Multi-channel neural signal recording system integrating DSP optimization and multi-module cooperative processing

Abstract

The invention introduces a multichannel neural recording system suitable for a biosensor. The multichannel neural recording system integrates nine key modules: a band-gap reference voltage module (1), a pulse signal generator module (2), a clock signal generator module (3), an instrument amplifier module (4), an impedance boosting auxiliary loop module (5), a direct current servo loop module (6), a ripple suppression loop module (7), an ADC module (8) and a DSP module (9). The band-gap reference voltage module (1), the pulse signal generator module (2) and the clock signal generator module (3) provide stable reference voltage for the system, and pulse signals and a clock are synchronous. The impedance lifting auxiliary loop module (5), the direct current servo loop module (6) and the ripple suppression loop module (7) work cooperatively, electrode offset is effectively eliminated, and the signal quality of the instrument amplifier module (4) is improved. The system is characterized in that the multi-channel instrument amplifier module is constructed, the DSP module (9) is used for carrying out complex processing on received digital signals of the ADC module (8), and the digital signals are fed back to the instrument amplifier module, so that the signal quality is further improved. The design of the system aims at realizing efficient and accurate neural signal acquisition and processing.

Description

Technical Field

[0001] This invention designs a multi-channel neural signal recording system that integrates digital signal processing (DSP) optimization and multi-module collaborative processing, involving integrated DSP technology and multi-module processing methods for improving the accuracy and efficiency of neural signal acquisition. It belongs to the field of bioelectronics. Background Art

[0002] With the rapid advancement of biomedical engineering and neuroscience, the demand for high-precision and high-efficiency neural signal recording systems is growing. Such systems play a crucial role in studying brain function, diagnosing neurological diseases, and developing brain-computer interfaces. However, existing neural signal recording technologies face a series of challenges, including weak signals, susceptibility to noise, and electrode offset, which severely impact signal quality and analysis accuracy. To overcome these challenges, researchers have been exploring more advanced signal processing techniques and system design methods. Traditional neural signal recording systems typically rely on analog circuits to amplify and filter weak neural signals. However, these analog approaches have limitations when processing multichannel signals, such as difficulty achieving high-precision signal synchronization and processing, and the stability and repeatability of analog circuits cannot meet the stringent requirements of modern neuroscience research. The development of digital signal processing (DSP) technology has provided new solutions for neural signal recording systems. DSP technology not only offers greater flexibility and programmability but also improves signal quality and analysis accuracy through algorithm optimization. In particular, multichannel neural signal recording systems that integrate DSP optimization and multi-module collaborative processing can achieve more efficient and accurate neural signal recording and analysis. This system achieves high-precision recording and analysis of neural signals through precise signal acquisition, efficient digital signal processing, and intelligent feedback mechanisms. It not only improves the signal-to-noise ratio and stability of the signal, but also enables simultaneous monitoring and analysis of multiple neural signals through multi-channel signal acquisition and processing technology, which is crucial for understanding complex neural networks and their functions. Summary of the Invention

[0003] The present invention relates to a multi-channel neural signal recording system, specifically a system suitable for biosensors. This system achieves efficient and accurate acquisition and processing of neural signals by integrating digital signal processing (DSP) optimization and multi-module collaborative processing technology. This system is designed to address existing neural signal recording technologies, including weak signals, susceptibility to noise interference, and electrode offset, while improving the signal-to-noise ratio and stability. Furthermore, through multi-channel signal acquisition and processing, it enables simultaneous monitoring and analysis of multiple neural signals.

[0004] The above-mentioned purpose of the present invention is mainly achieved through the following scheme:

[0005] A multi-channel neural recording system suitable for biosensors integrates nine key modules: a bandgap reference voltage module (1), a pulse signal generator module (2), a clock signal generator module (3), an instrumentation amplifier module (4), an impedance boost auxiliary loop module (5), a DC servo loop module (6), a ripple suppression loop module (7), an ADC module (8), and a DSP module (9).

[0006] Bandgap reference voltage module (1): provides a stable reference voltage, provides the necessary reference voltage for other modules of the entire system, and ensures the accuracy and consistency of signal processing.

[0007] Pulse signal generator module (2): generates a control signal for triggering the sampling process of the ADC module (8) to ensure the synchronization and accuracy of data acquisition.

[0008] Clock signal generator module (3): generates clock signals for synchronizing digital circuits in the system, including the ADC module (8) and the DSP module (9), to ensure consistency and coordination of data processing.

[0009] Instrumentation amplifier module (4): used to amplify weak neural signals while providing high input impedance and high common-mode rejection ratio to improve the signal-to-noise ratio.

[0010] Impedance boosting auxiliary loop module (5): by increasing input impedance, the signal receiving capability of the instrumentation amplifier module (4) is enhanced, and the load effect of the signal source is reduced.

[0011] DC servo loop module (6): used to eliminate or stabilize DC bias to ensure signal accuracy and reliability of subsequent processing.

[0012] Ripple suppression loop module (7): reduces ripples in the power supply or signal and improves signal quality, which is crucial for the performance of the instrumentation amplifier module (4) and the ADC module (8).

[0013] ADC module (8): converts the analog signal processed by the instrument amplifier module (4) and the DC servo loop module (6) into a digital signal, and provides processing data for the DSP module (9).

[0014] DSP module (9): receives the digital signal from the ADC module (8), performs complex digital signal processing, and feeds it back to the instrumentation amplifier module (4) to further improve the signal quality.

[0015] A multi-channel neural recording system suitable for biosensors is characterized by: firstly, a multi-channel instrumentation amplifier module is constructed; secondly, a DSP module (9) is used to perform complex processing on the digital signal received from the ADC module (8) and feed it back to the instrumentation amplifier module to further improve the signal quality. The system is designed to achieve efficient and accurate neural signal acquisition and processing.

[0016] The bandgap reference voltage module (1), pulse signal generator module (2) and clock signal generator module (3) provide the system with stable reference voltage, pulse signal and clock synchronization, which are the basis for the normal operation of the entire system. The impedance enhancement auxiliary loop module (5), DC servo loop module (6) and ripple suppression loop module (7) work together to improve the signal quality of the instrumentation amplifier module (4), effectively eliminate electrode offset and ensure the purity of the signal. As the core of signal processing, the instrumentation amplifier module (4) receives the signal from the impedance enhancement auxiliary loop module (5) and amplifies it. The amplified signal is further processed by the DC servo loop module (6) and the ripple suppression loop module (7) to eliminate DC bias and power supply ripple. The processed signal is sent to the ADC module (8) for analog-to-digital conversion, and the converted digital signal is sent to the DSP module (9) for deeper digital signal processing. The DSP module (9) performs complex processing on the received digital signal, including filtering, feature extraction, etc., to further analyze the neural signal. The processed signal can be fed back to the instrumentation amplifier module (4) to further improve the signal quality, forming a closed-loop control system to ensure the accuracy and reliability of signal processing.

[0017] A multi-channel neural signal recording system suitable for biosensors, characterized in that the circuit structure of the multi-channel instrument amplifier module (4) includes an operational amplifier OP1a, an operational amplifier OP1b, an operational amplifier OP2, a capacitor C IN , capacitor C FB , resistor R F , capacitor C M , capacitor C L , capacitor C HP , DC Servo Loop, Positive Feedback Loop. Among them, the capacitor C IN One end is connected to the input signal V IN The signal obtained by the chopper is connected to the other end and connected to the negative input section of the operational amplifier OP1 to filter out the noise signal in the input signal. The positive input terminal of the operational amplifier OP1a is connected to the ground, and the negative input terminal is connected to the feedback resistor R FConnected to the output of OP1a, used to set the gain of OP1a. The operational amplifier OP1b is similar to OP1a, with its positive input also connected to ground and its negative input connected to ground through the feedback resistor R F Connected to the output of OP1b, used to set the gain of OP1b. The output of OP1b is connected to the output of OP1a, forming the first stage differential amplifier. FB One section is connected to the negative input of OP1a and OP1b, and the other section is connected to the chopper to form a capacitive coupled instrumentation amplifier to filter the noise in the signal. The negative input of the operational amplifier OP2 is connected to the common output of OP1a and OP1b, and the positive input is connected to the ground. At the same time, the negative input of the operational amplifier OP2 is connected to the common output of OP1a and OP1b, and the positive input is connected to the ground. M Connected to the output of OP2 to set the gain of OP2. M Connected between the output and negative input of OP2, and R M Together they form another low-pass filter to further filter out high-frequency noise. L Connected between the output terminal of OP2 and ground for AC coupling to prevent DC components from affecting subsequent circuits. HP The feedback path automatically adjusts the output DC level of the OP2 to ensure DC stability of the output signal. The design of this loop is crucial to eliminating DC offset and improving signal accuracy. The positive feedback loop ensures the stability of the amplifier under different load conditions by increasing the input impedance. It is particularly worth mentioning that the circuit also includes a 25kHz F CHP Chopper Stabilization Circuit. This chopper stabilization circuit can significantly improve the DC accuracy and long-term stability of the amplifier.

[0018] Integrated DSP module collaborative processing system, characterized in that the circuit structure of the system includes instrument amplifier, ADC module, DSP module, Dither module, Sgn-Sgn LMS module, G DAC The output of the instrumentation amplifier is connected to the input of the ADC module to convert the analog signal into a digital signal. The ADC module contains Z -1 Delay unit and gain unit G ADC, used to sample and quantize the signal, and its output is connected to one input of the first adder. The other input of the first adder is connected to SW, which is used to selectively pass the signal to the DSP module or output it directly. The DSP module receives the signal from the first adder and performs digital signal processing on it, and its output is connected to one input of the second adder. The other input of the second adder is connected to the Sgn-Sgn LMS module, which receives the output signal d[n] and the delayed signal u[n] from the first adder and updates the filter coefficient W[n]. The output of the second adder is connected to the input of the first adder as the input signal of the first adder. The output of the Dither module is connected to Z -1 The input of the delay unit is connected to introduce jitter during the ADC quantization process to improve the quantization noise performance. -1 The output of the delay unit is connected to the input of the Sgn-Sgn LMS module to provide the delayed signal u[n]. The output of the dither module is also connected to the output of the DSP through the SW as an input signal and input to the third adder. DAC The module's input is connected to the output of the third adder to adjust the amplitude of the DAC output. The DAC module converts the digital signal back to an analog signal and feeds it into the instrumentation amplifier along with the input signal to optimize the input signal.

[0019] Compared with the existing technology, the technical solution of the present invention has the following advantages: 1. A multi-channel instrumentation amplifier module is constructed, which is specifically designed to process weak neural signals. By integrating multiple instrumentation amplifiers operating in parallel, this module can simultaneously amplify signals from different neural signal sources, thereby achieving synchronous acquisition of multi-channel signals. Each instrumentation amplifier has high input impedance and high common-mode rejection ratio (CMRR), which helps improve the signal-to-noise ratio and ensure signal purity and accuracy. In addition, by optimizing the amplifier design, including fine-tuning the gain and frequency response, the signal fidelity can be further improved. 2. A digital signal processor (DSP) module is used to perform complex processing on the digital signal received from the analog-to-digital converter (ADC) module. The DSP module uses advanced signal processing algorithms such as filtering, feature extraction, and noise suppression to enhance signal characteristics and reduce noise interference. These processing steps are crucial for extracting key information from neural signals, especially in the presence of significant background noise. 3. The signal processed by the DSP module is fed back to the instrumentation amplifier module. This feedback not only helps further adjust and optimize signal quality but also enables closed-loop control, ensuring system stability and reliability. In this way, the system is able to dynamically adapt to varying signal conditions, automatically adjusting its parameters to maintain optimal signal acquisition and processing performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Block diagram of a multi-channel neural signal recording system integrating DSP optimization and multi-module collaborative processing

[0021] Figure 2 Schematic diagram of a multi-channel instrumentation amplifier module

[0022] Figure 3 Schematic diagram of integrated DSP module collaborative processing DETAILED DESCRIPTION

[0023] In order to further introduce the specific content of the present invention and the structural characteristics of the circuit, the present invention is described in detail with reference to the accompanying drawings:

[0024] Figure 1 The block diagram of a multi-channel neural signal recording system integrating DSP optimization and multi-module collaborative processing is shown in the figure. As can be seen from the figure, a multi-channel neural recording system suitable for biosensors integrates nine key modules: a bandgap reference voltage module (1), a pulse signal generator module (2), a clock signal generator module (3), an instrumentation amplifier module (4), an impedance enhancement auxiliary loop module (5), a DC servo loop module (6), a ripple suppression loop module (7), an ADC module (8) and a DSP module (9).

[0025] Bandgap reference voltage module (1): provides a stable reference voltage, provides the necessary reference voltage for other modules of the entire system, and ensures the accuracy and consistency of signal processing.

[0026] Pulse signal generator module (2): generates a control signal for triggering the sampling process of the ADC module (8) to ensure the synchronization and accuracy of data acquisition.

[0027] Clock signal generator module (3): generates clock signals for synchronizing digital circuits in the system, including the ADC module (8) and the DSP module (9), to ensure consistency and coordination of data processing.

[0028] Instrumentation amplifier module (4): used to amplify weak neural signals while providing high input impedance and high common-mode rejection ratio to improve the signal-to-noise ratio.

[0029] Impedance boosting auxiliary loop module (5): by increasing input impedance, the signal receiving capability of the instrumentation amplifier module (4) is enhanced, and the load effect of the signal source is reduced.

[0030] DC servo loop module (6): used to eliminate or stabilize DC bias to ensure signal accuracy and reliability of subsequent processing.

[0031] Ripple suppression loop module (7): reduces ripples in the power supply or signal and improves signal quality, which is crucial for the performance of the instrumentation amplifier module (4) and the ADC module (8).

[0032] ADC module (8): converts the analog signal processed by the instrument amplifier module (4) and the DC servo loop module (6) into a digital signal, and provides processing data for the DSP module (9).

[0033] DSP module (9): receives the digital signal from the ADC module (8), performs complex digital signal processing, and feeds it back to the instrumentation amplifier module (4) to further improve the signal quality.

[0034] A multi-channel neural recording system suitable for biosensors is characterized by: firstly, a multi-channel instrumentation amplifier module is constructed; secondly, a DSP module (9) is used to perform complex processing on the digital signal received from the ADC module (8) and feed it back to the instrumentation amplifier module to further improve the signal quality. The system is designed to achieve efficient and accurate neural signal acquisition and processing.

[0035] The bandgap reference voltage module (1), pulse signal generator module (2) and clock signal generator module (3) provide the system with stable reference voltage, pulse signal and clock synchronization, which are the basis for the normal operation of the entire system. The impedance enhancement auxiliary loop module (5), DC servo loop module (6) and ripple suppression loop module (7) work together to improve the signal quality of the instrumentation amplifier module (4), effectively eliminate electrode offset and ensure the purity of the signal. As the core of signal processing, the instrumentation amplifier module (4) receives the signal from the impedance enhancement auxiliary loop module (5) and amplifies it. The amplified signal is further processed by the DC servo loop module (6) and the ripple suppression loop module (7) to eliminate DC bias and power supply ripple. The processed signal is sent to the ADC module (8) for analog-to-digital conversion, and the converted digital signal is sent to the DSP module (9) for deeper digital signal processing. The DSP module (9) performs complex processing on the received digital signal, including filtering, feature extraction, etc., to further analyze the neural signal. The processed signal can be fed back to the instrumentation amplifier module (4) to further improve the signal quality, forming a closed-loop control system to ensure the accuracy and reliability of signal processing.

[0036] Figure 2 The invention relates to a multi-channel neural signal recording system suitable for biosensors, characterized in that the circuit structure of the multi-channel instrument amplifier module (4) includes an operational amplifier OP1a, an operational amplifier OP1b, an operational amplifier OP2, a capacitor C IN , capacitor C FB , resistor RF , capacitor C M , capacitor C L , capacitor C HP , DC Servo Loop, Positive Feedback Loop. Among them, the capacitor C IN One end is connected to the input signal V IN The signal obtained by the chopper is connected to the other end and connected to the negative input section of the operational amplifier OP1 to filter out the noise signal in the input signal. The positive input terminal of the operational amplifier OP1a is connected to the ground, and the negative input terminal is connected to the feedback resistor R F Connected to the output of OP1a, used to set the gain of OP1a. The operational amplifier OP1b is similar to OP1a, with its positive input also connected to ground and its negative input connected to ground through the feedback resistor R F Connected to the output of OP1b, used to set the gain of OP1b. The output of OP1b is connected to the output of OP1a, forming the first stage differential amplifier. FB One section is connected to the negative input of OP1a and OP1b, and the other section is connected to the chopper to form a capacitive coupled instrumentation amplifier to filter the noise in the signal. The negative input of the operational amplifier OP2 is connected to the common output of OP1a and OP1b, and the positive input is connected to the ground. At the same time, the negative input of the operational amplifier OP2 is connected to the common output of OP1a and OP1b, and the positive input is connected to the ground. M Connected to the output of OP2 to set the gain of OP2. M Connected between the output and negative input of OP2, and R M Together they form another low-pass filter to further filter out high-frequency noise. L Connected between the output terminal of OP2 and ground for AC coupling to prevent DC components from affecting subsequent circuits. HP The feedback path automatically adjusts the output DC level of the OP2 to ensure DC stability of the output signal. The design of this loop is crucial to eliminating DC offset and improving signal accuracy. The positive feedback loop ensures the stability of the amplifier under different load conditions by increasing the input impedance. It is particularly worth mentioning that the circuit also includes a 25kHz F CHP Chopper Stabilization Circuit. This chopper stabilization circuit can significantly improve the DC accuracy and long-term stability of the amplifier.

[0037] Figure 3It is an integrated DSP module collaborative processing system, characterized in that the circuit structure of the system includes an instrument amplifier, an ADC module, a DSP module, a Dither module, a Sgn-Sgn LMS module, a G DAC The output of the instrumentation amplifier is connected to the input of the ADC module to convert the analog signal into a digital signal. The ADC module contains Z -1 Delay unit and gain unit G ADC , used to sample and quantize the signal, and its output is connected to one input of the first adder. The other input of the first adder is connected to SW, which is used to selectively pass the signal to the DSP module or output it directly. The DSP module receives the signal from the first adder and performs digital signal processing on it, and its output is connected to one input of the second adder. The other input of the second adder is connected to the Sgn-Sgn LMS module, which receives the output signal d[n] and the delayed signal u[n] from the first adder and updates the filter coefficient W[n]. The output of the second adder is connected to the input of the first adder as the input signal of the first adder. The output of the Dither module is connected to Z -1 The input of the delay unit is connected to introduce jitter during the ADC quantization process to improve the quantization noise performance. -1 The output of the delay unit is connected to the input of the Sgn-Sgn LMS module to provide the delayed signal u[n]. The output of the dither module is also connected to the output of the DSP through the SW as an input signal and input to the third adder. DAC The module's input is connected to the output of the third adder to adjust the amplitude of the DAC output. The DAC module converts the digital signal back to an analog signal and feeds it into the instrumentation amplifier along with the input signal to optimize the input signal.

[0038] Overall system operation process 1. Initialization: When the system starts, initialize the parameters of each module, including the bandgap reference voltage, clock signal and pulse signal generator. 2. Signal acquisition: The multi-channel instrumentation amplifier module receives the input signal of the neural signal source, and uses the input impedance improvement loop module, DC servo loop module and ripple suppression loop module for preliminary amplification and processing. 3. Signal digitization: The ADC module converts the processed analog signal into a digital signal. 4. Digital signal processing: The DSP module performs complex processing on the received digital signal, including filtering, feature extraction and adaptive filtering. 5. Feedback optimization: The processed signal is converted back to an analog signal through the DAC and fed back to the instrumentation amplifier module to further improve the signal quality. 6. Output: The final processed signal is transmitted through the output terminal V OUTOutput for subsequent analysis or application.

[0039] The above description is a specific embodiment of the present invention, and the principles of the present invention have been described in the above description. The scope of protection of the present invention is not limited to this. Any person skilled in the art who makes simple structural changes within the scope of the present invention shall fall within the scope of this invention. Therefore, the scope of protection of the present invention shall be based on the scope of the claims.

Claims

1. The present invention relates to a multi-channel neural signal recording system suitable for biosensors with integrated DSP optimization and multi-module collaborative processing, characterized in that: The system integrates nine key modules, namely a bandgap reference voltage module (1), a pulse signal generator module (2), a clock signal generator module (3), an instrumentation amplifier module (4), an impedance enhancement auxiliary loop module (5), a DC servo loop module (6), a ripple suppression loop module (7), an ADC module (8) and a DSP module (9). The bandgap reference voltage module (1) provides a stable reference voltage for the system through a specific circuit design, ensuring the normal operation of other modules and the accuracy of signal processing; the pulse signal generator module (2) can generate a pulse signal of a specific frequency and amplitude for driving the relevant operations and signal synchronization of the system; the clock signal generator module (3) provides an accurate clock signal for the timing control and synchronous operation of the system, ensuring that each module performs the corresponding function at the correct time point. The multi-channel instrumentation amplifier module (4) includes multiple independent channels, which can simultaneously amplify the input neural signals, and the channels are isolated from each other to avoid mutual interference between signals, thereby improving the acquisition efficiency and data volume of the system. The impedance enhancement auxiliary loop module (5) effectively improves the input impedance of the electrode through a specific circuit structure, reduces the polarization effect between the electrode and biological tissue, and reduces the impact of electrode offset on signal quality; the DC servo loop module (6) can monitor and compensate the DC bias voltage generated by the electrode offset in real time, and stabilize the bias voltage at an extremely low level through a feedback control mechanism; the ripple suppression loop module (7) uses advanced filtering technology and circuit design to effectively suppress high-frequency noise and ripple in the signal, reduce signal distortion, and improve signal purity and readability. The ADC module (8) converts the pre-processed analog neural signal into a digital signal. The converted digital signal has high resolution and low quantization error, and can accurately reflect the characteristics and information of the original neural signal. The DSP module (9) has powerful digital signal processing capabilities and can perform complex algorithm processing on the received digital signal, including but not limited to filtering, feature extraction, signal enhancement, noise suppression and other operations, and feeds the processed results back to the instrumentation amplifier module (4) to achieve closed-loop control and optimization of the system, thereby improving the overall performance and signal processing effect of the system. The modules of the system are connected by high-speed, low-noise signal transmission lines. The overall layout and structural design are compact and reasonable, which is easy to integrate and install in biosensors and adapt to different application scenarios and usage requirements. The present invention relates to a multi-channel neural signal recording system suitable for a biosensor, characterized in that the circuit structure of the multi-channel instrument amplifier module (4) includes an operational amplifier OP1a, an operational amplifier OP1b, an operational amplifier OP2, a capacitor C IN , capacitor C FB , resistor R F , capacitor C M , capacitor C L , capacitor C HP , DC Servo Loop, Positive Feedback Loop. Among them, the capacitor C IN One end is connected to the input signal V IN The signal obtained by the chopper is connected to the other end and connected to the negative input section of the operational amplifier OP1 to filter out the noise signal in the input signal. The positive input terminal of the operational amplifier OP1a is connected to the ground, and the negative input terminal is connected to the feedback resistor R F Connected to the output of OP1a, used to set the gain of OP1a. The operational amplifier OP1b is similar to OP1a, with its positive input also connected to ground and its negative input connected to ground through the feedback resistor R F Connected to the output of OP1b, used to set the gain of OP1b. The output of OP1b is connected to the output of OP1a, forming the first stage differential amplifier. FB One section is connected to the negative input of OP1a and OP1b, and the other section is connected to the chopper to form a capacitive coupled instrumentation amplifier to filter the noise in the signal. The negative input of the operational amplifier OP2 is connected to the common output of OP1a and OP1b, and the positive input is connected to the ground. At the same time, the negative input of the operational amplifier OP2 is connected to the common output of OP1a and OP1b, and the positive input is connected to the ground. M Connected to the output of OP2 to set the gain of OP2. M Connected between the output and negative input of OP2, it forms another low-pass filter together with R_M to further filter out high-frequency noise. L Connected between the output terminal of OP2 and ground for AC coupling to prevent DC components from affecting subsequent circuits. HP The feedback path automatically adjusts the output DC level of the OP2 to ensure DC stability of the output signal. The design of this loop is crucial to eliminating DC offset and improving signal accuracy. The positive feedback loop ensures the stability of the amplifier under different load conditions by increasing the input impedance. It is particularly worth mentioning that the circuit also includes a 25kHz F CHP Chopper Stabilization Circuit. This chopper stabilization circuit can significantly improve the DC accuracy and long-term stability of the amplifier. The present invention relates to an integrated DSP module collaborative processing system, which is characterized in that the circuit structure of the system includes an instrument amplifier, an ADC module, a DSP module, a Dither module, a Sgn-Sgn LMS module, a G DAC The output of the instrumentation amplifier is connected to the input of the ADC module to convert the analog signal into a digital signal. The ADC module contains Z -1 Delay unit and gain unit G ADC , used to sample and quantize the signal, and its output is connected to one input of the first adder. The other input of the first adder is connected to SW, which is used to selectively pass the signal to the DSP module or output it directly. The DSP module receives the signal from the first adder and performs digital signal processing on it, and its output is connected to one input of the second adder. The other input of the second adder is connected to the Sgn-Sgn LMS module, which receives the output signal d[n] and the delayed signal u[n] from the first adder and updates the filter coefficient W[n]. The output of the second adder is connected to the input of the first adder as the input signal of the first adder. The output of the Dither module is connected to Z -1 The input of the delay unit is connected to introduce jitter during the ADC quantization process to improve the quantization noise performance. -1 The output of the delay unit is connected to the input of the Sgn-Sgn LMS module to provide the delayed signal u[n]. The output of the dither module is also connected to the output of the DSP through the SW as an input signal and input to the third adder. DAC The module's input is connected to the output of the third adder to adjust the amplitude of the DAC output. The DAC module converts the digital signal back to an analog signal and feeds it into the instrumentation amplifier along with the input signal to optimize the input signal.

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