Method for quickly replacing electroencephalogram electrode

Abstract

The invention discloses a method for quickly replacing an electroencephalogram electrode, which relates to the technical field of nerve electrophysiological examination and polysleep monitoring, and comprises the following steps of: dividing an electrode wire into two parts, connecting the two parts through a wire concentration device, mutually connecting the two parts in a wire harness form, and enabling one end connected with a patient to be in one-to-one correspondence with one end connected with an amplifier, when the electrode is disassembled, the electrode wire harness at one end of the amplifier is fixed, and the wire concentration device at the joint is used for plugging; in the invention, the electrode wire is divided into two parts and is connected by the wire concentration device, so that the electrode replacement avoids an amplifier jack, the problems of loss and contact are avoided, and stable and reliable signal acquisition is ensured; due to the electrode wire bundling design, medical care operation and patient wearing are facilitated, the dismounting efficiency is improved, data errors are reduced, cross infection can be prevented, the electrode performance is improved from multiple aspects, the requirement for clinical high-precision and long-time stable monitoring of electroencephalogram signals is met, and technical development is promoted.

Description

Technical Field

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

[0002] In the field of neuroelectrophysiology (EEG) examination and polysomnography in brain science and clinical neurology, electrodes are key components, and their performance and ease of use directly affect the quality and efficiency of the test. At present, the commonly used EEG electrodes and polysomnography electrodes are mostly 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, and the other side to be attached to the patient's skin. In actual applications, when a single electrode is used up, 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, frequent plugging and unplugging of the electrode wire from the amplifier jack will inevitably cause serious wear or loosening of the battery cells in the amplifier that are in contact with the electrode wire. Once the battery cells are worn or loose, it will be difficult for the subsequently inserted electrode wires to ensure good contact, which will lead to a series of problems that seriously affect the test results, such as poor contact of the electrode wires, resulting in obstruction or interruption of signal transmission; increased impedance, causing distortion and attenuation of the collected EEG signals, reducing the quality and clarity of the signal; unstable electrodes, and the electrode position is prone to shifting during the test process, affecting the accuracy and stability of signal acquisition.

[0004] These problems have seriously hindered the effective application and development of EEG monitoring technology. In view of this, a method for quickly replacing EEG electrodes is provided to overcome the above problems, so as to improve the stability, reliability and convenience of using EEG electrodes and meet the needs of clinical diagnosis 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] In order 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 point is connected by a wire hub 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 unchanged, and the wire hub at the connection point is responsible 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 colors.

[0014] Furthermore, the electrodes on the electrode harness are disk-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 alpha waves in the EEG signals 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 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 the 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 wire into the amplifier jack by dividing the electrode wire into two parts and connecting them with a hub device, so that the electrode replacement and plugging are 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 of the subsequently inserted electrode wires, increased impedance, unstable electrodes, etc., effectively ensuring the stability and reliability of EEG signal acquisition, and providing a solid data foundation for clinical diagnosis.

[0018] The design of electrode wires bundled together greatly facilitates the operation and management of medical staff, and makes the electrodes on the patient side easier to remove, significantly increasing the operating efficiency. Moreover, the electrode wires bundled together are more comfortable to wear, beautiful and not easy to fall off, which improves the tolerance and cooperation of patients during long-term monitoring, ensures the continuity of the monitoring process, reduces data errors caused by patient discomfort or electrode displacement, and provides more comprehensive and reliable EEG signal data for clinical diagnosis, which helps doctors to more accurately judge the patient's condition and formulate more effective treatment plans. In addition, this design can also 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 is triggered, and a slow start and slow stop mechanism is adopted, thereby realizing the intelligent coordination of the plugging and unplugging operation with the EEG signal state, minimizing the interference of the plugging and unplugging operation on the EEG signal, and further improving the continuity and stability of EEG signal acquisition, so that doctors can obtain more complete and accurate EEG signals, which is helpful for in-depth analysis of 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 precise treatment of patients.

[0020] Based on the consideration of the complex electromagnetic environment of the hospital, the present invention arranges a high-sensitivity electromagnetic field sensor near the electrode, monitors the electromagnetic field strength and frequency at a frequency of 10 times per second, uses a hybrid algorithm combining an advanced support vector machine with a long short-term memory network to analyze the electromagnetic field data and establish a model to predict the future trend of electromagnetic field changes. For the characteristics of the EEG signals of different patients, such as patients with epilepsy or unexplained dizziness and confusion, when electromagnetic field interference is predicted, the electrode sensitivity and the low-pass filter cutoff frequency can be quickly adjusted according to the pre-built database to suppress the interference signal. This electrode performance prediction and adjustment method based on the change of environmental electromagnetic field fully considers the influence of the electromagnetic field generated by various electronic devices on the electrode performance, effectively reduces the interference of the environmental electromagnetic field on the electrode performance, ensures the accurate collection of the patient's characteristic EEG signals in a complex electromagnetic environment, provides more reliable and more 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 EEG monitoring technology field, and bring new breakthroughs and hopes for the diagnosis and treatment of neurological diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The schematic diagram of the traditional EEG electrode replacement method;

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

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work 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 also Figure 1-Figure 2 As shown, an embodiment of a method for quickly replacing EEG electrodes:

[0026] Scene Setting:

[0027] In the EEG monitoring room of the Department of Neurology of a comprehensive hospital with advanced medical facilities and professional technical teams, a long-term EEG monitoring process is being implemented for a 45-year-old male patient. The patient has been suffering from intermittent dizziness and confusion of unknown causes for a long time. The medical team hopes to use the high-precision brain electrical activity data obtained from this monitoring to assist in the accurate diagnosis of potential neurological diseases. Given that the monitoring time is expected to be up to 24 hours, during this period, the stability and signal quality of the electrode system are crucial for accurate diagnosis, and the electrodes need to be replaced regularly to maintain optimal monitoring performance and patient comfort.

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

[0029] step:

[0030] Following the established and standardized international 10-20 system electrode sorting rules in the field of clinical EEG monitoring, combined with the EEG signal monitoring needs of the patient's individual head specific area, the special gold-plated pin connector of the electrode bundle ① is carefully connected to the corresponding interface of the amplifier. This pin connector is made of metal materials with high conductivity, low impedance and good corrosion resistance, and uses a precise crimping process to ensure that the connection parts are tight, stable and reliable, thus building 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 types of hub connectors in terms of signal integrity, anti-interference performance, plug-in durability, and adaptability, a DB-15 connector with 15 independent pins was finally selected as the hub. The connector uses an optimized shielding structure design to effectively resist external electromagnetic interference and ensure the purity of signal transmission. Subsequently, the electrode wires ② and ③ are accurately connected through this DB-15 hub, and 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 of the harnesses on both sides, eliminating the risk of misconnection, and thus building a complete, efficient and stable electrode wire connection system, which provides a strong guarantee for the accurate collection and transmission of subsequent EEG signals.

[0032] Select disc-shaped silver-silver chloride electrodes that meet medical-grade biocompatibility standards and have excellent conductivity, and accurately paste them on the corresponding position of the patient's scalp according to the standard EEG electrode placement guidelines issued by the American Electroencephalography Association (AEEG). During the pasting process, a professionally formulated conductive paste is used, which has appropriate viscosity and conductivity, can effectively fill the tiny gap between the electrode and the skin, reduce contact impedance, and minimize signal loss caused by poor contact, ensuring that the collected EEG signals have high fidelity and high signal-to-noise ratio, providing reliable data support for clinical diagnosis.

[0033] The international 10-20 system electrode sorting 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, ensure the representativeness and integrity of the collected EEG signals, and provide a comprehensive data basis for accurate diagnosis. The selection of high-conductivity, low-impedance and corrosion-resistant pin connector materials and precision crimping technology is based on a deep understanding of the principles of electrical signal transmission and the characteristics of metal materials. High-quality materials and processes can reduce the reflection, scattering and attenuation of signals at the connection site, ensure efficient transmission of signals, and thus ensure that the collected EEG signals truly reflect the patient's brain electrical activity state.

[0034] The DB-15 connector has shown good performance in similar medical monitoring equipment applications. Its multi-pin design can meet the needs of complex electrode line connections, while the internal shielding structure can effectively block external electromagnetic interference and ensure the stability and reliability of signal transmission. Strict one-to-one connection is the basic requirement to ensure the normal operation of the electrode line system. Any wrong connection may cause signal acquisition errors or loss, affecting the accuracy of the diagnosis results.

[0035] The use of disc-shaped silver-silver chloride electrodes and special conductive paste that meet biocompatibility standards is to ensure that a stable, low-impedance electrical contact interface can be formed between the electrode and the skin. Silver-silver chloride electrodes have good electrochemical stability and low polarization potential, which can reduce electrochemical noise between the electrode and the skin and improve signal quality. The use of conductive paste is based on the electrical properties of the skin and the working principle of the electrode. By filling the gap and reducing the contact impedance, it ensures that the electrical signal can be smoothly transmitted from the cerebral cortex to the electrode, thereby improving the signal fidelity and signal-to-noise ratio, providing a more reliable basis for clinical diagnosis.

[0036] This electrode wire connection architecture abandons the traditional mode of directly plugging a single electrode wire into the amplifier jack, and fundamentally avoids the problem of wear and tear of the amplifier jack caused by repeated plugging and unplugging. By dividing the electrode wire into two parts and connecting them with a hub device, it effectively solves the key problems in the prior art that the amplifier battery core becomes worn or loose due to repeated plugging and unplugging, which in turn causes poor electrode wire contact, increased impedance, and decreased electrode stability, which seriously affect the quality and stability of EEG signal acquisition. It provides reliable hardware guarantee for long-term, high-precision EEG monitoring, ensuring that the collected EEG signals can accurately reflect the patient's brain electrophysiological state and improve the accuracy and reliability of diagnosis.

[0037] The design of electrode wires bundled together not only conforms to the principles of ergonomics and facilitates convenient and efficient operation and management by medical staff, but also makes it more comfortable and beautiful when worn by patients, effectively reducing the risk of accidental electrode detachment due to patient activities. This greatly improves the tolerance and cooperation of patients 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. Plugging and unplugging operation of EEG signal phase control during electrode replacement

[0039] step:

[0040] Before starting 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 used. The device can collect the patient's EEG signals in real time, accurately and continuously at a high sampling frequency of 1000 Hz per second. Through the high-speed and intensive sampling process, it is ensured that the subtle changes and characteristic information of the EEG signals can be fully captured, including the amplitude, phase and time series changes of different frequency components. At the same time, the 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, and then accurately extract the phase information of the alpha wave in the EEG signal. As a typical component of EEG activity in a quiet, relaxed and awake state, the accurate acquisition of the phase information of the alpha wave is of great significance for judging the functional state of the brain, especially in the process of electrode replacement, which can provide a key decision-making basis for intelligent plug-in 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 continuously and stably monitored. 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 unplug process, the control system sends accurate, continuous and dynamically adjusted control signals to the hub device by accurately 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 unplug process in real time to ensure that the hub device plugs and unplugs the electrode line smoothly, slowly and accurately, avoids instantaneous mechanical shocks that cause additional interference and noise to the EEG signal, ensures the stability and continuity of the EEG signal during the electrode replacement process, and guarantees the quality and reliability of the monitoring data.

[0042] The high sampling frequency of 1000 Hz per second is determined based on the in-depth study of the complex and changeable characteristics of EEG signals and the signal accuracy requirements of clinical diagnosis. EEG signals are weak, complex and have a wide frequency range of bioelectric signals. High sampling frequency can ensure that the signal is discretized sufficiently finely in the time domain, so as to capture the rapid changes and detailed information of the signal, avoid signal distortion and information loss caused by insufficient sampling, and provide a rich and accurate data basis 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 α wave phase information has important reference value for judging the physiological state and functional activities of the brain. Therefore, accurate extraction of α wave phase is a key step in realizing intelligent plug-in control, which can ensure that the electrode replacement operation is performed at the moment when the interference to the EEG signal is minimal.

[0043] The selection of the α wave phase in the range of 0° to 90° for plugging and unplugging operations is based on the conclusions drawn from a large number of clinical experimental studies and data analysis. Within this phase range, the brain's neural activity is relatively stable, and the energy distribution and change pattern of the α wave are relatively stable. At this time, plugging and unplugging operations have the least interference with EEG signals, which can minimize the signal fluctuations and noise caused by plugging and unplugging operations, and ensure the continuity and stability of EEG signals. The application of the 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 instantaneous impact force can be avoided from having adverse effects on the electrodes and EEG signals, ensuring the quality and stability of EEG signals during the operation. The use of closed-loop control algorithms further improves the accuracy and reliability of plugging and unplugging operations, and can adjust the control signal in real time according to force feedback and displacement information to ensure the stability and safety of the plugging and unplugging process.

[0044] Through high-precision signal acquisition and advanced phase monitoring technology, the hub device can be plugged in and out at a specific stage when the EEG signal is relatively stable, realizing intelligent coordination between the plugging and unplugging operation 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, provide a more reliable and detailed basis for disease diagnosis, improve the accuracy and reliability of diagnosis, reduce the risk of misdiagnosis and missed diagnosis due to signal interference, and provide strong support for the precise treatment of patients.

[0045] 3. Adjustment of electrode performance based on changes in environmental electromagnetic fields

[0046] step:

[0047] Several precisely calibrated high-sensitivity three-axis fluxgate electromagnetic field sensors are reasonably arranged near the electrodes. These sensors use advanced magnetoresistance effect principles and high-precision signal conditioning circuits to accurately measure magnetic field strength and frequency components ranging from low frequency (such as 50Hz mains interference, which is a common basic frequency interference source in hospital environments, mainly from lighting equipment, medical instruments, etc.) to high frequency (such as radio frequency interference in the wireless communication band, including interference generated by wireless network equipment and mobile communication equipment in hospitals). The sensor monitors the intensity and frequency changes of the environmental electromagnetic field in real time and quickly at a frequency of 10 times per second, and accurately transmits the collected three-dimensional magnetic field data to the data processing unit through a high-speed, interference-resistant data transmission line.

[0048] The data processing unit uses a powerful graphics processing unit (GPU) accelerated computing platform and a deep learning-based algorithm architecture to collect electromagnetic field data within 1 minute, and uses a hybrid algorithm that combines support vector machine (SVM) and long short-term memory network (LSTM) to conduct in-depth analysis and modeling of these data. This hybrid algorithm can give full play to the advantages of SVM in processing small samples and nonlinear data and the expertise of LSTM in time series prediction. Through learning and training of historical electromagnetic field data, an accurate model of the change of electromagnetic field intensity and frequency over time is established. Based on the laws and trends of historical data, the model can accurately predict the change trend of the electromagnetic field in the next 5 minutes, providing a reliable basis for adjusting electrode performance in advance.

[0049] For this patient with unexplained dizziness and confusion, during the monitoring process, when it is predicted that the environmental electromagnetic field will have an interference of increased intensity and a frequency of 50Hz in the next 5 minutes, the electrode parameter adjustment program is quickly started based on the personalized database of the impact of the electromagnetic field on the patient's EEG signals established in advance through a large amount of experimental and clinical data accumulation. By precisely controlling the circuit parameters of the electrode, the sensitivity of the electrode is reduced by 20%, reducing the electrode's response to interference signals, and at the same time reducing the cutoff frequency of the low-pass filter from 50Hz to 40Hz, effectively preventing the 50Hz interference signal from entering the subsequent signal acquisition and processing links, ensuring that the patient's EEG signal characteristics can be clearly collected, especially the potential abnormal EEG signals related to dizziness and confusion, providing strong support for doctors to accurately judge the condition.

[0050] In the complex electromagnetic environment of the hospital, there are electromagnetic interference sources of various frequencies and intensities, which will have a serious impact on the performance of EEG electrodes, causing the collected EEG signals to be contaminated by noise, affecting the accuracy of diagnosis. Therefore, it is necessary to deploy a highly sensitive three-axis fluxgate electromagnetic field sensor covering a wide frequency range, which can comprehensively and accurately monitor the changes in the environmental electromagnetic field. The sampling frequency of 10 times per second can capture the rapid changes of the electromagnetic field in time, providing timely and accurate data support for subsequent real-time adjustments.

[0051] The hybrid algorithm combining SVM and LSTM has significant advantages in processing complex electromagnetic field data modeling. It can mine the inherent laws and trends of electromagnetic field changes from a large amount of historical data, thereby achieving accurate prediction of future electromagnetic field changes. This machine learning-based method 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 early adjustment of electrode performance.

[0052] Adjusting electrode parameters according to a pre-established database is based on in-depth research on the interaction between electromagnetic fields and EEG signals and a large number of clinical practice verifications. Different patients have different sensitivity and response characteristics to electromagnetic field interference. By conducting long-term monitoring and analysis of EEG signals and electromagnetic field interference data of specific patients and establishing a personalized database, it is possible to quickly and accurately adjust electrode parameters when encountering electromagnetic field interference, minimize the impact of interference on EEG signals, ensure that the collected EEG signals truly reflect the patient's brain activity state, and improve the accuracy and reliability of diagnosis.

[0053] In a complex environment like a hospital filled with various electronic devices, electromagnetic field interference is an important factor affecting EEG electrode performance and signal quality. By real-time monitoring and precise modeling to predict electromagnetic field changes, and making targeted and 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 collection of patient characteristic EEG signals in complex electromagnetic environments. Doctors can obtain purer and more accurate EEG signals, which helps to more accurately judge the patient's condition, provide strong support for the formulation of effective treatment plans, improve the accuracy and reliability of clinical diagnosis, reduce the risk of diagnostic errors and treatment delays caused by electromagnetic field interference, and provide more reliable technical guarantees for the diagnosis and treatment of neurological diseases.

[0054] Summarize:

[0055] Through the above embodiments, the EEG electrode rapid replacement method of the present invention has shown excellent advantages and significant innovative value in actual clinical applications. First, the unique electrode line connection and line collection device design fundamentally avoids the repeated plugging and unplugging wear of the amplifier jack, effectively solves the key problems that have long plagued the field of EEG monitoring in the prior art, such as poor electrode line contact, increased impedance and unstable electrodes, ensures the stability and reliability of EEG signal acquisition, and provides solid basic data support for clinical diagnosis. Secondly, the EEG signal phase information is used to intelligently control the plug-in and unplug operation during the electrode replacement process, further reducing the interference to the EEG signal, improving the quality and continuity of the monitoring data, enabling doctors to obtain more complete and accurate EEG signals, and helping to deeply analyze the patient's EEG activity, and improving the accuracy and reliability of diagnosis. Finally, the electrode performance prediction and adjustment method based on the change of environmental electromagnetic field fully considers the impact of the complex electromagnetic environment of the hospital on the electrode performance, and effectively responds to various electromagnetic field interferences through real-time monitoring, precise modeling and intelligent adjustment, ensuring that the patient's EEG signal characteristics can be accurately collected under different electromagnetic field conditions, providing 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, not only significantly improving the quality and stability of EEG signal acquisition, but also greatly enhancing the adaptability and anti-interference ability of the electrode system to complex environments, and ultimately greatly improving the effect 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, and provide 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 point is connected by a wire hub 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 unchanged, and the wire hub at the connection point is responsible for plugging and unplugging.

2. A method for quickly replacing EEG electrodes as claimed in claim 1, characterized in that: The hub uses a DB-15 connector.

3. A method for quickly replacing EEG electrodes as claimed in claim 1, characterized in that: The wiring hub uses an M12 circular connector.

4. A method for quickly replacing EEG electrodes as claimed in claim 1, characterized in that: The cable hub uses LEMO push-pull self-locking circular connector.

5. A method for quickly replacing EEG electrodes as claimed in claim 1, characterized in that: The wiring hub uses an aviation plug, which includes but is not limited to GX16.

6. A method for quickly replacing EEG electrodes as claimed in claim 1, characterized in that: The wiring harnesses on both sides correspond one to one through the plugs.

7. A method for quickly replacing EEG electrodes as claimed in claim 1, characterized in that: The electrode wires are bundled and distinguished by color.

8. A method for quickly replacing EEG electrodes as claimed in claim 1, characterized in that: The electrodes on the electrode harness are disk-shaped electrodes.

9. A method for quickly replacing EEG electrodes as claimed in claim 1, characterized in that: During the electrode replacement process, EEG signals are collected at a sampling frequency of 1000 Hz per second, and the phase information of alpha waves in the EEG signals 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 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.

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