A method for quickly replacing EEG electrodes

Abstract

The present invention discloses a method for quickly replacing EEG electrodes, which relates to the technical field of neuroelectrophysiological examination and polysomnography monitoring, and comprises the following steps: dividing an electrode wire into two parts, connecting the connection points thereof with a wire hub device, and interconnecting them in the form of a wire harness, with one end connected to the patient corresponding to one end connected to the amplifier; when removing the electrode, the electrode wire harness at one end of the amplifier remains stationary, and the wire hub device at the connection point is used for plugging and unplugging; in the present invention, the electrode wire is divided into two parts and connected with a wire hub device, so that the electrode replacement avoids the amplifier jack, avoids loss and contact problems, and ensures stable and reliable signal acquisition; the electrode wire bundle design is convenient for medical staff to operate and patients to wear, improves disassembly efficiency, reduces data errors, and can prevent cross infection, thereby improving electrode performance in many aspects, meeting the clinical needs of high-precision and long-term stable monitoring of EEG signals, and promoting technological development.

Description

Technical Field

[0001] The present invention relates to the technical field of neuroelectrophysiological examination and polysomnography, and in particular to a method for quickly replacing EEG electrodes. Background Art

[0002] In the fields of neuroelectrophysiology (EEG) and polysomnography in brain science and clinical neurology, electrodes are key components whose performance and ease of use directly impact the quality and efficiency of testing. Currently, most commonly used EEG and polysomnography electrodes are in the form of single electrode wires.

[0003] However, this traditional electrode wire structure requires one side to be inserted into the electrode amplifier jack, while the other side is attached to the patient's skin. In actual applications, when a single electrode is used, it must be unplugged from the amplifier jack so that the electrode can be cleaned or replaced with a new one. However, as the number of times the electrode is used increases, frequently plugging and unplugging the electrode wire from the amplifier jack will inevitably cause serious wear or loosening of the battery cell in the amplifier that contacts the electrode wire. Once the battery cell is worn or loose, it will be difficult to ensure good contact with the subsequently inserted electrode wire, which will cause a series of problems that seriously affect the test results, such as poor contact of the electrode wire, resulting in obstruction or interruption of signal transmission; increased impedance, causing distortion and attenuation of the collected EEG signal, reducing the quality and clarity of the signal; unstable electrodes, which easily shift the electrode position during the test process, affecting the accuracy and stability of signal acquisition.

[0004] These issues have seriously hindered the effective application and development of EEG monitoring technology. Therefore, a method for quickly replacing EEG electrodes is provided to overcome these issues. This method improves the stability, reliability, and convenience of EEG electrode use, meeting the clinical diagnostic requirements for high-precision, long-term, stable monitoring of EEG signals. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for quickly replacing EEG electrodes to solve the problems raised in the above background technology.

[0006] To solve the above technical problems, the present invention provides a method for quickly replacing EEG electrodes, comprising the following steps:

[0007] The electrode wire is divided into two parts, and the connection is connected by a wire hub device and connected to each other in the form of a wire harness. The end connected to the patient corresponds one to one with the end connected to the amplifier. When removing the electrode, the electrode wire harness at one end of the amplifier remains stationary, and the wire hub device at the connection is used for plugging and unplugging.

[0008] Furthermore, the hub device adopts a DB-15 connector.

[0009] Furthermore, the wiring hub adopts an M12 circular connector.

[0010] Furthermore, the cable hub adopts a LEMO push-pull self-locking circular connector.

[0011] Furthermore, the line hub device uses an aviation plug, which includes but is not limited to GX16.

[0012] Furthermore, the wiring harnesses on both sides correspond one to one through the plugs.

[0013] Furthermore, the electrode wires are bundled and distinguished by color.

[0014] Furthermore, the electrodes on the electrode harness are disc-shaped electrodes.

[0015] Furthermore, during the electrode replacement process, EEG signals are collected at a sampling frequency of 1000 Hz per second, and the phase information of the alpha wave in the EEG signal is extracted using Fourier transform. When the alpha wave phase is in the range of 0° to 90°, the plug-in and unplug operation of the hub device is triggered, and a slow start and slow stop mechanism is adopted. At the same time, after the electrode replacement is completed, a high-sensitivity electromagnetic field sensor covering low frequency to high frequency is arranged near the electrode to monitor the electromagnetic field intensity and frequency at a frequency of 10 times per second. The support vector machine algorithm is used to analyze the electromagnetic field data within 1 minute to establish a model of intensity and frequency changes over time to predict the electromagnetic field change trend in the next 5 minutes. For patients with epilepsy, when electromagnetic field interference of a specific frequency and intensity is predicted, the electrode sensitivity and low-pass filter cutoff frequency are adjusted according to the pre-built database to suppress the interference signal.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] 1. The present invention completely changes the traditional mode of directly inserting a single electrode cable into the amplifier jack by dividing the electrode cable into two parts and connecting them with a hub device. This allows the electrode replacement and plugging-in to be separated from the amplifier jack, effectively avoiding unnecessary losses of the amplifier caused by repeated plugging and unplugging, such as battery wear or loosening, and thus eliminating the problems of poor contact, increased impedance, and unstable electrodes of subsequently inserted electrode cables. This effectively ensures the stability and reliability of EEG signal acquisition and provides a solid data foundation for clinical diagnosis.

[0018] The design of bundled electrode wires greatly facilitates operation and management by medical staff, while making patient-side electrodes easier to remove, significantly increasing operational efficiency. Furthermore, bundled electrode wires are more comfortable, aesthetically pleasing, and less likely to fall off, improving patient tolerance and compliance during long-term monitoring, ensuring the continuity of the monitoring process, and reducing data errors caused by patient discomfort or electrode displacement. This provides more comprehensive and reliable EEG signal data for clinical diagnosis, helping doctors more accurately determine a patient's condition and develop more effective treatment plans. Furthermore, this design can be used with disposable electrodes, effectively avoiding cross-infection and ensuring the health and safety of patients.

[0019] 2. During the electrode replacement process, the present invention uses advanced technical means to collect EEG signals at a sampling frequency of 1000 Hz per second, and uses Fourier transform to extract the phase information of α waves in the EEG signals. When the α wave phase is in the range of 0° to 90°, the plugging and unplugging operation of the hub device is triggered, and a slow start and slow stop mechanism is adopted to achieve intelligent coordination between the plugging and unplugging operation and the EEG signal state, minimize the interference of the plugging and unplugging operation on the EEG signal, further improve the continuity and stability of EEG signal acquisition, enable doctors to obtain more complete and accurate EEG signals, help to deeply analyze the patient's EEG activity, thereby improving the accuracy and reliability of diagnosis, reducing the risk of misdiagnosis and missed diagnosis due to signal interference, and providing strong support for the patient's precise treatment.

[0020] Based on the complex electromagnetic environment of hospitals, the present invention arranges high-sensitivity electromagnetic field sensors near the electrodes, monitors the electromagnetic field strength and frequency at a frequency of 10 times per second, and uses a hybrid algorithm combining advanced support vector machines and long short-term memory networks to analyze the electromagnetic field data and establish a model to predict future electromagnetic field change trends. According to the EEG signal characteristics of different patients, such as those with epilepsy or unexplained dizziness and confusion, when electromagnetic field interference is predicted, the electrode sensitivity and low-pass filter cutoff frequency can be quickly adjusted according to the pre-built database to suppress the interference signal. This method of predicting and adjusting electrode performance based on environmental electromagnetic field changes fully considers the impact of electromagnetic fields generated by various electronic devices on electrode performance, effectively reduces the interference of environmental electromagnetic fields on electrode performance, and ensures the accurate acquisition of patient characteristic EEG signals in complex electromagnetic environments. It provides more reliable and accurate technical support for clinical diagnosis, improves the accuracy and reliability of clinical diagnosis, reduces the risk of diagnostic errors and treatment delays caused by electromagnetic field interference, and provides a stronger technical guarantee for the diagnosis and treatment of neurological diseases. It has important clinical application value and innovative significance, and is expected to promote the development and progress of the entire field of EEG monitoring technology, bringing new breakthroughs and hope to the diagnosis and treatment of neurological diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic diagram of the traditional EEG electrode replacement method;

[0022] Figure 2 This is a schematic diagram of a method for quickly replacing EEG electrodes according to the present invention. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0024] See also Figure 1-Figure 2 , the present invention provides a technical solution:

[0025] See Figure 1-Figure 2 As shown, an embodiment of a method for quickly replacing EEG electrodes:

[0026] Scene setting:

[0027] In the neurology department's EEG monitoring room at a comprehensive hospital equipped with advanced medical facilities and a professional technical team, a 45-year-old male patient is undergoing long-term EEG monitoring. The patient suffers from intermittent dizziness and confusion of unknown cause. The medical team hopes that the high-precision brain electrical activity data obtained from this monitoring will assist in the accurate diagnosis of underlying neurological conditions. Given that the monitoring period is expected to last up to 24 hours, the stability of the electrode system and signal quality are crucial for accurate diagnosis. Regular electrode replacement is required to maintain optimal monitoring performance and patient comfort.

[0028] 1. Initial setup of electrode cable connection and hub

[0029] step:

[0030] Following the established and standardized international 10-20 system for electrode arrangement in clinical EEG monitoring, and incorporating the patient's specific EEG signal monitoring needs for the head, the custom-made gold-plated pin connector of the electrode bundle ① was carefully connected to the corresponding port on the amplifier. This pin connector is constructed from a highly conductive, low-impedance, and corrosion-resistant metal material. A precise crimping process ensures a tight, secure, and reliable connection, laying a solid foundation for the subsequent stable transmission of EEG signals and effectively reducing the risk of attenuation and distortion during signal transmission.

[0031] Based on a comprehensive evaluation of various hub connector types in terms of signal integrity, anti-interference performance, plug-in durability, and adaptability, a DB-15 connector with 15 independent pins was ultimately selected as the hub. This connector features an optimized shielding structure that effectively resists external electromagnetic interference and ensures the purity of signal transmission. Subsequently, electrode wires ② and ③ are precisely connected through this DB-15 hub. At the same time, the pre-designed line layout and connection specifications are strictly followed to ensure a one-to-one correspondence between the plugs and sockets on both sides of the wiring harness, eliminating the risk of misconnection. This creates a complete, efficient, and stable electrode wire connection system, providing a strong guarantee for the accurate acquisition and transmission of subsequent EEG signals.

[0032] Disc-shaped silver-silver chloride electrodes that meet medical-grade biocompatibility standards and possess excellent conductivity are precisely affixed to the corresponding location on the patient's scalp according to the standard EEG electrode placement guidelines issued by the American Association of Electroencephalography (AEEG). During the affixing process, a professionally formulated conductive paste with optimal viscosity and conductivity is used to effectively fill the tiny gaps between the electrode and the skin, reducing contact impedance and minimizing signal loss due to poor contact. This ensures that the collected EEG signals have high fidelity and a high signal-to-noise ratio, providing reliable data support for clinical diagnosis.

[0033] The international 10-20 system electrode arrangement rule is a standard method widely recognized in the field of EEG monitoring and verified by long-term clinical practice. It can comprehensively and systematically cover all key areas of the brain, ensuring the representativeness and integrity of the collected EEG signals, and providing a comprehensive data foundation for accurate diagnosis. The selection of high-conductivity, low-impedance, and corrosion-resistant pin connector materials and precision crimping processes are based on a deep understanding of the principles of electrical signal transmission and the properties of metal materials. High-quality materials and processes can reduce signal reflection, scattering, and attenuation at the connection site, ensuring efficient signal transmission, thereby ensuring that the collected EEG signals truly reflect the patient's brain electrical activity.

[0034] The DB-15 connector has demonstrated excellent performance in similar medical monitoring equipment applications. Its multi-pin design accommodates complex electrode cable connections, while its internal shielding effectively blocks external electromagnetic interference, ensuring stable and reliable signal transmission. Strict one-to-one connection is essential for proper functioning of the electrode cable system; any misconnection can result in signal acquisition errors or loss, compromising the accuracy of diagnostic results.

[0035] The use of biocompatible disc-shaped silver-silver chloride electrodes and specialized conductive paste ensures a stable, low-impedance electrical contact interface between the electrode and the skin. Silver-silver chloride electrodes offer excellent electrochemical stability and low polarization potential, reducing electrochemical noise between the electrode and skin and improving signal quality. The use of conductive paste, based on the electrical properties of the skin and the working principles of the electrodes, ensures smooth transmission of electrical signals from the cerebral cortex to the electrode by filling gaps and reducing contact impedance, thereby improving signal fidelity and signal-to-noise ratio, providing a more reliable basis for clinical diagnosis.

[0036] This electrode cable connection architecture abandons the traditional model of directly plugging a single electrode cable into the amplifier jack, fundamentally avoiding the problem of wear and tear caused by repeated plugging and unplugging of the amplifier jack. By dividing the electrode cable into two parts and connecting them with a cable hub, it effectively solves the key problem in existing technologies that causes wear or loosening of the amplifier core due to repeated plugging and unplugging, which in turn causes poor electrode cable contact, increased impedance, and decreased electrode stability, which seriously affects the quality and stability of EEG signal acquisition. It provides reliable hardware support for long-term, high-precision EEG monitoring, ensuring that the collected EEG signals can accurately reflect the patient's brain electrophysiological state, improving the accuracy and reliability of diagnosis.

[0037] The bundled electrode wire design not only conforms to ergonomic principles, facilitating convenient and efficient operation and management by medical staff, but also provides greater comfort and aesthetics for patients while wearing it, effectively reducing the risk of accidental electrode dislodgment due to patient activity. This significantly improves patient tolerance and compliance during long-term monitoring, reduces monitoring interruptions and data errors caused by patient discomfort or electrode displacement, ensures the continuity of the monitoring process and the accuracy of the data, and provides more comprehensive and reliable EEG signal data for clinical diagnosis, helping doctors to more accurately judge the patient's condition and develop more effective treatment plans.

[0038] 2. EEG signal phase control plugging and unplugging operation during electrode replacement

[0039] step:

[0040] Before initiating the electrode replacement procedure, a professional EEG signal acquisition device equipped with advanced micro-electromechanical system (MEMS) sensor technology and high-precision signal amplification and conditioning circuits is activated. This device is capable of real-time, accurate, and continuous acquisition of the patient's EEG signals at a high sampling rate of 1000 Hz per second. This high-speed, intensive sampling process ensures that subtle changes and characteristic information of the EEG signals are fully captured, including the amplitude, phase, and time series changes of different frequency components. Simultaneously, digital signal processing technology based on the Fast Fourier Transform (FFT) algorithm is used to efficiently and accurately convert the collected time-domain EEG signals into frequency-domain signals, thereby precisely extracting the phase information of the alpha waves in the EEG signals. As a typical component of EEG activity in a quiet, relaxed, and awake state, the accurate acquisition of alpha wave phase information is of great significance for determining the functional state of the brain, especially during the electrode replacement process, where it can provide a key decision-making basis for intelligent plug-in and plug-out control.

[0041] With the help of high-performance signal monitoring and analysis algorithms and field programmable gate array (FPGA) chips with powerful data processing capabilities, the alpha wave phase is monitored continuously and stably. When the phase of the alpha wave is accurately monitored to enter the range of 0° to 90°, the system immediately and automatically triggers the plug-in and unplug operation procedure of the hub device. During the plug-in and unplugging process, the control system sends precise, continuous and dynamically adjusted control signals to the hub device by precisely controlling the speed, torque and displacement of the motor according to the preset slow start and slow stop strategies. A closed-loop control algorithm is used to monitor the force feedback and displacement information during the plug-in and unplugging process in real time to ensure that the hub device plugs and unplugs the electrode wires smoothly, slowly and accurately, avoid instantaneous mechanical shocks that cause additional interference and noise to the EEG signal, ensure the stability and continuity of the EEG signal during the electrode replacement process, and guarantee the quality and reliability of the monitoring data.

[0042] The high sampling frequency of 1000 Hz per second was determined based on in-depth research into the complex and changeable characteristics of EEG signals and the signal accuracy requirements for clinical diagnosis. EEG signals are weak, complex, and have a wide frequency range. The high sampling frequency ensures that the signal is discretized sufficiently finely in the time domain, thereby capturing rapid changes and detailed information of the signal, avoiding signal distortion and information loss caused by insufficient sampling, and providing a rich and accurate data foundation for subsequent signal analysis and processing. The FFT algorithm is a classic and efficient signal processing method that can quickly and accurately convert time domain signals into frequency domain signals, facilitating in-depth analysis and processing of signals with different frequency components. The extraction of alpha wave phase information is of great reference value for judging the physiological state and functional activities of the brain. Therefore, accurately extracting the alpha wave phase is a key step in realizing intelligent plug-in and plug-out control, which can ensure that electrode replacement operations are performed at a time when interference with EEG signals is minimized.

[0043] The selection of a plugging and unplugging operation within the 0° to 90° alpha wave phase range is based on extensive clinical experimental research and data analysis. Within this phase range, brain neural activity is relatively stable, and the energy distribution and variation of alpha waves are relatively smooth. Plugging and unplugging at this time minimizes interference with EEG signals, minimizing signal fluctuations and noise caused by plugging and unplugging, ensuring EEG signal continuity and stability. The application of a slow-start and slow-stop mechanism is based on the principles of mechanical dynamics and signal interference control theory. By slowly increasing and decreasing the plugging and unplugging force, the adverse effects of instantaneous impact on the electrodes and EEG signals are avoided, ensuring EEG signal quality and stability during operation. The use of a closed-loop control algorithm further improves the precision and reliability of the plugging and unplugging operation, adjusting the control signal in real time based on force feedback and displacement information to ensure a smooth and safe plugging and unplugging process.

[0044] Through high-precision signal acquisition and advanced phase monitoring technology, the hub device can be plugged in and out during specific phases when the EEG signal is relatively stable, achieving intelligent coordination between the plugging and unplugging operations and the EEG signal status. This precise control method minimizes the interference of plugging and unplugging operations on EEG signals, ensures the continuity and stability of EEG signal acquisition, and improves the reliability and data quality of the entire EEG monitoring system. Doctors can obtain more complete and accurate EEG signal data, which helps to analyze the patient's EEG activity more deeply and accurately, providing a more reliable and detailed basis for disease diagnosis, improving the accuracy and reliability of diagnosis, reducing the risk of misdiagnosis and missed diagnosis due to signal interference, and providing strong support for the precise treatment of patients.

[0045] 3. Electrode performance adjustment based on changes in environmental electromagnetic fields

[0046] step:

[0047] Multiple, precisely calibrated, high-sensitivity, three-axis fluxgate electromagnetic field sensors are strategically positioned near the electrodes. Utilizing advanced magnetoresistive effect principles and high-precision signal conditioning circuitry, these sensors accurately measure magnetic field strength and frequency components ranging from low frequencies (such as 50Hz mains interference, a common source of fundamental frequency interference in hospital environments, primarily from lighting equipment and medical instruments) to high frequencies (such as radio frequency interference in the wireless communication band, including interference generated by wireless network equipment and mobile communication devices within hospitals). The sensors rapidly monitor the intensity and frequency changes of the ambient electromagnetic field in real time, at a rate of 10 times per second, and accurately transmit the collected three-dimensional magnetic field data to the data processing unit via high-speed, interference-resistant data transmission lines.

[0048] The data processing unit utilizes a powerful graphics processing unit (GPU) accelerated computing platform and a deep learning-based algorithm architecture to collect electromagnetic field data within one minute. This data is then analyzed and modeled using a hybrid algorithm combining a support vector machine (SVM) and a long short-term memory (LSTM) network. This hybrid algorithm leverages the advantages of SVM in processing small samples and nonlinear data, as well as the expertise of LSTM in time series prediction. By learning and training on historical electromagnetic field data, it establishes a precise model of how electromagnetic field intensity and frequency change over time. Based on the patterns and trends of historical data, this model can accurately predict the changing trends of the electromagnetic field within the next five minutes, providing a reliable basis for adjusting electrode performance in advance.

[0049] For this patient suffering from unexplained dizziness and confusion, during the monitoring process, when it was predicted that the environmental electromagnetic field would experience an increase in intensity and a frequency of 50Hz within the next 5 minutes, the electrode parameter adjustment program was quickly initiated based on a personalized database of the impact of electromagnetic fields on the patient's EEG signals, which had been established through a large amount of experimental and clinical data. By precisely controlling the electrode circuit parameters, the electrode sensitivity was reduced by 20%, reducing the electrode's response to interference signals. At the same time, the cutoff frequency of the low-pass filter was reduced from 50Hz to 40Hz, effectively preventing the 50Hz interference signal from entering the subsequent signal acquisition and processing links. This ensured that the patient's EEG signal characteristics could be clearly collected, especially potential abnormal EEG signals related to dizziness and confusion, providing strong support for doctors to accurately diagnose the condition.

[0050] The complex electromagnetic environment of a hospital is plagued by electromagnetic interference sources of varying frequencies and intensities. These sources can severely impact the performance of EEG electrodes, contaminating the collected EEG signals with noise and compromising diagnostic accuracy. Therefore, deploying highly sensitive three-axis fluxgate electromagnetic field sensors covering a wide frequency range is essential to comprehensively and accurately monitor changes in the ambient electromagnetic field. A sampling rate of 10 times per second allows for timely capture of rapid changes in the electromagnetic field, providing timely and accurate data support for subsequent real-time adjustments.

[0051] The hybrid algorithm combining SVM and LSTM has significant advantages in modeling complex electromagnetic field data. It can mine the inherent laws and trends of electromagnetic field changes from large amounts of historical data, thereby accurately predicting future electromagnetic field changes. This machine learning-based approach can adapt to different hospital environments and the complexity of electromagnetic field changes, improve the accuracy and reliability of predictions, and provide a scientific basis for the early adjustment of electrode performance.

[0052] Adjusting electrode parameters based on a pre-established database is based on in-depth research into the interaction between electromagnetic fields and EEG signals and extensive clinical validation. Different patients have varying sensitivity and response characteristics to EMF interference. By conducting long-term monitoring and analysis of specific patients' EEG signals and EMF interference data, and establishing a personalized database, we can quickly and accurately adjust electrode parameters when encountering EMF interference, minimizing the impact of interference on EEG signals and ensuring that the collected EEG signals truly reflect the patient's brain activity, thereby improving diagnostic accuracy and reliability.

[0053] In a complex environment like a hospital, which is filled with various electronic devices, electromagnetic field interference is a significant factor affecting EEG electrode performance and signal quality. By real-time monitoring and precise modeling to predict electromagnetic field changes, and by making targeted, intelligent adjustments to electrode parameters based on the patient's EEG signal characteristics, the impact of environmental electromagnetic fields on electrode performance can be effectively reduced, ensuring accurate acquisition of the patient's characteristic EEG signals in complex electromagnetic environments. Doctors can obtain purer and more accurate EEG signals, which helps to more accurately diagnose the patient's condition, provide strong support for the development of effective treatment plans, improve the accuracy and reliability of clinical diagnosis, reduce the risk of diagnostic errors and treatment delays due to electromagnetic field interference, and provide more reliable technical support for the diagnosis and treatment of neurological diseases.

[0054] Summarize:

[0055] Through the above embodiments, the rapid EEG electrode replacement method of the present invention has demonstrated outstanding advantages and significant innovative value in actual clinical applications. First, the unique electrode wire connection and wiring device design fundamentally avoids the wear and tear of the amplifier jack caused by repeated plugging and unplugging, effectively solving the key problems that have long plagued the field of EEG monitoring in the prior art, such as poor electrode wire contact, increased impedance, and electrode instability. It ensures the stability and reliability of EEG signal acquisition and provides solid basic data support for clinical diagnosis. Secondly, the use of EEG signal phase information for intelligent plug-in and unplug operation control during the electrode replacement process further reduces interference with EEG signals, improves the quality and continuity of monitoring data, enables doctors to obtain more complete and accurate EEG signals, facilitates in-depth analysis of patients' EEG activity, and improves the accuracy and reliability of diagnosis. Finally, the electrode performance prediction and adjustment method based on environmental electromagnetic field changes fully considers the impact of the hospital's complex electromagnetic environment on electrode performance. Through real-time monitoring, precise modeling, and intelligent adjustment, it effectively responds to various electromagnetic field interferences and ensures that the patient's EEG signal characteristics can be accurately collected under different electromagnetic field conditions. It provides more reliable and accurate technical support for clinical diagnosis and has important clinical application value and innovative significance.

[0056] In general, the technical means of the present invention have brought about an all-round improvement in the use and maintenance of EEG electrodes. It not only significantly improves the quality and stability of EEG signal acquisition, but also greatly enhances the adaptability and anti-interference ability of the electrode system to complex environments, ultimately greatly improving the effectiveness and accuracy of clinical diagnosis. This is a major innovation and improvement in existing EEG electrode technology, which can better meet the strict requirements of neuroelectrophysiological examinations and polysomnography in modern clinical neurology, providing a more powerful and reliable guarantee for the diagnosis and treatment of patients. It is expected to promote the development and progress of the entire field of EEG monitoring technology and bring new breakthroughs and hope to the diagnosis and treatment of neurological diseases.

Claims

1. A method for quickly replacing EEG electrodes, characterized in that: The following steps are involved: The electrode wire is divided into two parts, and the connection is connected with a wire hub device, and connected to each other in the form of a wire harness. The end connected to the patient corresponds to the end connected to the amplifier. When removing the electrode, the electrode harness at the amplifier end is not moved, and the wire hub device at the connection is used for plugging and unplugging. During the electrode replacement process, EEG signals are collected at a sampling frequency of 1000 Hz per second, and the phase information of the alpha wave in the EEG signal is extracted using Fourier transform. When the alpha wave phase is in the range of 0° to 90°, the plugging and unplugging operation of the hub device is triggered, and a slow start and slow stop mechanism is adopted. At the same time, after the electrode replacement is completed, high-sensitivity electromagnetic field sensors covering low to high frequencies are arranged near the electrodes to monitor the electromagnetic field intensity and frequency at a frequency of 10 times per second. The support vector machine algorithm is used to analyze the electromagnetic field data within 1 minute to establish a model of intensity and frequency changes over time to predict the electromagnetic field change trend in the next 5 minutes. For patients with epilepsy, when electromagnetic field interference of a specific frequency and intensity is predicted, the electrode sensitivity and low-pass filter cutoff frequency are adjusted according to the pre-built database to suppress the interference signal.

2. The method for quickly replacing EEG electrodes according to claim 1, wherein: The hub uses a DB-15 connector.

3. The method for quickly replacing EEG electrodes according to claim 1, wherein: The wiring hub uses an M12 circular connector.

4. The method for quickly replacing EEG electrodes according to claim 1, wherein: The cable hub uses LEMO push-pull self-locking circular connectors.

5. The method for quickly replacing EEG electrodes according to claim 1, wherein: The hub device uses aviation plugs, including GX16.

6. The method for quickly replacing EEG electrodes according to claim 1, wherein: The wiring harnesses on both sides correspond one to one through the plugs.

7. The method for quickly replacing EEG electrodes according to claim 1, wherein: The electrode wires are bundled and distinguished by color.

8. The method for quickly replacing EEG electrodes according to claim 1, wherein: The electrodes on the electrode harness are disc-shaped electrodes.

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