A brain-computer interface tibial nerve electrical stimulation closed-loop control system

Abstract

The present application discloses a brain-computer interface tibial nerve electrical stimulation closed-loop control system, comprising: a scalp electrophysiological monitoring terminal, a tibial nerve electrical stimulation control terminal and a programmable terminal; through the scalp electrophysiological monitoring terminal, scalp electrophysiological signals are monitored in real time in a non-invasive manner, and abnormal signals of overactive bladder are identified when the patient has symptoms of urgency; through the tibial nerve electrical stimulation control terminal, tibial nerve electrical stimulation control is automatically started in response to abnormal signals to achieve on-demand control of the patient at the onset of symptoms of overactive bladder and during the period of symptoms; treatment parameters related to on-demand control are obtained through the programmable terminal, and doctors can configure personalized treatment parameters in a targeted manner according to the displayed information, so as to perform real-time control of tibial nerve electrical stimulation for patients with overactive bladder, effectively improving the accuracy and treatment effect of treatment, reducing treatment time, and improving patient comfort and compliance.

Description

Technical Field

[0001] The present application relates to the field of neural electrical stimulation technology, and in particular to a brain-computer interface tibial nerve electrical stimulation closed-loop control system. Background Art

[0002] Tibial nerve regulation is an effective method of treating overactive bladder (frequent urination, urgency and urge incontinence) by stimulating the tibial nerve at the Sanyinjiao, combining the theory of traditional Chinese medicine acupuncture points. Tibial nerve regulation is generally performed by applying electrical stimulation pulses to the Sanyinjiao at the posterior tibia through a tibial nerve electrical stimulation generator, either through a transcutaneous patch or through acupuncture. The principle is that the tibial nerve contains nerve fibers from L4 to S3, which originate from the same spinal cord segment as the nerve fibers that control the bladder and pelvic floor. By stimulating the somatic afferent components, it inhibits the afferent activity of the bladder, blocks the transmission of abnormal sensations to the spinal cord and brain, and then affects and regulates the behavior of the sacral nerve-controlled effector organs such as the bladder, urethral sphincter and pelvic floor, playing the role of "neural regulation" and is used to treat overactive bladder.

[0003] At present, the general scheme for tibial nerve regulation to treat overactive bladder is to select a frequency between 0-200Hz and a constant size stimulation pulse for a treatment process of 30 minutes to 1 hour according to the actual clinical treatment situation. Although this general treatment scheme has achieved certain results in clinical practice, it still has problems such as poor real-time performance, poor treatment accuracy, and inability to achieve on-demand precision treatment. Therefore, according to the principle of tibial nerve treatment of overactive bladder, if the onset or occurrence of symptoms of overactive bladder can be accurately monitored in real time, tibial nerve electrical stimulation regulation can be applied in real time to achieve "on-demand stimulation" and "precision treatment", and to interfere with the transmission of abnormal urination sensation to the spinal cord and brain, it can better relieve the patient's symptoms. Summary of the invention

[0004] The embodiment of the present application provides a brain-computer interface tibial nerve electrical stimulation closed-loop control system to achieve real-time monitoring of the patient's scalp electrophysiological signals and automatic identification of abnormal signals, start tibial nerve electrical stimulation control, and realize real-time control and on-demand stimulation when overactive bladder symptoms begin to appear and during the symptoms, thereby improving the accuracy of treatment and achieving the technical effect of effectively alleviating the patient's symptoms.

[0005] The present application embodiment adopts the following technical solutions:

[0006] The embodiment of the present application provides a brain-computer interface tibial nerve electrical stimulation closed-loop control system, the system comprising: a scalp electrophysiological monitoring terminal, a tibial nerve electrical stimulation control terminal and a program control terminal, the scalp electrophysiological monitoring terminal is connected to the tibial nerve electrical stimulation control terminal, the program control terminal is connected to the tibial nerve electrical stimulation control terminal,

[0007] The scalp electrophysiological monitoring terminal is used to monitor the scalp electrophysiological signals in real time in a non-invasive manner and identify abnormal signals of overactive bladder when the patient has urinary urgency symptoms. The scalp electrophysiological signals can indirectly represent the frequency band related to overactive bladder when the patient has urinary urgency symptoms;

[0008] The tibial nerve electrical stimulation control end is used to respond to the abnormal signal and automatically start the tibial nerve electrical stimulation control, so as to achieve on-demand control of the patient when the symptoms of overactive bladder begin to appear and during the symptoms;

[0009] The program-controlled terminal is used to obtain the treatment parameters related to the on-demand regulation.

[0010] Optionally, it also includes: configuration information, the configuration information is configured to be generated by the program-controlled end and sent to the scalp electrophysiological monitoring end, the scalp electrophysiological monitoring end is also used to identify whether the abnormal signal exists through the scalp electrophysiological signal monitored in real time and the configuration information, the configuration information at least includes feature set configuration information and a feature recognition model, the feature set configuration information is used to screen the processing result of the scalp electrophysiological signal, and the feature recognition model is used to identify whether the abnormal signal exists according to the processing result of the scalp electrophysiological signal;

[0011] The tibial nerve electrical stimulation control end is also used to

[0012] When it is identified that the abnormal signal is restored to a non-abnormal signal of normal bladder activity, the tibial nerve electrical stimulation regulation is automatically turned off in response to the non-abnormal signal and according to a preset delay time;

[0013] The program control terminal is also used to obtain input information input by the doctor and generate the configuration information according to the input information.

[0014] Optionally, the program-controlled end includes a feature recognition setting unit, and the scalp electrophysiological monitoring end includes a feature recognition unit. The feature recognition setting unit is used to receive model input information in the input information, generate the feature recognition model according to the model input information, and send the feature recognition model to the feature recognition unit.

[0015] Optionally, the program control end includes a feature value set setting unit, and the scalp electrophysiological monitoring end includes a feature value set configuration unit.

[0016] The feature value set setting unit is used to receive the set input information in the input information, generate the feature set configuration information according to the set input information, and send the feature set configuration information to the feature value set configuration unit.

[0017] Optionally, the feature value set configuration unit is used to filter the processing result of the scalp electrophysiological signal according to the feature set configuration information, and obtain a feature value set, wherein the feature value set at least includes feature values ​​of overactive bladder in the patient's awake daily activity state and feature values ​​of overactive bladder in the patient's semi-sleep state after closing eyes;

[0018] The feature recognition unit is used to recognize the feature value set based on the feature recognition model and determine whether there is an abnormal signal.

[0019] Optionally, the program-controlled end further includes a raw data storage unit and a signal analysis unit.

[0020] The raw data storage unit is used to receive and display the scalp electrophysiological signal, the processing result of the scalp electrophysiological signal, and the abnormal signal judgment result;

[0021] The signal analysis unit is used to process the scalp electrophysiological signal to output and display a program-controlled processed signal.

[0022] Optionally, the program-controlled end further includes a treatment parameter setting unit, the treatment parameter setting unit is used to respond to the scalp electrophysiological signal, the processing result of the scalp electrophysiological signal and the abnormal signal judgment result, and receive the customized treatment parameter input by the doctor;

[0023] The treatment parameters are sent to the tibial nerve electrical stimulation control terminal, so that after the tibial nerve electrical stimulation control is automatically turned on, the patient can achieve on-demand control according to the treatment parameters when the symptoms of overactive bladder begin to appear and during the symptoms.

[0024] Optionally, the treatment parameters acquired by the programming terminal include at least one of the following: stimulation waveform, amplitude, pulse width, frequency, rising cycle, falling cycle, continuous cycle, treatment duration, variable frequency or constant frequency, high frequency, low frequency, voltage or current source.

[0025] Optionally, the scalp electrophysiological monitoring end also includes an acquisition unit and a feature extraction unit, the acquisition unit is used to acquire scalp electrophysiological signals located on the head through electrodes closely attached to the scalp; the feature extraction unit is used to perform cluster analysis on the scalp electrophysiological signals processed by the filtering unit according to a specific frequency band, and calculate the characteristic value in the specific frequency band as the processing result of the scalp electrophysiological signal; the specific frequency band includes the short-time spectrum energy and change rate of the θ wave with a passband of 3.5-8Hz, the short-time spectrum energy and change rate of the α wave with a passband of 8-12Hz, and the short-time spectrum energy and change rate of the β wave with a passband of 12-33Hz.

[0026] Optionally, the scalp electrophysiological monitoring terminal is also used to extract the first scalp electrophysiological signal characteristic value of the patient in a state of awake daily activities and a semi-sleep state after closing eyes under non-overactive bladder syndrome by wearing the device for a period of time in advance;

[0027] Extract the second scalp electrophysiological characteristic values ​​of patients with overactive bladder during daily activities in the awake state and in the semi-sleep state with eyes closed;

[0028] Based on the first scalp electrophysiological signal characteristic value and the second scalp electrophysiological characteristic value, obtaining a scalp electrophysiological characteristic set for pre-wearing use;

[0029] A comparative analysis is performed based on the scalp electrophysiological feature set during pre-wearing and use and the feature value set of electrophysiological signals monitored during formal wearing and use, and a determination is made as to whether the requirements for starting electrical stimulation therapy are met, so as to perform personalized pre-configuration for the patient.

[0030] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0031] First, the brain-computer interface tibial nerve electrical stimulation closed-loop control system of the present application adopts a closed-loop control design, and monitors the scalp electrophysiological signals in real time in a non-invasive manner through the scalp electrophysiological monitoring terminal, and identifies the abnormal signal of overactive bladder when the patient has urinary urgency symptoms; through the tibial nerve electrical stimulation control terminal, responds to the abnormal signal and automatically turns on the tibial nerve electrical stimulation control, so as to achieve "on-demand control" and "precise treatment" of the patient when the symptoms of overactive bladder begin to appear and during the symptoms; compared with traditional open-loop stimulation, the closed-loop control design of the present application is more intelligent and accurate;

[0032] Second, the brain-computer interface tibial nerve electrical stimulation closed-loop control system of the present application obtains on-demand control-related treatment parameters through the program-controlled terminal, and can display information such as scalp electrophysiological signals, signal processing results, and abnormal signal judgment results. It can not only perform tibial nerve electrical stimulation control through pre-stored standardized treatment parameters or treatment parameters automatically generated by the model, but also allows doctors to configure personalized treatment parameters in a targeted manner according to the above display information to perform tibial nerve electrical stimulation control on patients, effectively improving the accuracy and treatment effect of treatment, effectively alleviating patient symptoms, and is a manifestation of precision medicine;

[0033] Third, unlike the general control method used in related technologies, which has poor accuracy and causes discomfort to patients due to continuous electrical stimulation, and taking into account that continuous stimulation of the tibial nerve will enter a refractory period, the brain-computer interface tibial nerve electrical stimulation closed-loop control system of the present application can automatically turn on and off electrical stimulation control according to the monitoring results of individual scalp electrophysiological signals, thereby achieving on-demand stimulation, intermittent stimulation, and quantitative precise stimulation, effectively avoiding ineffective stimulation during the refractory period, and significantly reducing the discomfort caused by stimulation to patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0035] Figure 1 This is a schematic diagram of the structure of the brain-computer interface tibial nerve electrical stimulation closed-loop control system in the embodiment of the present application;

[0036] Figure 2 The energy state diagram of the EEG characteristics of healthy people under different bladder states;

[0037] Figure 3 This is a schematic diagram of the bands after EEG feature processing and identification in different bladder states of healthy people;

[0038] In the figure: 1. Scalp electrophysiological monitoring terminal; 2. Program control terminal; 3. Tibial nerve electrical stimulation control terminal;

[0039] 11. Acquisition unit; 12. Filtering unit; 13. Feature extraction unit; 14. Feature recognition unit; 15. First wireless transmission unit; 16. Feature value set configuration unit; 21. Second wireless transmission unit; 22. Raw data storage unit; 23. Signal analysis unit; 24. Feature recognition setting unit; 25. Feature value set setting unit; 26. Treatment parameter setting unit; 31. Third wireless transmission unit; 32. Electrical stimulation control unit; 33. Treatment parameter unit. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0041] To facilitate understanding of the technical solution of the brain-computer interface tibial nerve electrical stimulation closed-loop control system of the embodiment of the present application, the technical principle of the embodiment of the present application is first explained.

[0042] The inventors measured the scalp electrophysiological signals of different individuals in the bladder empty state and bladder urgent state. Figure 2 and Figure 3 As shown in Figure 2, taking healthy individuals as an example, the results of multiple experiments show that in the state of urinary bladder urgency, the prefrontal alpha wave of the subject is significantly lower than that in the state of bladder empty. Combined with Figure 2, it can be seen that the left side is the alpha wave energy reflecting the EEG state when the subject's bladder is empty, and the right side is the alpha wave energy reflecting the EEG state when the subject has a strong sense of urinary urgency. Afterwards, the inventor processed and analyzed the collected EEG data through machine learning technology, and combined with Figure 3 It can be seen that 343 segments in the resting state (i.e., when the bladder is empty) are identified as 313 segments in the resting state and 30 segments in the task state; 339 segments in the task state (i.e., when the bladder is in an urgent state) are identified as 24 segments in the resting state and 315 segments in the task state. This shows that the EEG characteristics of the subjects in different bladder states are significantly different.

[0043] Based on this, the technical concept of the present application is to monitor the patient's scalp electrophysiological signals under urinary urgency symptoms and non-urinary urgency symptoms in a non-invasive manner through EEG monitoring technology, and use the correlation between scalp electrophysiological signals and the patient's brain function to identify abnormal signals related to overactive bladder, and then according to the changes in the patient's EEG activity, start tibial nerve electrical stimulation regulation when the patient's urinary urgency symptoms appear, so as to achieve on-demand regulation and precise treatment at the beginning of overactive bladder symptoms and during the symptoms, thereby achieving the technical effect of improving the real-time and intelligence level of the system, improving the accuracy of treatment, and effectively alleviating the patient's overactive bladder symptoms.

[0044] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0045] The present application embodiment provides a brain-computer interface tibial nerve electrical stimulation closed-loop control system, such as Figure 1 As shown, a schematic diagram of the structure of a brain-computer interface tibial nerve electrical stimulation closed-loop control system is provided. The brain-computer interface tibial nerve electrical stimulation closed-loop control system of the embodiment of the present application comprises: a scalp electrophysiological monitoring terminal 1, a program control terminal 2, and a tibial nerve electrical stimulation control terminal 3, wherein the scalp electrophysiological monitoring terminal 1 is connected to the tibial nerve electrical stimulation control terminal 3, and the program control terminal 2 is connected to the tibial nerve electrical stimulation control terminal 3;

[0046] The scalp electrophysiological monitoring terminal 1 is used to monitor the scalp electrophysiological signals in real time in a non-invasive manner, and identify abnormal signals of overactive bladder when the patient has urinary urgency symptoms. The scalp electrophysiological signals can indirectly represent the frequency band related to overactive bladder when the patient has urinary urgency symptoms; the tibial nerve electrical stimulation control terminal 3 is used to respond to the abnormal signal and automatically start tibial nerve electrical stimulation control to achieve on-demand control of the patient when the symptoms of overactive bladder begin to appear and during the symptoms; the programmable control terminal 2 is used to obtain treatment parameters related to the on-demand control.

[0047] In this embodiment, firstly, the patient's EEG signal is collected and processed by the scalp electrophysiological monitoring terminal 1, that is, the scalp electrophysiological signal of the patient's body surface is monitored in a non-invasive manner, which may specifically include the scalp electrophysiological signal of the patient during urinary urgency symptoms and non-urinary urgency symptoms within a preset period; secondly, it is possible to judge and identify whether there is an abnormal signal based on the processing result of the scalp electrophysiological signal and the configuration information sent by the program-controlled terminal 2. When an abnormal signal exists, the scalp electrophysiological monitoring terminal 1 generates a control instruction and wirelessly transmits it to the tibial nerve electrical stimulation control terminal 3 to automatically start the electrical stimulation control; the scalp electrophysiological signal and its processing result are received and displayed by the program-controlled terminal 2, and the received scalp electrophysiological signal can also be processed at the program-controlled terminal 2. And output the program-controlled processing signal, and display the program-controlled processing signal, so that the doctor can make a comprehensive judgment based on the interactive information such as the scalp electrophysiological signal displayed by the program-controlled terminal 2, the processing result of the scalp electrophysiological signal, and the program-controlled processing signal, and input the input information related to the treatment parameter, so as to send the input information to the tibial nerve electrical stimulation control terminal 3 through the program-controlled terminal 2; finally, through the tibial nerve electrical stimulation control terminal 3, receive the control instruction of the scalp electrophysiological monitoring terminal 1, such as the control instruction of turning on or off the electrical stimulation pulse, and obtain the treatment parameters configured by the program-controlled terminal 2, and perform tibial nerve electrical stimulation control according to the control instruction and the treatment parameter, so as to realize the patient's on-demand control when the symptoms of overactive bladder begin to appear and during the symptoms. Of course, the treatment parameters related to the on-demand control in the embodiment of the present application can be standardized treatment parameters pre-stored in the treatment parameter setting unit 26, or can be treatment parameters automatically generated based on the patient's EEG signal through a pre-built machine learning model, or can be the electrical stimulation pulse parameters that the doctor comprehensively judges and sets according to the interactive interface information of the display unit 23, which is not limited here.

[0048] It can be seen that, unlike the existing technical solutions that use bladder pressure and volume parameters as indirect indicators for judging abnormal symptoms, the brain-computer interface tibial nerve electrical stimulation closed-loop control system of the embodiment of the present application can, on the one hand, monitor the patient's scalp electrophysiological signals in real time through the scalp electrophysiological monitoring terminal, and automatically identify the signals, thereby realizing real-time control and on-demand control of electrical stimulation during the overactive bladder symptom period. Compared with the traditional open-loop stimulation solution, it is more intelligent and forms a complete closed loop from the patient's brain electrical activity monitoring to the tibial nerve electrical stimulation control; on the other hand, the scalp electrophysiological signals, signal processing results, and abnormalities are displayed through the programmable terminal. The display information such as the signal judgment results enables the doctor to configure personalized treatment parameters in a targeted manner according to the above display information, which effectively improves the accuracy and effect of the treatment, reduces the treatment time, and improves the patient's comfort and compliance; on the other hand, since the tibial nerve will enter the refractory period due to continuous stimulation, no response will occur even if it is stimulated again within a certain period of time. Therefore, the present application can automatically turn on and off the electrical stimulation regulation based on the real-time monitoring results of the individual scalp electrophysiological signals, thereby realizing the on-demand stimulation, intermittent stimulation and quantitative precise stimulation of the regulation system, avoiding ineffective stimulation and reducing the discomfort of the patient caused by the stimulation.

[0049] In some embodiments of the present application, abnormal signals generally refer to signals related to overactive bladder, that is, the present application is particularly suitable for monitoring, symptom identification, evaluation and treatment of OAB patients (overactive bladder patients). Of course, the technical solution of the present application can also be extended to the monitoring and treatment of other urinary tract dysfunction symptoms, which is not limited here.

[0050] Preferably, the abnormal signals include but are not limited to abnormal signals related to overactive bladder, such as sensory evoked potentials, emotion evoked potentials and action evoked potentials that cause urination reactions; wherein sensory evoked potentials refer to potential signals related to the patient's sensory states such as the urge to urinate, emotion evoked potentials refer to potential signals related to emotional states such as anxiety and worry caused by the patient's urge to urinate and the influence of the external environment; action evoked potentials refer to potential signals related to the action state caused by the patient's urge to urinate; the above-mentioned evoked potentials are all related to the patient's brain functional activities, and their EEG characteristics under different bladder states have obvious differences. Therefore, by monitoring and identifying the above-mentioned evoked potentials, it can be determined whether the patient's scalp electrophysiological signals are abnormal; a feasible implementation method is to determine the specific frequency band of overactive bladder related to the patient's urgency symptoms based on the processing of the patient's scalp electrophysiological signals and the generation of time domain diagrams, so as to screen out abnormal spectrum energy and change states.

[0051] Of course, the above contents on the classification, identification and judgment of abnormal signals are exemplary embodiments, which are only for the convenience of understanding and simplified description, and cannot be understood as limitations on the present application.

[0052] In some embodiments, the brain-computer interface tibial nerve electrical stimulation closed-loop control system of the embodiment of the present application also includes: configuration information, the configuration information is configured to be generated by the program-controlled end 2 and sent to the scalp electrophysiological monitoring end 1, the scalp electrophysiological monitoring end 1 is also used to identify whether the abnormal signal exists through the real-time monitored scalp electrophysiological signal and the configuration information, the configuration information at least includes feature set configuration information and feature recognition model, the feature set configuration information is used to screen the processing results of the scalp electrophysiological signal, and the feature recognition model is used to identify whether the abnormal signal exists according to the processing results of the scalp electrophysiological signal; the tibial nerve electrical stimulation control end 3 is also used to respond to the non-abnormal signal and automatically turn off the tibial nerve electrical stimulation control according to the preset delay time when the abnormal signal is identified to be restored to a non-abnormal signal of normal bladder activity; the program-controlled end is also used to obtain input information entered by the doctor and generate the configuration information according to the input information.

[0053] For example, the input information input by the doctor is received through the program-controlled terminal 2, and the configuration information is generated according to the input information and sent to the scalp electrophysiological monitoring terminal 1; the scalp electrophysiological monitoring terminal 1 filters the processing results of the scalp electrophysiological signal according to the feature set configuration information in the configuration information, and obtains a feature value set; the feature recognition model in the configuration information is used to identify the feature value set to determine whether there is an abnormal signal; it can be understood that when an abnormal signal is identified, the tibial nerve electrical stimulation regulation is automatically turned on through the tibial nerve electrical stimulation regulation terminal 3, and then when the abnormal signal is restored to a non-abnormal signal, the tibial nerve electrical stimulation regulation is automatically turned off through the tibial nerve electrical stimulation regulation terminal 3; of course, after the abnormal signal disappears, a delay time can be set to realize the delayed closing function of the electrical stimulation regulation, thereby further ensuring the effect of the electrical stimulation treatment.

[0054] In some embodiments of the present application, the program-controlled end 2 includes a feature recognition setting unit 24, and the scalp electrophysiological monitoring end 1 includes a feature recognition unit 14. The feature recognition setting unit 24 is used to receive model input information in the input information, generate the feature recognition model according to the model input information, and send the feature recognition model to the feature recognition unit 14.

[0055] Specifically, the doctor's input information includes model input information. The feature recognition setting unit 24 is used to receive the model input information and generate a feature recognition model according to the model input information, and send the feature recognition model to the feature recognition unit 14 of the scalp electrophysiological monitoring terminal 1. The feature recognition model includes but is not limited to machine learning models such as support vector machines and neural networks. For example, model parameters and parameters such as thresholds for screening abnormal signals can be set by the feature recognition setting unit 24 and sent to the feature recognition unit 14 to complete the recognition of abnormal signals.

[0056] In some embodiments of the present application, the program-controlled end 2 includes a feature value set setting unit 25, and the scalp electrophysiological monitoring end 1 includes a feature value set configuration unit 16. The feature value set setting unit 25 is used to receive the set input information in the input information, generate the feature set configuration information based on the set input information, and send the feature set configuration information to the feature value set configuration unit 16.

[0057] Specifically, the doctor's input information also includes set input information. The feature value set setting unit 25 is used to receive the set input information and generate feature set configuration information according to the set input information, and send the feature set configuration information to the feature value set configuration unit 16 of the scalp electrophysiological monitoring terminal 1.

[0058] In some embodiments of the present application, the feature value set configuration unit 16 is used to filter the processing results of the scalp electrophysiological signal according to the feature set configuration information, and obtain a feature value set, wherein the feature value set at least includes the feature values ​​of overactive bladder when the patient is in a waking daily activity state, and the feature values ​​of overactive bladder when the patient is in a semi-sleep state after closing his eyes; the feature recognition unit 14 is used to identify the feature value set based on the feature recognition model, and determine whether there is an abnormal signal.

[0059] For example, the feature value set configuration unit 16 filters the processing results of the scalp electrophysiological signal according to the feature set configuration information transmitted by the program control terminal 2, and obtains a feature value set, which may specifically include information such as spectrum energy and change rate, peak value, RMS value (root mean square value), duration, etc.; the feature value set may be a subset of the original processing result set, or it may be the original processing result set itself. In other words, the feature value set configuration unit 16 may only contain part of the data in the feature value set setting unit 25 to improve the operating speed of the system. Furthermore, through the feature recognition unit 14, the feature value set is input into the pre-stored feature recognition model, and the correlation calculation is performed to determine whether there is an abnormal signal.

[0060] In some embodiments, the scalp electrophysiological monitoring terminal 1 also includes an acquisition unit 11 and a feature extraction unit 13, wherein the acquisition unit 11 is used to acquire scalp electrophysiological signals located on the head through electrodes closely attached to the scalp; the feature extraction unit 13 is used to perform cluster analysis on the scalp electrophysiological signals processed by the filtering unit according to a specific frequency band, and calculate the characteristic value in the specific frequency band as the processing result of the scalp electrophysiological signal; the specific frequency band includes the short-time spectrum energy and change rate of the θ wave with a passband of 3.5-8Hz, the short-time spectrum energy and change rate of the α wave with a passband of 8-12Hz, and the short-time spectrum energy and change rate of the β wave with a passband of 12-33Hz.

[0061] Specifically, refer to Figure 1 As shown, the scalp electrophysiological monitoring terminal 1 includes an acquisition unit 11, a filtering unit 12, a feature extraction unit 13, a feature value set configuration unit 16 and a feature recognition unit 14. The acquisition unit 11 acquires scalp electrophysiological signals and sends them to the filtering unit 12. The scalp electrophysiological monitoring terminal 1 acquires scalp electrophysiological signals through electrodes that are in close contact with the scalp. Preferably, the acquisition location is mainly located at the parietal lobe just above the head and the frontal lobe at the forehead. There is no limitation here. The scalp electrophysiological signals include changes in electrophysiological signals caused by electroencephalographic signals induced by related physiological and psychological activities caused by overactive bladder at the scalp, including changes in electrophysiological signals caused by emotional anxiety, urination sensation and related actions; thereby further improving the accuracy of scalp electrophysiological signal monitoring and recognition.

[0062] The filtering unit 12 performs filtering and Fourier transformation on the scalp electrophysiological signal and sends it to the feature extraction unit 13. The filtering process is to remove interference signals such as high frequency and electrooculogram in the scalp electrophysiological signal that are irrelevant to the target signal, and the low frequency and high frequency are filtered out by a bandpass filter, and the signal in the frequency band of 3Hz to 35Hz is retained. The feature extraction unit 13 performs cluster analysis on the signal processed by the filtering unit 12 according to a specific frequency band, calculates the characteristic value under the specific frequency band, and summarizes it as the processing result of the scalp electrophysiological signal to the characteristic value set configuration unit 16. Further, the specific frequency band for cluster analysis includes the short-time spectrum energy and change rate of the θ wave with a bandpass of 3.5~8Hz, the short-time spectrum energy and change rate of the α wave with a bandpass of 8~12Hz, and the short-time spectrum energy and change rate of the β wave with a bandpass of 12~33Hz. Therefore, the processing result of the scalp electrophysiological signal can be screened by the characteristic value set configuration unit 16 to obtain a characteristic value set, and the correlation calculation is performed by the feature recognition unit 14 to determine whether there is an abnormal signal.

[0063] In addition, the recognition of feature value sets includes but is not limited to the use of various recognition methods such as Bayesian algorithm in machine learning, cluster analysis, neural network classification, etc. The recognition effect can be judged by matching degree, recognition rate and false recognition rate, etc., which will not be elaborated here.

[0064] In some embodiments of the present application, the program-controlled end 2 also includes a raw data storage unit 22 and a signal analysis unit 23. The raw data storage unit 22 is used to receive and display scalp electrophysiological signals, processing results of the scalp electrophysiological signals, and abnormal signal judgment results; the signal analysis unit 23 is used to process the scalp electrophysiological signals to output and display program-controlled processing signals.

[0065] Specifically, continue to refer to Figure 1 As shown, the program-controlled terminal 2 includes a raw data storage unit 22, a signal analysis unit 23, a feature recognition setting unit 24, a feature value set setting unit 25, and a treatment parameter setting unit 26. Furthermore, the program-controlled terminal 2 can be run on electronic devices such as PCs, tablets, or mobile phones. The raw data storage unit 22 is used to receive and display scalp electrophysiological signals and corresponding signal processing results; the signal analysis unit 23 processes the scalp electrophysiological signals and outputs program-controlled processing signals, and displays the program-controlled processing signals, and the signal processing includes filtering and Fourier transform; then, the doctor inputs the corresponding input information into the program-controlled terminal 2 according to the information displayed by the raw data storage unit 22 and the signal analysis unit 23, and then generates the configuration information of the treatment parameters and sends it to the scalp electrophysiological monitoring terminal 1.

[0066] It should be noted that since the filtering process and Fourier transform of the program control terminal 2 are similar to the processing steps of the filtering unit 12 and the feature extraction unit 13 of the scalp electrophysiological monitoring terminal 1, they will not be described in detail here. It can be understood that both the scalp electrophysiological monitoring terminal 1 and the program control terminal 2 can process the collected raw data, and the difference lies in the difference in computing power, that is, the scalp electrophysiological monitoring terminal 1 can only process part of the screened data and identify it to improve the computing speed of the system.

[0067] Furthermore, the program-controlled terminal 2 can display information such as scalp electrophysiological signals, processing results of scalp electrophysiological signals, and program-controlled processing signal results in the form of charts, so as to facilitate doctors to make personalized and accurate configurations for patients. For example, the program-controlled terminal 2 can receive the scalp electrophysiological signal data sent by the scalp electrophysiological monitoring terminal 1 in real time, and display the data in the form of charts in terms of time domain, frequency domain, and time-frequency characteristics. At the same time, its characteristic values ​​are also calculated in a similar manner to the scalp electrophysiological monitoring terminal 1, and displayed in the chart together with the signal processing results of the scalp electrophysiological monitoring terminal 1. With the help of charts and data, doctors can configure individual-specific identification standards for patients in a targeted manner through the characteristic recognition setting unit 24 and the characteristic value set setting unit 25, thereby improving the accuracy of treatment.

[0068] In some embodiments, the programmable terminal 2 also includes a treatment parameter setting unit 26, which is used to respond to the scalp electrophysiological signal, the processing result of the scalp electrophysiological signal and the abnormal signal judgment result, and receive the customized treatment parameters input by the doctor; send the treatment parameters to the tibial nerve electrical stimulation regulation terminal 3, so that after the tibial nerve electrical stimulation regulation is automatically turned on, the patient can achieve on-demand regulation according to the treatment parameters when the symptoms of overactive bladder begin to appear and during the symptoms.

[0069] Furthermore, the scalp electrophysiological monitoring terminal 1 will also send information such as abnormal signal judgment results to the program control terminal 2. The doctor will make a comprehensive judgment based on the information displayed by the program control terminal 2, give corresponding treatment parameters, input the treatment parameters through the treatment parameter setting unit 26, and send the treatment parameters to the tibial nerve electrical stimulation control terminal 3. In this way, the doctor can configure personalized treatment parameters in a targeted manner based on the above displayed information, effectively improving the treatment effect.

[0070] In some preferred embodiments, the treatment parameters obtained by the programming terminal 2 include at least one of the following: stimulation waveform, amplitude, pulse width, frequency, rising cycle, falling cycle, continuous cycle, treatment duration, variable frequency or constant frequency, high frequency, low frequency, voltage or current source.

[0071] In some embodiments, the scalp electrophysiological monitoring terminal 1 further includes a first wireless transmission unit 15, the program-controlled terminal 2 further includes a second wireless transmission unit 21, and the tibial nerve electrical stimulation control terminal 3 further includes a third wireless transmission unit 31. The scalp electrophysiological monitoring terminal 1, the program-controlled terminal 2, and the tibial nerve electrical stimulation control terminal 3 perform wireless transmission through the first wireless transmission unit 15, the second wireless transmission unit 21, and the third wireless transmission unit 31, which can minimize the restrictions on the patient's activities when worn.

[0072] In some embodiments, Figure 1 As shown, the tibial nerve electrical stimulation control terminal 3 also includes an electrical stimulation control unit 32 and a treatment parameter unit 33. The electrical stimulation control unit 32 receives the control instructions of the scalp electrophysiological monitoring terminal 1 through the third wireless transmission unit 31, and the treatment parameter unit 33 obtains the treatment parameters configured by the program control terminal 2, thereby performing tibial nerve electrical stimulation control according to the control instructions and the treatment parameters, and applying corresponding electrical stimulation pulses to the patient.

[0073] From the above, it can be seen that the control process of the closed-loop control system for tibial nerve electrical stimulation of the brain-computer interface of the embodiment of the present application is as follows:

[0074] When monitoring and treatment is required, the patient first wears a scalp electrophysiological monitoring terminal 1 on the head. The scalp electrophysiological monitoring terminal 1 collects scalp electrophysiological signals through electrodes that are close to the scalp, processes the collected signals, and sends the original scalp electrophysiological signals and signal processing results to the program control terminal 2. The program control terminal 2 displays the above information, and analyzes, processes and displays the received scalp electrophysiological signals; the doctor configures appropriate configuration information through the feature recognition setting unit 24 and the feature value set setting unit 25 according to the displayed original data storage unit 22 and the display results of the signal analysis unit 23, and sends it to the scalp electrophysiological monitoring terminal 1. The scalp electrophysiological monitoring terminal 1 determines whether there is an abnormal signal based on the processing results and configuration information of the scalp electrophysiological signals. When an abnormal signal exists, a control instruction is sent to the tibial nerve electrical stimulation control terminal 3. In addition, the scalp electrophysiological monitoring terminal 1 will also send information such as the abnormal signal judgment results to the programming terminal 2. The doctor will then make a comprehensive judgment based on all the information displayed by the programming terminal 2, give corresponding treatment parameters, and input the treatment parameters through the treatment parameter setting unit 26 (the treatment parameters automatically generated or pre-stored by the model can also be obtained). Finally, the treatment parameters are sent to the tibial nerve electrical stimulation control terminal 3 for treatment.

[0075] In some embodiments, the scalp electrophysiological monitoring terminal 1 is also used to extract a first scalp electrophysiological signal characteristic value of the patient under non-overactive bladder conditions when the patient is awake in daily activities and in a semi-asleep state after closing the eyes by wearing the device for a period of time in advance; extract a second scalp electrophysiological characteristic value of the patient under overactive bladder conditions when the patient is awake in daily activities and in a semi-asleep state after closing the eyes; obtain a scalp electrophysiological characteristic set for pre-wearing and use based on the first scalp electrophysiological signal characteristic value and the second scalp electrophysiological characteristic value; compare and analyze the scalp electrophysiological characteristic set for pre-wearing and use with the characteristic value set of the electrophysiological signal monitored during formal wearing and use, and determine whether the requirements for starting electrical stimulation treatment are met, so as to perform personalized pre-configuration for the patient.

[0076] For example, in one embodiment of the present application, the scalp electrophysiological monitoring terminal 1 can directly judge abnormal signals and perform electrical stimulation treatment. The scalp electrophysiological monitoring terminal 1 is pre-configured for patients in a personalized manner to improve the accuracy of treatment. The configuration process is to extract the characteristic values ​​of the patient's scalp electrophysiological signals under non-overactive bladder conditions by wearing the device for a short period of time, including daily activities when awake and semi-sleep states after closing eyes. At the same time, the characteristic values ​​of the patient under overactive bladder are extracted. These characteristic values ​​will each be combined into a set, and compared and analyzed with the characteristic value set of the electrophysiological signal monitored by the device when it is officially used, to determine whether the current situation meets the indications for starting electrical stimulation treatment.

[0077] For another example, in another embodiment of the present application, when monitoring treatment is required, the doctor may also configure the feature recognition model to the scalp electrophysiological monitoring terminal 1 in advance through the feature recognition setting unit 24 according to the patient's clinical condition or the pre-configuration result of the scalp electrophysiological monitoring terminal 1, and configure the feature set configuration information through the feature value set setting unit 25 for pre-configuration. Of course, the above content related to pre-configuration is only an exemplary description and cannot be understood as a limitation to the present application.

[0078] In addition, the scalp electrophysiological monitoring terminal 1 of the embodiment of the present application can be used in conjunction with the programmable terminal 2. Of course, it can also be improved by relevant technical personnel in the field to realize offline use of the scalp electrophysiological monitoring terminal 1; for example, standardized treatment parameters corresponding to relevant symptoms are pre-stored in the scalp electrophysiological monitoring terminal 1, and the tibial nerve electrical stimulation control terminal 3 is regulated by the pre-stored information, which is not limited here.

[0079] In summary, this application has achieved at least the following technical effects:

[0080] First, the brain-computer interface tibial nerve electrical stimulation closed-loop control system of the embodiment of the present application can monitor the patient's scalp electrophysiological signals in real time and automatically identify the signals. If abnormal signals related to overactive bladder such as sensory evoked potentials, emotion evoked potentials and action evoked potentials that may cause urination reactions are found, the tibial nerve electrical stimulation control is turned on to achieve on-demand stimulation and on-demand control during the symptomatic period of overactive bladder, which is smarter and more accurate than traditional open-loop stimulation.

[0081] Second, the brain-computer interface tibial nerve electrical stimulation closed-loop control system of the embodiment of the present application displays scalp electrophysiological signals, signal processing results, abnormal signal judgment results and other display information through the programmable end, so that doctors can configure personalized treatment parameters in a targeted manner according to the above display information and send them to the tibial nerve electrical stimulation control end, thereby improving the accuracy of treatment and effectively alleviating patient symptoms. It is the embodiment of precision medicine.

[0082] It should be noted that in this application, unless otherwise clearly specified and limited, the terms such as "connection" and "fixation" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or communication with each other; it can be a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0083] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0084] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A brain-computer interface tibial nerve electrical stimulation closed-loop control system, wherein: The system comprises: a scalp electrophysiological monitoring terminal, a tibial nerve electrical stimulation control terminal and a program control terminal, wherein the scalp electrophysiological monitoring terminal is connected to the tibial nerve electrical stimulation control terminal, and the program control terminal is connected to the tibial nerve electrical stimulation control terminal. The scalp electrophysiological monitoring terminal is used to Real-time monitoring of scalp electrophysiological signals in a non-invasive manner, and identifying abnormal signals of overactive bladder when the patient has urinary urgency symptoms, wherein the scalp electrophysiological signals can indirectly represent the frequency band associated with overactive bladder when the patient has urinary urgency symptoms; The tibial nerve electrical stimulation control end is used to Responding to the abnormal signal and automatically starting tibial nerve electrical stimulation regulation to achieve on-demand regulation for the patient at the onset of symptoms of overactive bladder and during the symptoms; The program-controlled terminal is used to obtain the treatment parameters related to the on-demand regulation; The system further includes configuration information, wherein the configuration information is configured to be generated by the program control terminal and sent to the scalp electrophysiological monitoring terminal, and the scalp electrophysiological monitoring terminal is also used to Identify whether the abnormal signal exists through the real-time monitored scalp electrophysiological signal and the configuration information, wherein the configuration information at least includes feature set configuration information and a feature recognition model, wherein the feature set configuration information is used to screen the processing result of the scalp electrophysiological signal, and the feature recognition model is used to identify whether the abnormal signal exists according to the processing result of the scalp electrophysiological signal; The tibial nerve electrical stimulation control end is also used to When it is identified that the abnormal signal is restored to a non-abnormal signal of normal bladder activity, the tibial nerve electrical stimulation regulation is automatically turned off in response to the non-abnormal signal and according to a preset delay time; The program control terminal is also used to obtain input information input by the doctor and generate the configuration information according to the input information; The program control end includes a feature recognition setting unit, and the scalp electrophysiological monitoring end includes a feature recognition unit, and the feature recognition setting unit is used to receiving model input information in the input information, generating the feature recognition model according to the model input information, and sending the feature recognition model to the feature recognition unit; The program control end includes a feature value set setting unit, and the scalp electrophysiological monitoring end includes a feature value set configuration unit. The characteristic value set setting unit is used to receiving set input information in the input information, generating the feature set configuration information according to the set input information, and sending the feature set configuration information to the feature value set configuration unit; The characteristic value set configuration unit is used to Filtering the processing result of the scalp electrophysiological signal according to the feature set configuration information, and obtaining a feature value set, wherein the feature value set at least includes feature values ​​of overactive bladder when the patient is in a waking daily activity state, and feature values ​​of overactive bladder when the patient is in a semi-sleep state after closing his eyes; The feature recognition unit is used to The feature value set is identified based on the feature identification model, and it is determined whether there is an abnormal signal.

2. The system of claim 1, wherein: The program-controlled end also includes a raw data storage unit and a signal analysis unit. The raw data storage unit is used to receive and display the scalp electrophysiological signal, the processing result of the scalp electrophysiological signal, and the abnormal signal judgment result; The signal analysis unit is used to process the scalp electrophysiological signal to output and display a program-controlled processed signal.

3. The system of claim 2, wherein: The program control terminal also includes a treatment parameter setting unit, which is used to responding to the scalp electrophysiological signal, the processing result of the scalp electrophysiological signal and the abnormal signal determination result, and receiving the customized treatment parameter input by a doctor; The treatment parameters are sent to the tibial nerve electrical stimulation control terminal, so that after the tibial nerve electrical stimulation control is automatically turned on, the patient can achieve on-demand control according to the treatment parameters when the symptoms of overactive bladder begin to appear and during the symptoms.

4. The system of claim 3, wherein: The treatment parameters acquired by the program control terminal include at least one of the following: stimulation waveform, amplitude, pulse width, frequency, rising cycle, falling cycle, continuous cycle, treatment duration, variable frequency or constant frequency, voltage or current source.

5. The system of claim 1, wherein: The scalp electrophysiological monitoring terminal also includes a collection unit and a feature extraction unit. The collection unit is used to The scalp electrophysiological signals located on the head are collected through electrodes that are closely attached to the scalp; The feature extraction unit is used to The scalp electrophysiological signals processed by the filtering unit are clustered and analyzed according to specific frequency bands, and the characteristic values ​​in the specific frequency bands are calculated as the processing results of the scalp electrophysiological signals; the specific frequency bands include the short-time spectrum energy and change rate of theta waves with a passband of 3.5-8 Hz, the short-time spectrum energy and change rate of alpha waves with a passband of 8-12 Hz, and the short-time spectrum energy and change rate of beta waves with a passband of 12-33 Hz.

6. The system of claim 1, wherein: The scalp electrophysiological monitoring terminal is also used By wearing the device for a period of time in advance, the first scalp electrophysiological signal characteristic value of the patient in the state of awake daily activities and in the semi-sleep state with eyes closed without overactive bladder is extracted; Extract the second scalp electrophysiological characteristic values ​​of patients with overactive bladder during daily activities in the awake state and semi-sleep state with eyes closed; Based on the first scalp electrophysiological signal characteristic value and the second scalp electrophysiological characteristic value, obtaining a scalp electrophysiological characteristic set for pre-wearing use; A comparative analysis is performed based on the scalp electrophysiological feature set during pre-wearing and use and the feature value set of electrophysiological signals monitored during formal wearing and use, and a determination is made as to whether the requirements for starting electrical stimulation therapy are met, so as to perform personalized pre-configuration for the patient.

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