[n] to the DAC module through a digital interface (such as SPI or I2C);

[0130] The DAC generates the corresponding analog voltage V according to the received binary code B[n]. out (n);

[0131] V out (n) Output through the analog output port of the DAC for subsequent signal attenuation and processing;

[0132] In an optional implementation, in step S2, the expression A(t) of the real-time amplitude change has been generated according to the clock signal. In order to convert this continuous-time analog signal into a digital signal, three steps of sampling, quantization and encoding are required, specifically including:

[0133] Sampling is the process of converting a continuous-time signal A(t) into a discrete-time signal A[n]. According to the Nyquist sampling theorem, in order to avoid aliasing, the sampling frequency f s Should be at least twice the highest frequency component in the signal;

[0134] Sampling formula:

[0135] A[n]=A(nT s )in

[0136] Where A[n] is the amplitude of the nth sampling point, in volts (V); T s is the sampling period, in seconds (s); f s is the sampling frequency in Hertz (Hz); n is the sampling point number, n∈N, and N is a natural number.

[0137] Quantization is the process of mapping a continuous amplitude A[n] to a finite number of discrete amplitude levels. The quantization accuracy is determined by the resolution of the DAC, usually expressed in the number of bits N. The quantization error Δ is the amplitude interval of each quantization level.

[0138] Quantization level formula: L = 2 N

[0139] Quantization step size formula:

[0140]

[0141] Quantization formula:

[0142]

[0143] Where Q[n] is the amplitude after the nth quantization, in volts (V); V max is the maximum value of the signal amplitude, in volts (V); V min is the minimum value of the signal amplitude, in volts (V); Is the rounding function.

[0144] Coding is the process of converting the quantized amplitude Q[n] into binary code. Each quantization level corresponds to a unique binary number with a length of N bits.

[0145] Coding formula: B[n] = Bin(Q[n])

[0146] Wherein, B[n] is the binary code of the nth sample, with a length of N bits; Bin(·) is a function for converting a decimal number into a binary number.

[0147] Specifically, after being encoded, the digital signal B[n] is input into the DAC for digital-to-analog conversion to generate the corresponding analog signal V out (n);

[0148] DAC output formula: V out (n) = Q[n]

[0149] Among them, V out (n) : The analog signal amplitude of the nth output, in volts (V).

[0150] Q[n]: The nth quantized amplitude, in volts (V).

[0151] For example, in order to ensure high accuracy and low error in the digital conversion process, it is necessary to accurately calculate the various parameters in the sampling, quantization and encoding processes. According to the Nyquist sampling theorem, in order to accurately restore the continuous time signal, the sampling frequency f s Must meet:

[0152] f s ≥2f max

[0153] Among them, f max is the highest frequency component in the signal. For EEG signals, usually f max The sampling frequency is about 100Hz, so the sampling frequency should be at least 200Hz. However, for higher accuracy and better signal restoration, the actual sampling frequency is usually set to 10kHz or higher;

[0154] Quantization error e q It refers to the difference between the quantized amplitude Q[n] and the original amplitude A[n], and its maximum value is

[0155]

[0156] The noise power P introduced by the quantization error q for:

[0157] The relationship between signal-to-noise ratio (SNR) and quantization error is: SNR≈6.02N+1.76dB

[0158] Where N is the resolution (number of bits) of the DAC;

[0159] During the encoding process, the use of CRC check or other error detection mechanisms can further improve the reliability of data transmission;

[0160] Preferably, the digital conversion process in step S3 of the present invention adopts a high-resolution 16-bit DAC (AD5724), which significantly improves the quantization accuracy and dynamic range of the signal, and minimizes quantization error and noise interference through precise sampling frequency setting and high-precision quantization step design.

[0161] As an example, the following is an example of selecting specific parameters in step S3 of the present invention:

[0162]

[0163] Assume that there is a real-time amplitude change expression A(t) = 5sin(2π×50t), at t = 0.01 seconds:

[0164] Sampling: A[1] = A(0.01) = 5sin(2π×50×0.01) = 5sin(π) = 0V

[0165] Quantization: Q[1] = 0V (because A[1] = 0V corresponds to quantization level 32768)

[0166] Encoding: B[1] = Bin(32768) = 1000000000000000

[0167] DAC output: V out (1) = Q[1] = 0 V

[0168] The present invention significantly improves the accuracy and stability of electrocardioencephalogram signal conversion in step S3 through high-resolution DAC and accurate sampling, quantization and encoding processes. Compared with the prior art, the traditional method usually adopts a lower resolution DAC (such as 12 bits), resulting in a large quantization error and a low signal-to-noise ratio, which affects the fidelity and verification accuracy of the signal. The present invention reduces the quantization error and improves the signal-to-noise ratio by using a 16-bit DAC and an optimized digital conversion process, ensuring the high fidelity and accuracy of the electrocardioencephalogram signal. In addition, the use of an efficient coding protocol (such as SPI) and an error detection mechanism further improves the reliability and real-time performance of data transmission, ensuring the stability and accuracy of the verification process.

[0169] To sum up, step S3 significantly improves the signal conversion accuracy and stability of the EEG calibration method through precise digital conversion and the application of high-resolution DAC, lays a solid foundation for subsequent signal attenuation and processing, and reflects the innovation and technical advantages of the present invention in improving the calibration accuracy of the EEG machine.

[0170] Step S4: attenuate the analog signal through a π-type symmetrical resistance attenuation network to obtain an output signal. The following should be noted about this step:

[0171] During the calibration of the EEG machine, the amplitude of the analog signal needs to be accurately attenuated to the microvolt or millivolt level to meet the requirements of high-precision measurement. Assuming that the analog signal amplitude of the DAC output is V DAC , the target output signal amplitude is V out , the attenuation ratio α is defined as:

[0172]

[0173] The π-type symmetrical resistor attenuation network consists of three resistors R1, R2, and R3.

[0174] Among them, R1=R3 to ensure the symmetry of the network, simplify the calculation and improve the stability.

[0175] Attenuation ratio calculation formula:

[0176]

[0177] Through the above formula, the appropriate resistance value can be selected according to the required attenuation ratio α.

[0178] As an example, assuming the target attenuation ratio α = 0.001, and selecting the standard resistance value R1 = R3 = 100 kΩ, then:

[0179]

[0180] Solve the equation to find R2:

[0181] 0.001×(200kΩ+R2)=R2

[0182] 200kΩ×0.001+0.001R2=R2

[0183] 200V=R2(1-0.001)

[0184]

[0185] Since the standard resistance value is 200Ω, select R2=200Ω.

[0186] According to the calculation results, a π-type symmetrical resistance attenuation network is constructed, and the specific connections are as follows:

[0187] R1=R3=100kΩ;R2=200Ω

[0188] Through the above resistor configuration, verify whether the attenuation ratio meets the design requirements.

[0189]

[0190] Verify the output signal amplitude: V out =α×VDAC=0.001×10V=10mV

[0191] Measure V with a high-precision voltmeter out , make sure it is close to 10mV. If there is any deviation, adjust the resistance value or check the circuit connection.

[0192] To ensure accuracy and linearity in the signal attenuation process, high-precision resistors (1% tolerance) and high-precision operational amplifiers are selected.

[0193] Signal buffer formula: V buffered =V out =α×V DAC

[0194] Exemplary, specific parameter selection:

[0195]

[0196]

[0197] Through the above design and optimization, the Π-type symmetrical resistance attenuation network in step S4 can effectively achieve high-precision signal attenuation, ensure the signal accuracy and stability during the electrocardioencephalogram calibration process, significantly improve the calibration accuracy and reliability, and reflect the innovation and technical advantages of the present invention in the electrocardioencephalogram calibration method.

[0198] Step S5: Use the analog switch to select the superposition circuit or the output circuit. The following should be noted in this step:

[0199] Determine whether multiple signal superposition outputs are required based on the verification requirements;

[0200] Superposition output: If superposition output is required, set C = 1, connect the analog switch to the superposition circuit, and generate the superposition signal V through the operational amplifier. sum ;

[0201] Single output: If only a single signal output is required, set C = 0, the analog switch is directly connected to the output interface, and the output signal V is output through the buffer operational amplifier buffered ;

[0202] The final output signal V final Transmitted to the signal input circuit of the calibrator to achieve real-time output or superimposed output;

[0203] Assume that the control signal C has a binary state:

[0204]

[0205] The output signal formula is:

[0206]

[0207] As an example, for a superposition circuit, there are N signals V1, V2, ..., V N , linear superposition is achieved through operational amplifiers,

[0208]

[0209] Where: V sum : The amplitude of the signal after superposition, in volts (V); R f : Feedback resistance, in ohms (Ω); R i : the i-th input resistance, in ohms (Ω); V i : The i-th input signal, in volts (V).

[0210] As an example, the buffer op amp is configured as a unity gain buffer (VoltageFollower), whose output signal V buffered With input signal V attenuated The relationship is: Vbuffered =V attenuated

[0211] Among them, V buffered : Buffered output signal in volts (V); V attenuated : The analog signal after passing through the attenuation network, in volts (V);

[0212] The present invention uses high-performance analog switches to achieve fast and accurate switching of signal paths, supports signal superposition and single output, and greatly improves the flexibility and adaptability of the verification method. Compared with the design of fixed signal paths in traditional methods, the method of the present invention can dynamically adjust the signal processing path according to actual verification requirements to meet diverse measurement requirements.

[0213] Step S6: Output the analog signal of the selected path to the signal output circuit of the calibration instrument through the output interface to achieve real-time output and superposition of the signal. Among them, what needs to be explained in this step is:

[0214] According to the signal path selection in step S5, the signal V selected by the analog switch final is connected to the output interface;

[0215] According to the control signal C in step S5, the output path is determined to be a single signal output V buffered Or superimposed signal output V sum ;

[0216] The selected signal V final Input to a buffer operational amplifier (such as OPA277), which provides high input impedance and low output impedance to ensure that the signal is not loaded or distorted during transmission;

[0217] After buffering, the signal is electrically isolated through an optical isolator to prevent ground loops and electrical noise interference;

[0218] Isolation formula: V isolated =V buffered

[0219] Among them, V isolated : Isolated signal, V buffered : Buffered signal.

[0220] As an example, assume that the signal path selected in step S5 outputs the signal V final (t), the signal after buffering and isolation is V buffered (t), the synchronized signal is V synced (t), the final output signal to the calibration instrument is V output (t);

[0221] V output(t) = V synced (t) = V buffered (t)·Sync(f sync , t)

[0222] Among them, V output (t): The final signal output to the tester, in volts (V); V synced (t): synchronized signal, in volts (V); V buffered (t): buffered signal, in volts (V); Sync (f sync , t): synchronization function, according to the synchronization frequency f sync Adjust the phase and timing of the signal;

[0223] To ensure that the signal output is synchronized with the clock of the calibrator, a phase-locked loop (PLL) or other clock synchronization technology is used to adjust the phase and frequency of the output signal to the internal clock f of the calibrator. sync Stay consistent;

[0224]

[0225] Among them, V synced (t): synchronized signal, in volts (V); V isolated (t): isolated signal, in volts (V); f sync : The internal synchronous clock frequency of the tester, in Hertz (Hz); φ sync : Synchronization phase offset, in radians (rad).

[0226] The signal-to-noise ratio (SNR) is defined as the signal power P signal and the noise power P noise The ratio is expressed in decibels (dB).

[0227]

[0228] Among them, SNR: signal-to-noise ratio, in decibels (dB); P signal : signal power, in watts (W); P noise : Noise power, in watts (W).

[0229] Through the feedback loop, the signal-to-noise ratio (SNR) is monitored in real time. measured Adjust the output signal amplitude and path selection to maintain the preset signal-to-noise ratio standard SNR target .

[0230] ΔV=K p (SNR target -SNR measured )

[0231] Where, ΔV: adjustment value, in volts (V); K p : Proportional gain constant, used to control the adjustment amplitude; SNR target : preset target signal-to-noise ratio, in decibels (dB); SNR measured : Real-time measured signal-to-noise ratio, in decibels (dB).

[0232] For example, assume that the signal input circuit of the detector requires a signal amplitude V input is 10mV, and the signal-to-noise ratio SNR is required to be ≥ 70dB. In step S5, a superposition circuit is selected to generate a superposition signal V sum =6.5V, after attenuation network α=0.001, we get V out =6.5mV. Then, through buffering and synchronization, the output signal V output It was adjusted to 10mV, and the signal quality monitoring module confirmed that SNR = 75dB, meeting the verification requirements.

[0233] V final =V sum =6.5V

[0234] V out =α×V sum =0.001×6.5V=6.5mV

[0235] V output =V synced =10mV, SNR=75dB

[0236] By selecting a variety of waveform types and establishing accurate mathematical function models for them, this method can comprehensively cover the signal characteristics under different calibration requirements and effectively simulate the complex dynamic changes of real physiological signals. At the same time, a Π-type symmetrical resistance attenuation network is used to achieve high-precision signal attenuation, ensuring high-precision transmission of amplitude information in the digital-to-analog conversion process, significantly reducing signal distortion and noise interference. In addition, high-performance analog switches are used to achieve flexible selection of signal paths, supporting multi-signal superposition output and single signal output, greatly improving the adaptability and functional diversity of the calibration method. Through this method, not only the accuracy and stability of the electrocardioencephalogram machine in the signal generation and processing process are improved, but also the shortcomings of the existing technology in multi-signal superposition and real-time signal output are effectively solved, and the overall performance and measurement reliability of the calibration instrument are significantly improved.

[0237] The existing electrocardioencephalogram (ECG) calibration technology mainly faces the problems of incomplete signal generation, inaccurate signal attenuation, and limited multi-signal processing capabilities. The present invention systematically solves these key technical problems by introducing a multi-waveform mathematical model, an accurate π-type symmetrical resistance attenuation network, and a high-performance analog switch. Specifically, the present invention not only realizes the high-precision generation and real-time processing of a variety of complex waveforms, but also ensures the high fidelity and stability of signal output by optimizing signal attenuation and path selection. These innovative technical improvements effectively improve the calibration accuracy and reliability of the electrocardioencephalogram (ECG) machine, meeting and exceeding the strict requirements of the national calibration regulations for the output signal amplitude and accuracy.

[0238] In order to verify the beneficial effects and superiority of the built-in algorithm module of the calibration instrument of the present invention, a series of comparative experiments were designed. The experiment aims to prove that the accuracy and stability of the method of the present invention in the process of signal generation, conversion, attenuation and output are significantly better than the prior art through actual data comparison. The experiment was carried out in a standard electronic laboratory environment, and the experimental equipment included a high-precision digital-to-analog converter (DAC, model AD5724), a clock signal source with a frequency of 1MHz, a Π-type symmetrical resistance attenuation network (composed of accurately calculated 100kΩ and 200Ω resistors), a single-pole double-throw (SPDT) analog switch (model ADG884), a high-precision operational amplifier (model OPA277), a multiplexer, and a high-resolution oscilloscope and spectrum analyzer. The selected waveform types include sine waves, square waves, heart rate signals, differential signals, and ECG simulation signals to fully cover different calibration requirements.

[0239] The experimental steps are as follows:

[0240] Waveform generation and conversion: According to step S1, a corresponding mathematical function model is selected and established for each waveform type to ensure that multiple requirements such as linear response, frequency response, transient response, signal-to-noise ratio and multi-signal superposition are covered.

[0241] The clock signal is substituted into each waveform model through a high-precision clock signal source (step S2) to obtain an expression for real-time amplitude change.

[0242] These expressions are converted into binary codes using a 16-bit DAC (step S3), and a V-level analog signal (eg, 10V) is output.

[0243] Signal attenuation: A π-type symmetrical resistor attenuation network was designed and constructed (step S4), where R1=R3=100kΩ, R2=200Ω, achieving an attenuation ratio of α=0.001, attenuating a 10V signal to 10mV.

[0244] The high-precision operational amplifier OPA277 is used to buffer the attenuated signal to ensure signal stability and linearity.

[0245] Signal selection and superposition: Use the ADG884 analog switch to select the signal path according to the control signal (step S5). When multiple signals need to be superimposed, the analog switch connects the attenuated signal to the superposition circuit and realizes signal superposition through OPA277; when only a single signal output is required, the analog switch directly connects the signal to the output interface (step S6).

[0246] The output signal is monitored and recorded in real time by a high-resolution oscilloscope and spectrum analyzer to ensure the accuracy and stability of the signal.

[0247] Experimental data record:

[0248] The conventional method (existing technology) and the method of the present invention are respectively used to generate and process various waveform signals, and key parameters such as linearity, signal-to-noise ratio and signal error are recorded.

[0249] Ensure the comprehensiveness and reliability of the data, obtain the average value through repeated experiments, and reduce the impact of accidental errors.

[0250] Through the above experimental steps, comparative data of the traditional method and the method of the present invention in terms of signal output accuracy, linearity and signal-to-noise ratio under different waveform types were collected and recorded. The following is a table of experimental results.

[0251] Experimental data recording

[0252] The following is a table of experimental data, which records the comparison results of the signal output accuracy, linearity and signal-to-noise ratio of the method of the present invention and the prior art under different waveform types.

[0253]

[0254] The experimental data table shows the comparison of signal output performance between the method of the present invention and the prior art under different waveform types. Through detailed analysis, it can be clearly seen that the method of the present invention is superior to the prior art in key performance indicators such as signal output accuracy, linearity and signal-to-noise ratio. The specific analysis is as follows:

[0255] Improvement of signal output accuracy: The signal error of the method of the present invention under all waveform types is significantly lower than that of the prior art. For example, the error of the sine wave is reduced from 0.01mV in the prior art to 0.005mV in the present invention, indicating that the present invention can better maintain the accuracy and stability of the signal during the signal generation and attenuation process, and reduce the error introduced by conversion and attenuation. This result proves the effectiveness of the method of the present invention in high-precision signal processing and ensures the measurement reliability of the calibration instrument in practical applications.

[0256] Significant improvement in linearity: Linearity is a key indicator for evaluating the accuracy of system response. The linearity of the method of the present invention is significantly improved under all waveform types. The linearity of the sine wave is improved from 0.5% to 0.2%, the square wave is improved from 1.0% to 0.4%, the heart rate signal is improved from 1.5% to 0.7%, the differential signal is improved from 1.2% to 0.5%, and the ECG simulation signal is improved from 1.8% to 0.6%. High linearity means that the output signal is more consistent with the theoretical model, and the nonlinear distortion of the system is effectively reduced, ensuring the accuracy and consistency of the response of the tester when processing different signal types. This improvement significantly enhances the applicability and measurement accuracy of the tester in a variety of application scenarios.

[0257] Significant improvement in signal-to-noise ratio (SNR): The signal-to-noise ratio is an important indicator for measuring signal quality. The SNR of the method of the present invention is significantly higher than that of the prior art under various waveform types. The SNR of the sine wave is increased from 60dB to 75dB, the square wave is increased from 55dB to 70dB, the heart rate signal is increased from 50dB to 65dB, the differential signal is increased from 58dB to 72dB, and the ECG simulation signal is increased from 52dB to 68dB. A higher signal-to-noise ratio means that the noise component in the output signal is effectively reduced, and the purity and reliability of the signal are greatly improved. This is especially important for calibration instruments that require high precision and high reliability. It can provide more accurate measurement results under low-amplitude signal conditions, greatly improving the application value of electrocardioencephalogram machines in clinical diagnosis and research.

[0258] Comprehensive performance improvement: Experimental results show that the method of the present invention is superior to the existing technology in key indicators such as signal output accuracy, linearity and signal-to-noise ratio, which fully demonstrates its technical innovation and practicality in improving the calibration accuracy. By optimizing each link of signal generation, conversion, attenuation and output, the method of the present invention achieves a comprehensive improvement in the overall system performance and significantly improves the measurement accuracy and reliability of the calibration instrument.

[0259] It will be appreciated that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but will be a routine task of design, fabrication, and production for those of ordinary skill having the benefit of this disclosure without undue experimentation.

[0260] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A handheld electrocardioencephalogram (ECG) tester, characterized in that: include, The verification is achieved through the following steps: S1. According to the test requirements, select multiple waveform types, establish a mathematical function model for each waveform, and define the relationship between amplitude and time; S2. Substituting the clock signal into the relationship between amplitude change and time, to obtain an expression for real-time amplitude change; S3, converting the expression of the real-time amplitude change into binary code and outputting an analog signal through a DAC; S4, performing signal attenuation on the analog signal through a Π-type symmetrical resistance attenuation network to obtain an output signal; S5. Use the analog switch to select the superposition circuit or the output circuit, where: If multiple signals need to be superimposed and output, the analog switch connects the attenuated analog signal to the superposition circuit, and the multiple signals are superimposed using an operational amplifier or a mixer; If only a single signal output is required, the analog switch will directly connect the attenuated analog signal to the output interface; S6. The analog signal of the selected path is output to the signal output circuit of the calibrator through the output interface to realize the real-time output and superposition of the signal.

2. The handheld electrocardioencephalogram (ECG) tester according to claim 1, characterized in that: The electrocardiograph calibration requirements include linear response calibration, frequency response calibration, transient response calibration, signal-to-noise ratio calibration and multi-signal superposition calibration.

3. The handheld electrocardioencephalogram (ECG) tester according to claim 2, characterized in that: According to the test requirements, select the waveform type that can effectively simulate the characteristics of real physiological signals, including: Sine wave: used for linear response and frequency response verification; Square wave: used for frequency response and transient response verification; Heart rate signal: used for signal-to-noise ratio and transient response verification, simulating the pulse characteristics of real ECG signals; Differential signal: used for transient response and frequency response verification, simulating the rate of change of signals; ECG simulation signal: used for multi-signal superposition and signal-to-noise ratio verification, simulating the complex waveforms of P wave, QRS complex wave and T wave in the real electrocardiogram.

4. The handheld electrocardioencephalogram tester according to claim 3, characterized in that: The clock signal T(t) is represented as a square wave, and its mathematical expression is: T(t)=sign(sin(2πF T t)) Where T(t) is the clock signal value at time t, which can be +1 or -1; F T The frequency of the clock signal, measured in Hertz (Hz), determines the period of the clock signal t is the time variable, in seconds (s); sign(·) is the sign function, defined as: This function converts the output of the sine function into the high and low levels of a standard square wave.

5. The handheld electrocardioencephalogram tester according to claim 4, characterized in that: Step S3 includes: The expression A(t) of real-time amplitude change is converted into binary code B[n] through sampling, quantization and encoding; Transmit the binary code B[n] to the DAC module through the digital interface; The DAC generates the corresponding analog voltage V according to the received binary code B[n]. out (n); V out (n) Output through the analog output port of the DAC for subsequent signal attenuation and processing.

6. The handheld electrocardioencephalogram tester according to claim 5, characterized in that: The π-type symmetrical resistor attenuation network includes three resistors R1, R2, and R3; The attenuation ratio calculation formula is: Among them, α is the attenuation ratio.

7. The handheld electrocardioencephalogram tester according to claim 6, characterized in that: Determine whether multiple signal superposition outputs are required according to the verification requirements and set the value of the control signal C; Superposition output: If superposition output is required, set C = 1, connect the analog switch to the superposition circuit, and generate the superposition signal V through the operational amplifier. sum ; Single output: If only a single signal output is required, set C = 0, the analog switch is directly connected to the output interface, and the output signal V is output through the buffer operational amplifier buffered ; The final output signal V final =V sum or V final =V buffered The signal is transmitted to the signal input circuit of the calibrator to achieve real-time output or superimposed output.

8. The handheld electrocardioencephalogram tester according to claim 7, characterized in that: The selected signal is input to the buffer operational amplifier; after buffering, the signal is electrically isolated by an optical isolator, and is output to the detector after synchronization to obtain an output signal.

9. The handheld electrocardioencephalogram tester according to claim 8, characterized in that: Specifically, the selected signal path output signal V final (t), the signal after buffering and isolation is V buffered (t), the synchronized signal is V synced (t), the final output signal to the calibration instrument is V output (t); V output (t)=V synced (t)=V buffered (t)·Sync(f sync ,t) Among them, V output (t): The final signal output to the tester, in volts (V); V synced (t): synchronized signal, in volts (V); V buffered (t): buffered signal, in volts (V); Sync (f sync , t): synchronization function, according to the synchronization frequency f sync Adjust the phase and timing of the signal.

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