Bio-electricity signal and electrode impedance acquisition system and method

Abstract

The invention provides a bio-electricity signal and electrode impedance acquisition system and method, and relates to the technical field of bio-electricity signal acquisition and processing. According to the specific technical scheme, the integrated bio-electricity signal acquisition chip is used for generating an alternating current excitation signal with a specific frequency and a fixed amplitude through an internally integrated excitation source; continuously applying an alternating current excitation signal to one or more target electrodes through an internal analog switch array; the integrated bio-electricity signal acquisition chip is used for acquiring a mixed digital signal from a target electrode, and the mixed digital signal is formed by superposing a bio-electricity signal, a noise signal and an impedance response signal generated by an alternating current excitation signal on target electrode impedance; and the microcontroller unit is used for extracting electrode impedance information from the mixed digital signal and recovering the bio-electricity signal.

Description

Technical Field

[0001] This disclosure relates to the field of bioelectric signal acquisition and processing technology, and in particular to a bioelectric signal and electrode impedance acquisition system and method. Background Technology

[0002] Electroencephalogram (EEG) signal acquisition is an important tool in modern medical diagnosis and scientific research. In EEG signal acquisition, the contact impedance between the electrodes and the skin is a key factor affecting signal quality. In clinical applications, the American Academy of Sleep Medicine (AASM) explicitly requires in its sleep staging standards that the impedance of EEG electrodes should be less than 5 kΩ, and the impedance of ECG and EMG electrodes should be less than 10 kΩ. In long-term monitoring scenarios such as sleep monitoring and epilepsy diagnosis, electrode impedance can change due to factors such as patient activity and sweating; therefore, real-time, online monitoring of electrode impedance is crucial.

[0003] Most existing electrode impedance detection schemes rely on additional, independent excitation sources and detection circuits (impedance detection chips or circuit modules). These external modules generate specific excitation signals (such as AC signals of a specific frequency), which are switched to the measuring electrodes through an analog switch matrix. The impedance is then calculated through another set of measurement circuits, which increases system complexity, cost, power consumption, and circuit size. This is not conducive to the portability and miniaturization of the device, which is contrary to the current development trend of wearable and portable medical devices. Summary of the Invention

[0004] This disclosure provides a bioelectrical signal and electrode impedance acquisition system and method, which solves the problems of insufficient portability and miniaturization in existing electrode impedance detection schemes. The technical solution is as follows:

[0005] According to a first aspect of the present disclosure, a bioelectric signal and electrode impedance acquisition system is provided, characterized in that it includes an integrated bioelectric signal acquisition chip and a microcontroller unit;

[0006] The integrated bioelectric signal acquisition chip is used to continuously apply an AC excitation signal of a specific frequency and fixed amplitude generated by an internally integrated excitation source to one or more target electrodes.

[0007] The integrated bioelectric signal acquisition chip is used to acquire a mixed digital signal from the target electrode. The mixed digital signal includes a superposition of a bioelectric signal, a noise signal, and an impedance response signal generated on the impedance of the target electrode by the AC excitation signal.

[0008] The microcontroller unit is used to extract electrode impedance information from the mixed digital signal and recover the bioelectric signal.

[0009] This disclosure utilizes a collaborative architecture of an integrated EEG acquisition chip and a microcontroller unit, reusing the excitation source and analog switch array integrated within the chip. This eliminates the need for external independent excitation sources, detection circuits, and analog switch matrices, fundamentally simplifying the system hardware architecture and reducing complexity, cost, and size, thus adapting to the development trend of wearable and portable medical devices. By continuously applying an AC excitation signal to the target electrode and simultaneously acquiring a mixed digital signal containing EEG signals, noise signals, and impedance response signals, combined with digital domain synchronous quadrature demodulation technology to extract the electrode complex impedance (including real and imaginary parts) and digital notch filtering to recover the pure EEG signal, real-time synchronous electrode impedance detection and EEG signal acquisition are achieved. This avoids the interruption interference to the continuity of EEG signals caused by traditional time-division detection, eliminates the crosstalk risk of external excitation sources through homogeneous design, and breaks through the limitation of existing technologies that can only measure impedance amplitude, comprehensively reflecting the electrode contact state.

[0010] In one embodiment, in extracting electrode impedance information from the mixed digital signal, the microcontroller unit is specifically configured to:

[0011] In the digital domain, an in-phase digital reference signal and a quadrature digital reference signal are generated that are synchronized with the frequency and phase of the AC excitation signal;

[0012] The mixed digital signal is multiplied by the in-phase reference signal and the quadrature reference signal;

[0013] The product results are subjected to a fixed-duration integral averaging process to obtain the in-phase integral result and the orthogonal integral result;

[0014] Based on the in-phase integration result and the quadrature integration result, combined with the current amplitude of the excitation source, the electrode group impedance information is calculated. The electrode impedance information is the electrode complex impedance, which includes the real part and the imaginary part of the electrode complex impedance.

[0015] This disclosure generates in-phase / quadrature digital reference signals that are strictly synchronized with the excitation signal, ensuring phase matching in multiplication operations, reducing impedance calculation errors, and improving extraction accuracy; integral averaging can suppress non-periodic interference, improving result stability and signal-to-noise ratio; it obtains complex impedances containing real and imaginary parts, accurately reflecting electrode contact characteristics and ensuring acquisition reliability; digital domain processing has strong anti-interference capabilities and is easy to upgrade and optimize software, improving system flexibility.

[0016] In one embodiment, regarding the recovery of the bioelectrical signal, the microcontroller unit is specifically configured to:

[0017] The mixed digital signal is subjected to digital notch filtering to remove the impedance response signal and noise signal, thereby obtaining the bioelectric signal.

[0018] This disclosure employs digital notch filtering to specifically remove impedance response signals and noise signals from mixed digital signals. It can accurately locate the frequency band of interference signals, effectively filtering out interference while preserving the effective frequency components of bioelectrical signals to the greatest extent, avoiding the distortion of bioelectrical signals caused by traditional filtering methods. It can directly recover bioelectrical signals from mixed digital signals without the need for additional signal separation hardware, simplifying the processing flow, improving the real-time performance of bioelectrical signal recovery, and ensuring the accuracy of subsequent feature extraction, disease diagnosis, and other analyses of bioelectrical signals such as electrocardiograms and electroencephalograms.

[0019] In one embodiment, the formula for calculating the impedance information of the electrode group is:

[0020] R = K * V_I / I;

[0021] X c =K*V_Q / I;

[0022] Where R represents the real part, K ​​represents the proportionality coefficient, V_I represents the in-phase integral result, V_Q represents the orthogonal integral result, and X c Let I represent the imaginary part, and let I represent the current amplitude of the excitation source.

[0023] In one embodiment, regarding the generation of an in-phase digital reference signal synchronized with the frequency and phase of the AC excitation signal, the microcontroller unit is specifically configured to:

[0024] Digital phase-locked loop technology is used to determine the phase of the AC excitation signal by analyzing the zero-crossing points of the mixed digital signal;

[0025] Based on phase locking, the DDS algorithm is used to generate in-phase reference signals.

[0026] This disclosure employs digital phase-locked loop (PLL) technology to determine the phase of the AC excitation signal by analyzing the zero-crossing points of the mixed digital signal. This method has strong anti-interference capabilities and is unaffected by noise or bioelectrical signals in the mixed digital signal. It can accurately track the phase changes of the excitation signal and achieve stable phase locking even if the excitation signal has a small frequency drift. Based on the locked phase, a DDS algorithm is used to generate an in-phase reference signal. Compared with the traditional method of generating reference signals using analog oscillators, this method has higher frequency resolution and better phase accuracy. Moreover, the signal generation process is programmable and controllable, and the reference signal parameters can be flexibly adjusted, ensuring the frequency and phase synchronization between the in-phase reference signal and the AC excitation signal. This provides a reliable benchmark for subsequent accurate impedance calculations.

[0027] In one embodiment, regarding the generation of an orthogonal digital reference signal synchronized with the frequency and phase of the AC excitation signal, the microcontroller unit is specifically configured to:

[0028] The in-phase reference signal is digitally phase-shifted by 90° to generate the quadrature digital reference signal.

[0029] This disclosure directly generates orthogonal digital reference signals by performing a 90° digital phase shift on in-phase reference signals. This eliminates the need for independently designing orthogonal signal generation circuits or algorithms, significantly simplifying the generation process and reducing system development complexity and hardware costs. Furthermore, generating orthogonal signals based on the phase shift of in-phase reference signals ensures that the phase difference between the two signals is precisely 90°, avoiding the phase deviation problem that easily occurs when generating orthogonal signals independently. This reduces phase errors in complex impedance calculations from the source and further improves the accuracy of electrode impedance extraction.

[0030] In one embodiment, the duration of the integral averaging process is an integer multiple of the period of the AC excitation signal.

[0031] The integration time of this invention is set to an integer multiple of the excitation signal period. This utilizes periodicity to cancel out interference, suppress periodic noise components, improve the signal-to-noise ratio and stability of the integration results, and ensure the accuracy and repeatability of impedance calculation.

[0032] In one embodiment, the specific frequency is far from the effective frequency of the bioelectric signal.

[0033] The excitation signal frequency in this disclosure is far from the effective frequency of the bioelectric signal, avoiding interference and masking caused by frequency overlap, ensuring the integrity of the bioelectric signal; reducing the difficulty of filtering and separation, reducing signal loss, and improving separation efficiency and quality.

[0034] In one embodiment, regarding the specific frequency, fixed amplitude AC excitation signal generated by the internally integrated excitation source, the integrated bioelectric signal acquisition chip is specifically used for:

[0035] Configure the lead shedding control register of the integrated bioelectric signal acquisition chip, set the current amplitude of the internal constant current source to 24nA, and set it to fDR / 4 working mode to generate an AC excitation signal of a specific frequency and fixed amplitude.

[0036] This disclosure reuses the chip's internal resources, eliminating the need for external excitation circuits, simplifying system design, and reducing cost and size; the 24nA amplitude balances biosafety and the detectability of the response signal, and the frequency generated by the fDR / 4 mode is far from the effective frequency band of bioelectricity, reducing signal interference and ensuring detection and acquisition accuracy.

[0037] According to a second aspect of the present disclosure, a method for acquiring bioelectrical signals and electrode impedance is provided, characterized in that the method is applied to the bioelectrical signal and electrode impedance acquisition system described in any one of the first aspects, and the method includes:

[0038] The integrated bioelectric signal acquisition chip continuously applies an AC excitation signal of a specific frequency and fixed amplitude generated by an internally integrated excitation source to one or more target electrodes.

[0039] The integrated bioelectric signal acquisition chip acquires a mixed digital signal from the target electrode. The mixed digital signal includes: a superposition of a bioelectric signal, a noise signal, and an impedance response signal generated by the AC excitation signal on the impedance of the target electrode.

[0040] The microcontroller unit extracts electrode impedance information from the mixed digital signal and recovers the bioelectric signal.

[0041] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0042] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0043] Figure 1 This is a schematic diagram of the structure of a bioelectric signal acquisition system shown in an embodiment of this disclosure;

[0044] Figure 2 This is a schematic diagram of the equivalent circuit model of the electrode-skin contact impedance shown in the embodiments of this disclosure;

[0045] Figure 3 This is a schematic diagram of another bioelectrical signal and electrode impedance acquisition system shown in this embodiment. Figure 1 ;

[0046] Figure 4 This is a schematic diagram of another bioelectrical signal and electrode impedance acquisition system shown in this embodiment. Figure 2 ;

[0047] Figure 5 This is a flowchart illustrating a method for acquiring bioelectrical signals and electrode impedance according to an embodiment of this disclosure. Detailed Implementation

[0048] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0049] Figure 1 This is a schematic diagram of a bioelectrical signal and electrode impedance acquisition system according to an embodiment of this disclosure, as shown below. Figure 1 As shown, the bioelectric signal acquisition system includes an integrated bioelectric signal acquisition chip 1 and a microcontroller unit 2;

[0050] The bioelectric signals disclosed herein may include: electrocardiogram (ECG), electromyography (EMG), and electroencephalogram (EEG).

[0051] The integrated bioelectric signal acquisition chip is used to continuously apply an AC excitation signal to one or more target electrodes through an AC excitation signal of a specific frequency and fixed amplitude generated by an internally integrated excitation source.

[0052] The integrated bioelectric signal acquisition chip provides a stable, safe, and interference-free built-in excitation source for electrode impedance detection, replacing the complex external excitation circuits in existing technologies.

[0053] Integrated bioelectric signal acquisition chips can use TI's ADS series bioelectric signal analog front-end chips, such as ADS1298, ADS1293, ADS1296, etc.; they can also use ADI's ADA series chips, such as ADAS1000; they can also use Innosilicon's ADSD1299; and they can also use some domestic chips for measuring biological tissue components, such as Chipsea Technologies' CS1256, etc.

[0054] The integrated bioelectric signal acquisition chip has a built-in constant current source for lead detachment detection. The original function of this constant current source for lead detachment detection is to determine whether the electrode has detached.

[0055] In one embodiment, regarding the specific frequency, fixed amplitude AC excitation signal generated by the internally integrated excitation source, the integrated bioelectric signal acquisition chip is specifically used for:

[0056] Configure the lead shedding control register of the integrated bioelectric signal acquisition chip, set the current amplitude of the internal constant current source to 24nA, and set it to fDR / 4 working mode to generate an AC excitation signal of a specific frequency and fixed amplitude.

[0057] In this embodiment, a square wave signal is selected as the excitation signal because the integrated EEG acquisition chip (such as ADS1299) only supports square wave output mode. From a technical perspective, other waveforms such as sine waves and triangle waves are theoretically equally applicable, and the corresponding synchronous quadrature demodulation processing logic remains consistent. However, the square wave signal has more prominent practical advantages: First, it is highly compatible with the signal characteristics of digital systems, and the generation process is simple and efficient, requiring no additional complex analog circuit support. Second, its phase characteristics are clear and well-defined, and the calculation difficulty of zero-crossing detection and synchronous calibration is low, which can significantly improve the accuracy of the demodulation process. Third, its harmonic components are concentrated and the frequency can be accurately predicted, which can be easily filtered out by subsequent digital notch filtering, effectively avoiding the impact of harmonic interference on EEG signals and impedance detection, and ultimately ensuring that the system obtains a better signal-to-noise ratio.

[0058] Specifically, parameter calibration is performed through the chip's internal dedicated register (LOFF register, i.e., lead detachment control register), without requiring hardware modification. The specific configuration process is as follows:

[0059] Current amplitude configuration: The output current of the internal constant current source is fixed at 24nA (the stable value calibrated by the chip at the factory, which satisfies both the detectability of the impedance response signal and the safety standards of biomedical devices, and will not cause physiological stimulation to the human body).

[0060] Frequency mode configuration: Set to "fDR / 4 mode" (fDR is the chip's data sampling rate). When fDR is configured to 1kSPS (1000 samples per second), the fundamental frequency of the AC excitation signal can reach 250Hz, which is higher than the frequency band of bioelectric signals.

[0061] Signal type generation: Output low-frequency AC square wave signal (the harmonic characteristics of the square wave signal are controllable and can be easily synchronized and demodulated by digital circuits to adapt to subsequent signal processing flow).

[0062] Setting the frequency to 250Hz keeps it far away from the effective frequency band of most biological signals (such as EEG 0.5-100Hz, ECG 0.05-100Hz, EMG 10-500Hz; for EMG signals, when fDR is configured to 4kSPS (4000 samples per second), the fundamental frequency of the AC excitation signal can reach 1000Hz. fDR supports up to 16kSPS, which means the fundamental frequency of the AC excitation signal can reach up to 4000Hz). This avoids the natural superposition and interference between the excitation signal and the biological signal at the frequency level, reducing the difficulty of subsequent "signal separation".

[0063] Setting the amplitude to 24nA can match the resolution (e.g., 24-bit) of the chip's built-in analog-to-digital converter (ADC) and the gain range of the programmable gain amplifier (PGA), generating a sufficiently strong response voltage (V = I × Z) on the electrode impedance, ensuring that the impedance response signal can still be accurately acquired even when the electrode impedance is at the AASM standard threshold (EEG < 5kΩ, ECG / EMG < 10kΩ).

[0064] In one embodiment, the specific frequency is far from the effective frequency of the bioelectric signal, which can be 0.5 Hz to 100 Hz.

[0065] By channel selection of the analog switch array inside the integrated bioelectric signal acquisition chip, the 250Hz AC square wave excitation signal generated by the constant current source inside the integrated bioelectric signal acquisition chip is continuously and uninterruptedly injected into the target electrode (supporting parallel application of multiple electrodes, adapting to multi-channel bio-acquisition scenarios, such as a 16-channel EEG cap).

[0066] Existing technologies mostly employ "time-division application," which requires pausing biosignal acquisition when switching channels to measure impedance, resulting in signal continuity interruption. In contrast, "continuous application" allows the excitation signal and biosignal to be superimposed on the electrode in real time, providing a prerequisite for the chip to "synchronously acquire mixed digital signals" and ensuring the integrity of the biosignal (especially suitable for scenarios requiring long-term continuous acquisition, such as epilepsy diagnosis and sleep monitoring).

[0067] The integrated bioelectric signal acquisition chip is used to acquire a mixed digital signal from the target electrode. The mixed digital signal includes a superposition of a bioelectric signal, a noise signal, and an impedance response signal generated on the impedance of the target electrode by the AC excitation signal.

[0068] The integrated bioelectric signal acquisition chip synchronously acquires mixed digital signals containing valid signals and interference signals.

[0069] Integrated biosensor chips have built-in high-resolution ADCs (such as the 24-bit ADC of the ADS1299) that are adapted to the weak characteristics of biosignals at the microvolt level, preventing effective signals from being drowned out by noise.

[0070] The acquired signal is a superposition of three types of signals, as shown in the formula:

[0071] V_mix[n]=V_bio[n]+V_imp[n]+V_noise[n];

[0072] Where V_mix[n] represents a mixed digital signal;

[0073] V_bio[n] represents bioelectric signals (such as EEG 0.5-100Hz, ECG 0.05-100Hz, EMG 10-500Hz, random low / medium frequency characteristics, amplitude in microvolts);

[0074] V_imp[n] represents the impedance response signal (the voltage drop generated on the electrode impedance by the AC excitation signal, which is in phase and frequency with the excitation signal, and its amplitude is proportional to the electrode impedance);

[0075] V_noise[n] represents noise signals (including environmental electromagnetic interference, internal chip thermal noise, skin contact noise, etc., without fixed frequency and phase).

[0076] The sampling rate of the ADC (fDR = 1kSPS) is 4 times the frequency of the excitation signal (250Hz), which satisfies the Nyquist sampling theorem and avoids signal aliasing. At the same time, the acquisition action and the application of the excitation signal are "synchronized in real time", that is, the mixed digital signal acquisition is completed at the same time and on the same channel without time difference, ensuring the phase consistency of V_imp[n] with the excitation signal.

[0077] In this embodiment, weak biological signals are amplified by PGA (gain selectable from 1 to 24 times), and combined with the high quantization accuracy of 24-bit ADC, V_bio[n] and V_imp[n] are accurately captured, thereby improving the signal-to-noise ratio of the original data.

[0078] The microcontroller unit is used to extract electrode impedance information from the mixed digital signal and recover the bioelectric signal.

[0079] The microcontroller unit (e.g., MCU, such as the STM32 series) establishes high-speed communication with the integrated biosignal acquisition chip via the SPI interface. The operating clock of the microcontroller unit is strictly synchronized with the main clock of the integrated biosignal acquisition chip (e.g., the main clock of the ADS1299 is 2.048MHz), ensuring that the timing of the application of the excitation signal is completely aligned with the subsequent signal acquisition timing of the chip, without phase offset or time delay.

[0080] In one embodiment, in extracting electrode impedance information from the mixed digital signal, the microcontroller unit is specifically configured to:

[0081] In the digital domain, an in-phase digital reference signal and a quadrature digital reference signal are generated that are synchronized with the frequency and phase of the AC excitation signal.

[0082] Specifically, in generating an in-phase digital reference signal synchronized with the frequency and phase of the AC excitation signal, the microcontroller unit is specifically configured to perform the following steps A1-A4:

[0083] A1. Using digital phase-locked loop technology, the phase of the AC excitation signal is determined by analyzing the zero-crossing point of the mixed digital signal;

[0084] Based on phase locking, the DDS algorithm is used to generate in-phase reference signals.

[0085] In one embodiment, regarding the generation of an orthogonal digital reference signal synchronized with the frequency and phase of the AC excitation signal, the microcontroller unit is specifically configured to:

[0086] The in-phase reference signal is digitally phase-shifted by 90° to generate the quadrature digital reference signal.

[0087] The MCU generates two types of reference signals that are strictly synchronized with the excitation signal through a digital phase-locked loop (PLL) + direct digital frequency synthesis (DDS) algorithm:

[0088] The unit amplitude square wave of the in-phase reference signal (Ref_I[n]) and the 250Hz AC excitation signal generated by the chip are "completely consistent in frequency and completely synchronized in phase" (by analyzing the zero crossing point of the mixed digital signal, the phase of the excitation signal is accurately locked to avoid demodulation errors caused by phase shift);

[0089] The quadrature reference signal (Ref_Q[n]) is obtained by performing a 90° digital phase shift on the in-phase reference signal. It has the same frequency as the excitation signal but is 90° out of phase, and is used to capture the imaginary part of the impedance.

[0090] In this disclosure, the reference signal is only in phase and orthogonal to V_imp[n] (impedance response signal), and has no correlation with V_bio[n] (biological signal) and V_noise[n] (noise), providing a physical basis for signal separation.

[0091] A2. Perform a multiplication operation on the mixed digital signal, the in-phase reference signal, and the quadrature reference signal.

[0092] The mixed digital signal (V_mix[n] = V_bio[n] + V_imp[n] + V_noise[n]) is multiplied point by point with the in-phase reference signal (Ref_I[n]) to obtain the in-phase product signal: Product_I[n] = V_mix[n] × Ref_I[n];

[0093] The mixed digital signal is multiplied point by point with the orthogonal reference signal (Ref_Q[n]) to obtain the orthogonal product signal: Product_Q[n] = V_mix[n] × Ref_Q[n].

[0094] For the impedance response signal (V_imp[n]), it is in phase and frequency with the excitation signal. Therefore, after multiplying it with Ref_I[n], a stable positive DC component is obtained (if V_imp[n] is in the positive half-cycle, Ref_I[n] is also positive, and the product is positive; during the negative half-cycle, both are negative, and the product is still positive); after multiplying it with Ref_Q[n], a stable orthogonal DC component is obtained (the phase difference is 90°, but the amplitude is proportional to the capacitive reactance).

[0095] For biological signals (V_bio[n]), which are random, low-frequency and uncorrelated with the reference signal (250Hz), after multiplication they will be randomly assigned as alternating positive and negative signals (without a stable DC component);

[0096] For the noise signal (V_noise[n]), it has no fixed frequency and phase, is not correlated with the reference signal, and after multiplication, it is also an alternating signal with alternating positive and negative values ​​(without a stable DC component).

[0097] A3. Perform a fixed-duration integral averaging on the product results to obtain the in-phase integral result and the orthogonal integral result.

[0098] The duration of the integral averaging process is an integer multiple of the period of the AC excitation signal.

[0099] The integration duration must be set to an integer multiple of the excitation signal period (preferably 64ms, corresponding to 16 complete cycles of a 250Hz excitation signal, with each cycle being 4ms), to effectively suppress interference from EEG signals and random noise.

[0100] Integrating over integer multiples of a period ensures that the DC component of the impedance response signal is fully accumulated, while allowing the alternating components of the biological signal and noise to "cancel each other out" during integration (the total contribution of the alternating positive and negative components within one period tends to zero).

[0101] Integrate Product_I[n] and Product_Q[n] for 64ms each, then divide by the integration time (or number of sampling points) and average to obtain the final result:

[0102] The in-phase integral result (V_I) is proportional to the real part of the electrode impedance (resistance R).

[0103] The result of the orthogonal integral (V_Q) is proportional to the imaginary part of the electrode impedance (capacitive reactance X). C ).

[0104] like Figure 2The diagram shows the equivalent circuit model of the contact impedance between the electrode and the skin. The resistance (R) corresponds to the physical contact resistance between the electrode and the skin, reflecting the tightness between the electrode and the skin surface (such as the stratum corneum). The tighter the contact (such as after the skin is cleaned and the electrode is firmly attached), the smaller the R value; the poorer the contact (such as dry skin and loose electrode), the larger the R value. It is the core parameter for judging the physical contact state of the electrode.

[0105] Capacitor element (X) C The equivalent capacitance at the electrode-skin interface originates from the "metal-electrolyte" interface formed between the electrode's metal surface and the electrolyte (sweat, conductive gel) on the skin's surface. The electrolyte acts as a dielectric, creating a capacitive structure between the electrode and skin. The capacitive reactance X is inversely proportional to the capacitance C, as shown in the formula: X... C =1 / (2πfC), where f is the excitation signal frequency, reflecting the stability of the interfacial electrochemical properties.

[0106] The EEG signal is uncorrelated with the reference signal (including in-phase and quadrature reference signals). After multiplication and integration averaging, its contribution approaches zero, thus being effectively separated. Similarly, the noise signal is also separated after the same processing because it is uncorrelated with the reference signal. The impedance signal is in phase and frequency with the reference signal and is completely synchronized. Finally, the in-phase integral and quadrature integral results proportional to the real and imaginary parts of the electrode impedance are obtained, respectively.

[0107] A4. Based on the in-phase integration result and the quadrature integration result, combined with the current amplitude of the excitation source, the electrode group impedance information is calculated. The electrode impedance information is the electrode complex impedance, which includes the real part and the imaginary part of the electrode complex impedance.

[0108] In one embodiment, the formula for calculating the impedance information of the electrode group is:

[0109] R = K * V_I / I;

[0110] X c =K*V_Q / I;

[0111] Where R represents the real part of the electrode impedance (unit: Ω), reflecting the physical contact resistance between the electrode and the skin (the closer the contact, the smaller R); K represents the proportional coefficient, determined by system hardware parameters (including excitation signal amplitude, PGA gain, reference signal amplitude, ADC resolution, etc.), and is determined after calibration using standard impedance calibration components (such as resistors and capacitors with known resistance values) to ensure calculation accuracy; V_I represents the in-phase integration result, X c The imaginary part of the electrode impedance (unit: Ω) reflects the capacitive reactance of the electrode-skin interface (the more stable the interface, the higher the capacitance). c (The closer to a fixed value), V_Q represents the result of the orthogonal integration, and I represents the current amplitude of the excitation source.

[0112] The ADS1299 chip's internal constant current source supports four configurable current amplitude modes: 6nA, 24nA, 6uA, and 24uA. Among these, 24nA represents a moderate amplitude selection that balances safety and signal-to-noise ratio. If the current amplitude is too small (e.g., 6nA), the impedance response signal amplitude corresponding to the electrode impedance is weak and easily drowned out by noise, increasing the difficulty of detection and identification. If the amplitude is too large (e.g., 24uA), it may not only pose potential safety risks to the human body but also enhance signal interference and degrade the quality of EEG signal acquisition. It should be noted that 24nA is not the only feasible configuration option. For example, 6uA may theoretically meet the basic requirements for safety and signal-to-noise ratio in some application scenarios, but its actual adaptability (including signal stability under different skin conditions and electrode types, and human tolerance for long-term monitoring) still needs further verification and confirmation through targeted experiments.

[0113] In this disclosure, based on the integral results and the known excitation current value, the real and imaginary parts of the electrode impedance are calculated using Ohm's law, and a moving average filter is used to improve measurement stability.

[0114] In one embodiment, regarding the recovery of the bioelectrical signal, the microcontroller unit is specifically configured to:

[0115] The mixed digital signal is subjected to digital notch filtering to remove the impedance response signal and noise signal, thereby obtaining the bioelectric signal.

[0116] This step is the purification of bioelectric signals (EEG, ECG, EMG, etc.). The microcontroller unit (MCU) uses a two-stage filtering strategy of "first suppressing specific interferences and then filtering out high-frequency noise in a broad spectrum" to accurately separate pure bioelectric signals from the mixed digital signals (V_mix[n] = V_bio[n] + V_imp[n] + V_noise[n]). This solves the core problem of excitation signal crosstalk, suppresses broad-spectrum high-frequency noise, and ensures that the bioelectric signals themselves are not distorted.

[0117] In one embodiment, the mixed digital signal can be subjected to digital notch filtering and low-pass filtering to filter out the impedance response signal and noise signal.

[0118] The impedance response signal (V_imp[n]) and its harmonics are generated by a 250Hz AC excitation signal on the electrode impedance. The frequency is fixed (250Hz) and the amplitude is large, which is the main source of interference.

[0119] High-frequency noise signals (V_noise[n]) include environmental electromagnetic interference (such as 50Hz power frequency harmonics, wireless signal interference), internal thermal noise of chips, etc., and their frequencies are mostly higher than the effective frequency band of bioelectric signals (such as EEG 0.5-100Hz, ECG 0.05-100Hz, EMG 10-500Hz).

[0120] The core objective of two-stage filtering is:

[0121] Digital notch filtering can accurately and narrowly suppress 250Hz excitation signals and their harmonics, and completely remove V_imp[n].

[0122] Low-pass filtering can broadly attenuate high-frequency noise above the effective frequency band of bioelectric signals and remove useless components in V_noise[n].

[0123] The final output retains only the pure bioelectric signal (V_bio_clean[n]) that meets the effective frequency band requirements and is free from distortion.

[0124] When performing digital notch filtering, a narrowband digital notch filter (also known as a "band-stop filter") can be used. The center frequency (fc) can be precisely set to 250Hz (completely consistent with the excitation signal frequency). At the same time, multi-stage notches or wide-coverage notches can be designed for harmonics (500Hz, 750Hz) to ensure that all excitation-related interference is suppressed. The filter bandwidth (BW) can be designed to be narrow (e.g., 10-20Hz). If the bandwidth is too wide, it will attenuate the high-frequency components of the bioelectric signal. If the bandwidth is too narrow, it will not be able to effectively cover the small frequency fluctuations of the excitation signal (e.g., ±1Hz deviation caused by chip clock drift). The attenuation can be set to ≥40dB. The higher the attenuation, the stronger the interference suppression effect. 40dB means that the amplitude of the 250Hz signal is attenuated to less than 1% of the original, which is negligible.

[0125] When performing low-pass filtering, a low-pass filter (either FIR or IIR type) is used. A low-pass filter "allows signals below the cutoff frequency to pass through while attenuating signals above the cutoff frequency".

[0126] The cutoff frequency (fc) is strictly matched to the upper limit of the effective frequency band of the bioelectric signal to ensure that "all useful signals pass through while all noise signals are blocked":

[0127] The cutoff frequency of the EEG signal was set to 100Hz (effective bandwidth 0.5-100Hz), preserving the complete components of delta waves (0.5-4Hz), theta waves (4-8Hz), alpha waves (8-13Hz), beta waves (13-30Hz), and gamma waves (30-100Hz).

[0128] The cutoff frequency of the ECG signal is set to 100Hz (effective frequency band 0.05-100Hz), preserving the morphological details of the P wave, QRS wave, and T wave without affecting the judgment of heart rate and rhythm.

[0129] The cutoff frequency of the electromyographic signal is set to 500Hz (effective frequency band 10-500Hz) to match the high-frequency electrical signals generated by muscle contraction.

[0130] Taking the ADS1299 for acquiring EEG signals as an example, the specific operating steps are as follows:

[0131] 1. System initialization configuration.

[0132] The ADS1299 is configured with an internal constant current source to inject a square wave current I_inject(t) with a frequency of f_LOFF into the target electrode.

[0133] Configure the ADS1299 to work in normal EEG acquisition mode, and set the sampling rate to 1k sampling rate;

[0134] Configure the ADS1299 internal constant current source LOFF register to set the internal constant current source to AC fDR / 4 working mode, and generate a square wave current I_inject(t) (24nA) with a frequency of f_LOFF (250Hz).

[0135] Select the electrode channel whose impedance needs to be detected using the BIAS_SENSP and BIAS_SENSN registers, and inject the excitation signal.

[0136] 2. Signal acquisition.

[0137] ADC synchronous acquisition of mixed digital signals: V_mix[n] = V_eeg[n] + V_imp[n] + V_noise[n];

[0138] Where V_eeg[n] is the EEG signal (0.5-100Hz), V_imp[n] is the impedance response signal, and V_noise[n] is the noise signal;

[0139] 3. Synchronous orthogonal demodulation is achieved.

[0140] a. Generation of digital reference signal:

[0141] In the MCU, the software generates a digital square wave signal that is completely synchronized with the frequency and phase of the square wave injected by the ADS1299;

[0142] Digital phase-locked loop (PLL) technology is used to precisely lock the phase of the excitation signal by analyzing the zero-crossing points of the mixed digital signal;

[0143] Based on the locked phase, the DDS algorithm is used to generate a synchronized in-phase reference signal Ref_I[n].

[0144] A quadrature reference signal Ref_Q[n] is generated by a 90° digital phase shift;

[0145] b. Signal demodulation processing:

[0146] The acquired mixed digital signal V_mix[n] is multiplied point by point with the digital reference signal Ref[n].

[0147] In-phase channel: Product_I[n] = V_mix[n] × Ref_I[n];

[0148] The correct path is: Product_Q[n] = V_mix[n] × Ref_Q[n];

[0149] Set a 64ms integration window (containing 16 complete cycles, one complete cycle is 4ms), integrate and average the product results to obtain the DC component V_dc;

[0150] For the impedance signal V_imp[n]: as described above, it generates a stable DC component V_dc, and V_dc∝Z*I_inject.

[0151] For the EEG signal V_EEG[n]: EEG is a random, low-frequency signal that is uncorrelated with Ref[n]. After being multiplied by Ref[n] (a square wave with alternating high and low levels), its positive or negative value is randomly multiplied by +1 or -1, and its contribution tends to zero during long-term integration or averaging.

[0152] For noise: the average contribution of all noise that is not at the same frequency or phase as Ref[n] also tends to zero.

[0153] c. Impedance calculation:

[0154] The V_dc obtained after integration / averaging is proportional to the electrode impedance.

[0155] By calibrating the system, the proportional coefficient K (which is related to the excitation current amplitude, PGA gain, reference signal amplitude, etc.) is determined, and then the impedance Z = K * V_dc.

[0156] Real resistance: R = K × V_I / I;

[0157] Virtual capacitive reactance: X c =K×V_Q / I;

[0158] Total impedance magnitude:

[0159] 4. Protection of EEG signals.

[0160] To obtain the EEG signal, the impedance measurement square wave needs to be removed from the original mixed digital signal V_mix[n]. Since the square wave frequency f_LOFF is precisely known, a high-performance digital notch filter can be designed to accurately filter out this frequency and its main harmonics, thereby outputting a pure V_EEG[n].

[0161] A digital notch filter is applied to the original mixed digital signal V_mix[n].

[0162] Precisely filter out the 250Hz excitation signal and its main harmonic components;

[0163] Outputs a clean, interference-free EEG signal V_eeg_clean[n].

[0164] Most existing electrode impedance detection schemes rely on additional, independent excitation sources and detection circuits (impedance detection chips or circuit modules). These external modules generate specific excitation signals (such as AC signals of a specific frequency), which are switched to the measuring electrodes through an analog switch matrix. The impedance is then calculated through another set of measurement circuits, which increases system complexity, cost, power consumption, and circuit size. This is not conducive to the portability and miniaturization of the device, which is contrary to the current development trend of wearable and portable medical devices. In this disclosure, the constant current source for lead detachment detection built into the integrated EEG acquisition chip (such as ADS1299) is reused, eliminating the need for an additional independent excitation source. By configuring the chip's internal LOFF (lead detachment control register), it can be set to fDR / 4 working mode to generate a 250Hz, 24nA low-frequency AC square wave excitation signal, completely eliminating the need for the external excitation circuit required by traditional solutions. At the same time, the core process of impedance detection (synchronous reference signal generation, multiplication operation, integral averaging, and complex impedance calculation) is implemented by the microcontroller unit (MCU) through software algorithms, eliminating the need to build an additional independent impedance detection chip or analog measurement circuit. Furthermore, electrode channel switching is completed through the chip's internal analog switch array (rather than an external analog switch matrix). The entire system consists only of the integrated EEG acquisition chip and the MCU, without any redundant external hardware modules. This design significantly simplifies the system hardware architecture, effectively reducing system complexity, design costs, power consumption, and overall size. It perfectly aligns with the miniaturization and lightweight development trend of wearable and portable medical devices, fundamentally solving the problem of existing solutions contradicting the development needs of portable devices.

[0165] Existing methods often employ time-division detection mechanisms. Because they require switching measurement channels, impedance measurement and EEG signal acquisition are typically performed in a time-division manner. When measuring electrode impedance, the EEG acquisition channel must be paused or switched, which interrupts or interferes with the continuity of the EEG signal during impedance measurement, making true real-time synchronous monitoring impossible. This solution utilizes a constant current source within an integrated EEG acquisition chip to continuously apply a specific frequency (250Hz) and fixed amplitude (24nA) AC excitation signal to the target electrode. Unlike existing technologies that use analog switch matrices to switch channels for time-division excitation, this eliminates the need for EEG acquisition interruptions caused by channel switching. Using the chip's built-in analog-to-digital converter (ADC), a mixed digital signal containing EEG signals, noise signals, and impedance response signals is simultaneously acquired. This achieves synchronous acquisition of two core signals on the same hardware channel and at the same time sequence. It eliminates the need to pause EEG acquisition to measure impedance separately and avoids temporal discontinuities caused by time-division acquisition, completely breaking the contradiction of "stopping EEG for impedance measurement." The microcontroller unit (MCU) processes the synchronously acquired mixed digital signals in parallel: on one hand, it extracts electrode complex impedance information from the mixed digital signals through synchronous quadrature demodulation technology (generating a synchronous reference signal → multiplication operation → integral averaging over an entire cycle); on the other hand, it synchronously filters out excitation signals and noise components through digital notch filtering to restore pure bioelectrical signals. The entire processing is completed in parallel in the digital domain without switching processing channels, ensuring both the real-time performance of impedance detection and complete non-interference with the continuity of EEG signals.

[0166] Existing methods may introduce additional interference through external excitation sources, especially external high-frequency excitation sources. If poorly designed, their excitation signals can easily crosstalk to the highly sensitive EEG acquisition front end, becoming a source of interference and degrading signal quality. In this disclosure, the lead detachment detection constant current source built into the integrated EEG acquisition chip (such as ADS1299) is reused as the excitation source. No external excitation module needs to be deployed. The excitation signal is generated directly inside the chip and applied to the electrodes through the chip's own analog switch array. It is integrated with the EEG acquisition front end in a homogeneous design, eliminating the signal crosstalk path between the external excitation source and the acquisition channel, thus fundamentally eliminating the possibility of additional interference introduced by the external excitation source.

[0167] Most existing technologies can only measure the amplitude of electrode impedance, failing to obtain phase information and thus not fully reflecting the contact state of the electrodes. This disclosure breaks through the limitation of traditional impedance detection focusing only on amplitude. It generates in-phase and quadrature reference signals that are completely synchronized with the frequency and phase of the excitation signal in the digital domain (step S4), and multiplies the mixed digital signal with the two types of reference signals respectively (step S5). Since the impedance response signal is strictly synchronized with the reference signal, after multiplication and whole-cycle integration and averaging, two stable DC components are separated. The in-phase integral result (V_I) is proportional to the real part of the electrode impedance (physical contact resistance), and the quadrature integral result (V_Q) is proportional to the imaginary part of the electrode impedance (interface capacitive reactance, which is directly related to phase information). Since EEG signals and noise are unrelated to the reference signal, their contribution tends to zero after integration and are effectively eliminated, ensuring the purity of the real and imaginary part information. Furthermore, the real part R corresponds to the degree of physical contact between the electrode and the skin (such as electrode loosening or insufficient skin cleaning leading to an increase in R), while the imaginary part X corresponds to the electrochemical stability of the electrode-skin interface (such as gel drying or electrolyte loss leading to an abnormality in X).

[0168] In summary, the solution disclosed herein can realize a low-cost, highly integrated, and truly real-time synchronized method for detecting bioelectrical signals and electrode impedance.

[0169] Figure 3 and Figure 4 This is another bioelectrical signal and electrode impedance acquisition system shown in the embodiments of this disclosure, such as... Figure 3 and Figure 4 As shown, it includes: an analog signal acquisition unit, a digital signal processing unit, and a host computer.

[0170] The analog signal acquisition unit 1 includes: an electrode array 11 and an analog front end 12;

[0171] Electrode array 11 contains a multi-channel electrode group consisting of “electrode 1, electrode 2…electrode n”, used to acquire human body signal sources.

[0172] The analog front-end 12 (example: ADS1299) generates a specific frequency, fixed amplitude AC excitation signal (corresponding to the 250Hz, 24nA square wave excitation in the above embodiment) through its internally integrated constant current source, and directly applies the excitation current to the target electrode (without requiring an external excitation source or analog switch matrix). Using its internal multi-channel ADC, the mixed analog signal transmitted from the electrode array is synchronously sampled and converted from analog to digital, transforming the mixed analog signal into a mixed digital signal. The synchronous sampling ensures that signals from all electrode channels are simultaneously acquired by the same ADC module, guaranteeing the "same source and same sequence" of the bioelectrical signal and the impedance response signal, laying the data foundation for subsequent synchronous detection.

[0173] exist Figure 3 In the process, the electrode array (11) collects "human body hybrid analog signals" and transmits them to the analog front end (12) through "physical channel connection"; the analog front end (12) generates an excitation current and applies it to the target electrode; at the same time, the hybrid analog signals are synchronously sampled and quantized through a multi-channel ADC to obtain "hybrid digital signals"; the analog front end (12) transmits the "hybrid digital signals" to the digital signal processing unit (2) through "SPI communication data stream"; after receiving the digital signals, the digital signal processing unit (2) executes algorithms such as synchronous quadrature demodulation (extracting electrode complex impedance) and digital notch filtering (recovering bioelectric signals).

[0174] Digital signal processing unit 2 (such as MCU / DSP) processes data via parallel dual-path processing:

[0175] Path A is used for electrode impedance extraction and includes 4 modules:

[0176] Reference signal generation module (211): Based on "hybrid digital signal", it generates two types of reference signals that are completely synchronized with the frequency and phase of the analog front-end excitation signal.

[0177] In-phase digital reference signal: in phase with the excitation signal;

[0178] Quadrature digital reference signal: obtained by digitally phase shifting the in-phase reference signal by 90°.

[0179] Synchronous quadrature demodulation module (212): Performs point-by-point multiplication operations on the "mixed digital signal" with the "in-phase reference signal" and the "quadrature reference signal" respectively, and then performs integral averaging on the product result as an integer multiple of the excitation signal period;

[0180] Impedance calculation module (213): Combining the known "excitation current amplitude (I)" and "system calibration proportional coefficient (K)", the electrode complex impedance is calculated using the formula:

[0181] Real part (R): (R = K * V_I / I) ((V_I) is the result of in-phase integration, reflecting the physical contact resistance);

[0182] Imaginary part (X): (X=K*V_Q / I)((V_Q) is the result of orthogonal integration, reflecting the interface capacitive reactance / phase characteristics).

[0183] Calibrate output impedance data (R,X) (214): Perform system calibration (eliminate hardware errors) on the calculated real part (R) and imaginary part (X) to output accurate electrode complex impedance data.

[0184] Pathway B is used for EEG signal recovery and includes three modules:

[0185] Digital notch filter (221): With the excitation signal frequency (e.g., 250Hz) as the center frequency, a narrow bandwidth filter is designed to accurately filter out the impedance response signal and its harmonic components in the mixed signal;

[0186] Low-pass filter (222): Filters out high-frequency noise (such as environmental electromagnetic interference) in the mixed signal and retains the effective frequency band of the EEG signal;

[0187] Output module (223): After two-stage filtering, a "pure EEG signal" is obtained.

[0188] Upper computer interaction module (214): Digital signal processing unit 2 transmits "real-time impedance value (R,X)" and "real-time EEG signal" to the upper computer through "USB / Ethernet" communication link to realize data display, storage and subsequent analysis, and adapt to the needs of clinical monitoring (such as sleep monitoring, epilepsy diagnosis).

[0189] The technical advantages of this disclosure are:

[0190] 1. This disclosure utilizes the lead detachment detection constant current source built into the EEG acquisition chip such as ADS1299, and sets it to a specific frequency AC square wave mode through register configuration, completely eliminating the need for external excitation circuit. In other words, this disclosure makes full use of the chip's internal resources, eliminating the need for external circuit, and significantly reducing system complexity, cost and size.

[0191] 2. Inspired by modulation and demodulation techniques in communications, this disclosure proposes synchronous quadrature demodulation technology for the first time and applies it to real-time impedance detection of EEG electrodes. It abandons the traditional filtering and separation techniques that cannot achieve synchronous detection of EEG acquisition and electrode impedance, and achieves true real-time synchronous detection to ensure the continuity of EEG signal acquisition.

[0192] 3. Provides complex impedance measurement capability to obtain more comprehensive information on electrode contact status;

[0193] 4. It has excellent anti-interference performance, ensuring measurement accuracy and reliability;

[0194] 5. Achieving a perfect fusion of EEG signal acquisition and impedance detection on the same hardware platform, enabling synchronous acquisition and separation of the two signals at the same time and on the same hardware channel. This solves the timing contradiction of the traditional solution, which is that "EEG cannot be acquired when impedance is measured, and impedance cannot be measured when EEG is acquired," and solves the technical problem of difficulty in balancing real-time performance and accuracy in traditional methods.

[0195] Figure 5 This is a flowchart illustrating a method for acquiring bioelectrical signals and electrode impedance according to an embodiment of this disclosure. This method is applied to a bioelectrical signal acquisition system as described in any of the foregoing embodiments, such as... Figure 4As shown, the method includes the following steps S101-S103:

[0196] S101, the integrated bioelectric signal acquisition chip uses an internally integrated excitation source to generate a specific frequency, fixed amplitude AC excitation signal; and continuously applies the AC excitation signal to one or more target electrodes.

[0197] S102, an integrated bioelectric signal acquisition chip acquires a mixed digital signal from the target electrode. The mixed digital signal includes the superposition of the impedance response signal generated by the bioelectric signal, noise signal and AC excitation signal on the impedance of the target electrode.

[0198] S103, the microcontroller unit extracts electrode impedance information from the mixed digital signal and recovers the bioelectric signal.

[0199] In one embodiment, the microcontroller unit extracts electrode impedance information from the mixed digital signal, including:

[0200] In the digital domain, an in-phase digital reference signal and a quadrature digital reference signal are generated that are synchronized with the frequency and phase of the AC excitation signal;

[0201] The mixed digital signal is multiplied by the in-phase reference signal and the quadrature reference signal;

[0202] The product results are subjected to a fixed-duration integral averaging process to obtain the in-phase integral result and the orthogonal integral result;

[0203] Based on the in-phase integration result and the orthogonal integration result, combined with the current amplitude of the excitation source, the electrode group impedance information is calculated. The electrode impedance information is the electrode complex impedance, which includes the real part and the imaginary part of the electrode complex impedance. The real part characterizes the physical contact tightness between the target electrode and the skin, and the imaginary part characterizes the electrochemical stability of the target electrode and skin interface.

[0204] In one embodiment, the microcontroller unit recovers the bioelectrical signal from the mixed digital signal, including:

[0205] The mixed digital signal is subjected to digital notch filtering to remove the impedance response signal and noise signal, thereby obtaining the bioelectric signal.

[0206] In one embodiment, the formula for calculating the impedance information of the electrode group is:

[0207] R = K * V_I / I;

[0208] X c =K*V_Q / I;

[0209] Where R represents the real part, K ​​represents the proportionality coefficient, V_I represents the in-phase integral result, V_Q represents the orthogonal integral result, and X c Let I represent the imaginary part, and let I represent the current amplitude of the excitation source.

[0210] In one embodiment, generating an in-phase digital reference signal synchronized with the frequency and phase of the AC excitation signal includes:

[0211] Digital phase-locked loop technology is used to determine the phase of the AC excitation signal by analyzing the zero-crossing points of the mixed digital signal;

[0212] Based on phase locking, the DDS algorithm is used to generate in-phase reference signals.

[0213] In one embodiment, generating an orthogonal digital reference signal synchronized with the frequency and phase of the AC excitation signal includes:

[0214] The in-phase reference signal is digitally phase-shifted by 90° to generate the quadrature digital reference signal.

[0215] In one embodiment, the duration of the integral averaging process is an integer multiple of the period of the AC excitation signal.

[0216] In one embodiment, the specific frequency is far from the effective frequency of the bioelectric signal.

[0217] In one embodiment, the AC excitation signal of a specific frequency and fixed amplitude generated by the internally integrated excitation source includes:

[0218] Configure the lead shedding control register of the integrated bioelectric signal acquisition chip, set the current amplitude of the internal constant current source to 24nA, and set it to fDR / 4 working mode to generate an AC excitation signal of a specific frequency and fixed amplitude.

[0219] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0220] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

Claims

1. A bioelectrical signal and electrode impedance acquisition system, characterized in that, Includes an integrated bioelectric signal acquisition chip and a microcontroller unit; The integrated bioelectric signal acquisition chip is used to generate an AC excitation signal of a specific frequency and fixed amplitude through an internally integrated excitation source; and to continuously apply the AC excitation signal to one or more target electrodes through an internal analog switch array. The integrated bioelectric signal acquisition chip is used to acquire a mixed digital signal from the target electrode. The mixed digital signal includes a superposition of a bioelectric signal, a noise signal, and an impedance response signal generated on the impedance of the target electrode by the AC excitation signal. The microcontroller unit is used to extract electrode impedance information from the mixed digital signal and recover the bioelectric signal.

2. The system according to claim 1, characterized in that, In extracting electrode impedance information from the mixed digital signal, the microcontroller unit is specifically configured to: In the digital domain, an in-phase digital reference signal and a quadrature digital reference signal are generated that are synchronized with the frequency and phase of the AC excitation signal; The mixed digital signal is multiplied by the in-phase reference signal and the quadrature reference signal; The product results are subjected to a fixed-duration integral averaging process to obtain the in-phase integral result and the orthogonal integral result; Based on the in-phase integration result and the orthogonal integration result, combined with the current amplitude of the excitation source, the electrode group impedance information is calculated. The electrode impedance information is the electrode complex impedance, which includes the real part and the imaginary part of the electrode complex impedance. The real part characterizes the physical contact tightness between the target electrode and the skin, and the imaginary part characterizes the electrochemical stability of the target electrode and skin interface.

3. The system according to claim 2, characterized in that, In the aspect of recovering bioelectrical signals from the mixed digital signals, the microcontroller unit is specifically configured to: The mixed digital signal is subjected to digital notch filtering to remove the impedance response signal and noise signal, thereby obtaining the bioelectric signal.

4. The system according to claim 2, characterized in that, The formula for calculating the impedance information of the electrode group is: R = K * V_I / I; X c =K*V_Q / I; Where R represents the real part, K ​​represents the proportionality coefficient, V_I represents the in-phase integral result, V_Q represents the orthogonal integral result, and X c Let I represent the imaginary part, and let I represent the current amplitude of the excitation source.

5. The system according to claim 2, characterized in that, In the aspect of generating an in-phase digital reference signal synchronized with the frequency and phase of the AC excitation signal, the microcontroller unit is specifically configured to: Digital phase-locked loop technology is used to determine the phase of the AC excitation signal by analyzing the zero-crossing points of the mixed digital signal; Based on phase locking, the DDS algorithm is used to generate in-phase reference signals.

6. The system according to claim 5, characterized in that, In the aspect of generating an orthogonal digital reference signal synchronized with the frequency and phase of the AC excitation signal, the microcontroller unit is specifically configured to: The in-phase reference signal is digitally phase-shifted by 90° to generate the quadrature digital reference signal.

7. The system according to claim 2, characterized in that, The duration of the integral averaging process is an integer multiple of the period of the AC excitation signal.

8. The system according to claim 1, characterized in that, The specific frequency is far from the effective frequency of bioelectrical signals.

9. The system according to claim 1, characterized in that, Regarding the specific frequency and fixed amplitude AC excitation signal generated by the internally integrated excitation source, the integrated bioelectric signal acquisition chip is specifically used for: Configure the lead shedding control register of the integrated bioelectric signal acquisition chip, set the current amplitude of the internal constant current source to 24nA, and set it to fDR / 4 working mode to generate an AC excitation signal of a specific frequency and fixed amplitude.

10. A method for acquiring bioelectrical signals and electrode impedance, characterized in that, The method is applied to the bioelectric signal acquisition system as described in any one of claims 1-9, and the method includes: The integrated bioelectric signal acquisition chip continuously applies an AC excitation signal of a specific frequency and fixed amplitude generated by an internally integrated excitation source to one or more target electrodes. The integrated bioelectric signal acquisition chip acquires a mixed digital signal from the target electrode. The mixed digital signal includes a superposition of a bioelectric signal, a noise signal, and an impedance response signal generated by the AC excitation signal on the impedance of the target electrode. The microcontroller unit extracts electrode impedance information from the mixed digital signal and recovers the bioelectric signal.

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