Induction type program control electric guiding method and device

Abstract

The invention discloses an induction type program control electric guiding method and device, and relates to the technical field of medical instruments. According to the inductive program-controlled electric guiding method and device, neural electrophysiological signals of an epilepsy origin area are acquired and detected in an inductive mode, and the neural electrophysiological signals of the epilepsy origin area can be monitored in real time; establishing an epilepsy prediction model based on potential difference characteristics, and calculating an epilepsy identification prediction result according to an epilepsy identification rule; meanwhile, by arranging the subscalp low potential generation module, the stability of the potential difference of the neural electrophysiological signals in the epileptic origin area is achieved, the problems that in-vitro low potential is unstable and the potential difference is not large enough during epileptic seizure are effectively solved, and the treatment effect of epileptic seizure intervention is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to an inductive program-controlled electrical guidance method and device. Background Art

[0002] Electrically guided treatment of epilepsy refers to the use of guiding electrodes made of highly conductive materials and circuit control systems to guide the high voltage (1000-3000uV) generated by local epileptic discharges in the brain to the extracranial area with lower voltage (<100uV), thereby reducing the high voltage of epileptic discharges and avoiding the spread of epileptic discharges, thereby preventing and alleviating the occurrence of clinical symptoms of epilepsy.

[0003] Traditional electrical guidance methods and devices have the function of conducting neural electrophysiological signals out of the body, which is convenient for studying the relationship between current conduction intensity and treatment effect, and preventing and alleviating the occurrence of clinical symptoms of epilepsy. There are several prominent problems: First, the traditional method of adjusting the guidance current by regulating the resistance of the guidance electrode has unsatisfactory actual effect; second, the traditional method of electrical guidance by manual intervention has not formed a closed-loop control method that relies on automatic electrical guidance and intelligent identification by sensors, which is inconvenient and untimely to operate, and the control effect is unsatisfactory; third, electrophysiological signals rely on manual collection, data acquisition is poor in real time, the amount of data is small, and the recording and analysis are cumbersome, which is not conducive to the continuous and in-depth development of epilepsy treatment research; fourth, the traditional method uses the bioelectricity of the scalp surface as the low potential. When epilepsy occurs, the bioelectricity of the scalp surface is unstable, causing epilepsy monitoring and intervention disorders.

[0004] There is an urgent need to develop inductive and programmable electrical guidance methods and devices. Summary of the invention

[0005] The object of the present invention is to provide an inductive programmable electrical guidance method and device for solving at least part of the above-mentioned problems in the derivation of neuro-electrophysiological signals from the traditional epilepsy origin area.

[0006] The present invention provides the following technical solutions:

[0007] The present invention provides an inductive program-controlled electrical guidance method for stably deriving neuroelectrophysiological signals from an epileptic origin area. The inductive program-controlled electrical guidance method comprises:

[0008] S1. Obtaining neuroelectrophysiological signals from the epileptic origin area;

[0009] S2, calculating the potential difference characteristics of the neural electrophysiological signal;

[0010] S3, calculating epilepsy recognition prediction results based on the potential difference characteristics of neuroelectrophysiological signals;

[0011] S4. When the epilepsy identification prediction result does not show an epileptic seizure, obtain the external program control connection state. If it is in the program control connection state and the working parameter data is obtained, correct the system operation parameters and return to S1; if it is not in the program control connection state, return to S1;

[0012] S5. When the epilepsy identification result shows an epileptic seizure, start the low potential, establish the potential difference between the epilepsy origin area and the low potential electrode, and form a guiding current; wait for the guiding time setting value to end, terminate the low potential, and return to S1.

[0013] Optionally, the step of acquiring the neuroelectrophysiological signal of the epilepsy origin area in S1 includes:

[0014] Setting up nerve electrophysiological signal guiding electrodes in the epileptic origin area;

[0015] The potential difference of the monitoring guide electrode is the neurophysiological signal of the epileptic origin area.

[0016] Optionally, the step S2 calculates the potential difference feature of the neural electrophysiological signal, including:

[0017] Extract the potential difference features from neural electrophysiological signals;

[0018] The potential difference characteristics are not limited to the size, frequency, and time width of the potential difference.

[0019] Optionally, the step S3 calculates the epilepsy recognition prediction result based on the potential difference feature of the neuroelectrophysiological signal, including:

[0020] The potential difference feature of the neuroelectrophysiological signal is input into an epilepsy prediction model based on the potential difference feature to obtain a recognition result.

[0021] Optionally, the step of inputting the potential difference feature of the neuroelectrophysiological signal into an epilepsy prediction model based on the potential difference feature to obtain a recognition result includes:

[0022] inputting the potential difference feature into an epilepsy prediction model based on the potential difference feature;

[0023] The epilepsy prediction model based on potential difference features is based on epilepsy recognition rules and outputs epilepsy recognition prediction results.

[0024] Optionally, the step of establishing the epilepsy prediction model based on potential difference characteristics includes:

[0025] Summarize the laws and relationships between neuroelectrophysiological signal characteristics and clinical epileptic seizures, wherein the neuroelectrophysiological signal characteristics are not limited to the magnitude, frequency, and time width of the potential difference;

[0026] The machine learning method is used to train the big data of neurophysiological signals of historical epileptic seizures to form an epilepsy recognition model;

[0027] The epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is:

[0028] Epilepsy identification rule 1: collect neuroelectrophysiological signals. When the potential difference is higher than the potential difference setting value and the number of consecutive occurrences is greater than the number of setting values, it is judged as positive and regarded as an epileptic seizure.

[0029] Optionally, the potential difference setting value is 100uV-500uV; Optionally, the number setting value is 10 times;

[0030] Optionally, the epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is:

[0031] Epilepsy recognition rule 2, feature matching of the collected neuroelectrophysiological signal potential difference feature with the neuroelectrophysiological signal potential difference feature of the epilepsy recognition model, when the matching degree is higher than the matching degree threshold, it is judged as positive and regarded as an epileptic seizure; optionally, the matching degree threshold is 80%;

[0032] Optionally, the above-mentioned epilepsy identification rule 1 and / or one or more epilepsy identification rules 2 are selected and combined according to clinical experience, and the probability of epilepsy occurrence is calculated by weighted average method to improve the accuracy of epilepsy diagnosis;

[0033] Optionally, the boot time setting value in S5 is 0.1 second.

[0034] The present application also provides an inductive program-controlled electric guidance device for stably deriving neuroelectrophysiological signals from an epileptic origin area, characterized in that the inductive program-controlled electric guidance device comprises:

[0035] An electric guidance device body, an in vitro programmable control module, at least one guiding electrode terminal, at least one guiding electrode connecting wire, and at least one guiding electrode; the guiding electrode is connected to the guiding electrode terminal through the guiding electrode connecting wire, and is used to guide the neural electrophysiological signal to the electric guidance device body; the number of the guiding electrode connecting wires and the guiding electrodes is consistent with the number of epilepsy origin areas to be guided.

[0036] Optionally, the inductive programmable electric guiding device may further include a soft cover for the guiding electrode terminal, which is used to insulate and seal the guiding electrode terminal when the guiding electrode terminal is not fully used.

[0037] Optionally, the main body of the electric guidance device includes: an electric signal acquisition module, a core processing control module, a wireless communication and energy transmission module, a low potential generation module, and a battery module; the main body of the electric guidance device is set under the scalp when used;

[0038] The electrical signal acquisition module is connected to the guiding electrode terminal and is used to collect the neurophysiological signals of the epilepsy origin area and output the neurophysiological signals to the core processing control module; the number of the electrical signal acquisition modules is the same as the number of the guiding electrode terminal and they are connected accordingly;

[0039] The core processing control module is used to receive the neuroelectrophysiological signal of the epilepsy origin area output by the electrical signal acquisition module, and perform small signal amplification, filtering, and AD conversion on the neuroelectrophysiological signal, and input the digital signal into the microprocessor to perform potential difference calculation and feature extraction; the core processing control module adopts an epilepsy prediction model based on potential difference characteristics, and predicts epileptic seizures based on the potential difference characteristics. If epileptic seizures occur, the core processing control module sends a low potential start instruction to the low potential generation module to establish a current path from the guide electrode to the low potential electrode; if epileptic seizures do not occur, the core processing control module stops sending the low potential start instruction to the low potential generation module, and disconnects the current path from the guide electrode to the low potential electrode; the steps of establishing the epilepsy prediction model based on potential difference characteristics include:

[0040] Summarize the laws and relationships between neuroelectrophysiological signal characteristics and clinical epileptic seizures, wherein the neuroelectrophysiological signal characteristics are not limited to the magnitude, frequency, and time width of the potential difference E;

[0041] The machine learning method is used to train the big data of neurophysiological signals of historical epileptic seizures to form an epilepsy recognition model;

[0042] The epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is:

[0043] Epilepsy identification rule 1: collect neuroelectrophysiological signals. When the potential difference is higher than the potential difference setting value and the number of consecutive occurrences is greater than the number of setting values, it is judged as positive and regarded as an epileptic seizure.

[0044] Optionally, the potential difference setting value is 100uV-500uV; Optionally, the number setting value is 10 times;

[0045] Optionally, the epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is:

[0046] Epilepsy recognition rule 2, feature matching of the collected neuroelectrophysiological signal potential difference feature with the neuroelectrophysiological signal potential difference feature of the epilepsy recognition model, when the matching degree is higher than the matching degree threshold, it is judged as positive and regarded as an epileptic seizure; optionally, the matching degree threshold is 80%;

[0047] Optionally, the above-mentioned epilepsy identification rule 1 and / or one or more epilepsy identification rules 2 are selected and combined according to clinical experience, and the probability of epilepsy occurrence is calculated by weighted average method to improve the accuracy of epilepsy diagnosis;

[0048] The wireless communication and energy transmission module is used to establish information communication and energy transmission with the external program control module. On the one hand, the wireless communication and energy transmission module obtains the working parameters input by the external program control module by wireless transmission; the working parameters are not limited to the monitoring frequency of the neuroelectrophysiological signal, the low potential value of different guiding electrode pathways, the potential difference setting value, and the number of setting values; the output data of the core processing control module is sent to the external program control module, and the output data of the core processing control module is not limited to the terminal number of the collected neuroelectrophysiological signal and the potential difference characteristics of the neuroelectrophysiological signal; on the other hand, the wireless communication and energy transmission module establishes a wireless power transmission connection with the external program control module, and stores the acquired electric energy in the battery module to realize wireless power transmission charging;

[0049] The low potential generating module is provided with a low potential electrode sheet on the outside, and the low potential electrode sheet is connected to the guiding electrode terminal; the low potential generating module is used to receive the low potential start instruction issued by the core processing control module, and when the low potential generating module receives the low potential start instruction, the low potential generated by the module is connected to the low potential electrode sheet, thereby establishing a stable neuroelectrophysiological signal potential difference between the guiding electrode and the low potential electrode sheet, and realizing current guidance; when the low potential generating module does not receive the low potential start instruction, the low potential generated by the module is disconnected from the low potential electrode sheet, and the neuroelectrophysiological signal monitoring state of the epilepsy origin area of ​​the guiding device body is restored; the number of the low potential generating modules is the same as the number of the guiding electrode terminal, and they are connected accordingly;

[0050] The battery module is used to store the electric energy obtained by the wireless communication and energy transmission module from the external programmable control module, and to provide the electric energy required for the operation of other modules of the electric guidance device body.

[0051] Optionally, the extracorporeal programmable control module includes an information communication module and a wireless power output module; the information communication module is used to transmit working parameters to the wireless communication and energy transmission module of the electric guidance device body, and obtain the output data of the core processing control module, and send it to the computer for data storage and analysis; the wireless power output module is used to transmit electric energy to the wireless communication and energy transmission module of the electric guidance device body to realize charging of the battery module of the guidance device body.

[0052] The present invention provides an inductive programmable electrical guidance method and device. Firstly, the neuroelectrophysiological signals of the epilepsy origin area are inductively monitored through an electrical signal acquisition module and a guiding electrode, thereby realizing real-time monitoring of the neuroelectrophysiological signals of the epilepsy origin area. Secondly, an epilepsy prediction model based on potential difference characteristics of a core processing control module is integrated with one or more epilepsy recognition rules, thereby effectively improving the rapidity and accuracy of epileptic seizure judgment and providing a prerequisite for subsequent epilepsy intervention. Thirdly, a stable low potential is generated through a low potential generation module, thereby establishing a stable neuroelectrophysiological signal potential difference between the guiding electrode and the low potential electrode sheet, thereby effectively solving the problem of instability of the external low potential during epileptic seizures and greatly improving the therapeutic effect of epileptic seizure intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a flow chart of an inductive program-controlled electric guidance method in one embodiment of the present application;

[0054] Figure 2 is a schematic structural diagram of an inductive program-controlled electric guidance device in one embodiment of the present application;

[0055] Figure 3 is a schematic diagram of the internal module connection of the guiding device body in one embodiment of the present application;

[0056] The names of the parts corresponding to the numbers in the figure are: 1-electric guidance device body, 2-guiding electrode terminal, 3-guiding electrode connecting wire, 4-guiding electrode, 5-guiding electrode terminal soft cover, 6-in vitro program control module, 6-in vitro program control module, 7-electric signal acquisition module, 8-core processing control module, 9-wireless communication and energy transmission module, 10-low potential generation module, 101-low potential electrode sheet, 11-battery module. DETAILED DESCRIPTION

[0057] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] Figure 1 It is a flow chart of the inductive program-controlled electric guidance method in one embodiment of the present application.

[0059] like Figure 1 The inductive programmable electric guidance method shown includes:

[0060] S1. Obtaining neuroelectrophysiological signals from the epileptic origin area;

[0061] S2, calculating the potential difference characteristics of the neural electrophysiological signal;

[0062] S3, calculating epilepsy recognition prediction results based on the potential difference characteristics of neuroelectrophysiological signals;

[0063] S4. When the epilepsy identification prediction result does not show an epileptic seizure, obtain the external program control connection state. If it is in the program control connection state and the working parameter data is obtained, correct the system operation parameters and return to S1; if it is not in the program control connection state, return to S1;

[0064] S5. When the epilepsy identification result shows an epileptic seizure, start the low potential, establish the potential difference between the epilepsy origin area and the low potential electrode, and form a guiding current; wait for the guiding time setting value to end, terminate the low potential, and return to S1.

[0065] See also Figure 1 , in this embodiment,

[0066] The S1 acquires the neurophysiological signal of the epilepsy origin area, including:

[0067] Setting up nerve electrophysiological signal guiding electrodes in the epileptic origin area;

[0068] The potential difference of the monitoring guide electrode is the neurophysiological signal of the epileptic origin area.

[0069] Optionally, the step S2 calculates the potential difference feature of the neural electrophysiological signal, including:

[0070] Extract the potential difference features from neural electrophysiological signals;

[0071] The potential difference characteristics are not limited to the size, frequency, and time width of the potential difference.

[0072] See also Figure 1 In this embodiment, the S3 calculates the epilepsy recognition prediction result based on the potential difference feature of the neuroelectrophysiological signal, including:

[0073] The potential difference feature of the neuroelectrophysiological signal is input into an epilepsy prediction model based on the potential difference feature to obtain a recognition result.

[0074] Optionally, the step of inputting the potential difference feature of the neuroelectrophysiological signal into an epilepsy prediction model based on the potential difference feature to obtain a recognition result includes:

[0075] inputting the potential difference feature into an epilepsy prediction model based on the potential difference feature;

[0076] The epilepsy prediction model based on potential difference features is based on epilepsy recognition rules and outputs epilepsy recognition prediction results.

[0077] Optionally, the step of establishing the epilepsy prediction model based on potential difference characteristics includes:

[0078] Summarize the laws and relationships between neuroelectrophysiological signal characteristics and clinical epileptic seizures, wherein the neuroelectrophysiological signal characteristics are not limited to the magnitude, frequency, and time width of the potential difference;

[0079] The machine learning method is used to train the big data of neurophysiological signals of historical epileptic seizures to form an epilepsy recognition model;

[0080] The epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is:

[0081] Epilepsy identification rule 1: collect neuroelectrophysiological signals. When the potential difference is higher than the potential difference setting value and the number of consecutive occurrences is greater than the number of setting values, it is judged as positive and regarded as an epileptic seizure.

[0082] Optionally, the potential difference setting value is 100uV-500uV; Optionally, the number setting value is 10 times;

[0083] Optionally, the epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is:

[0084] Epilepsy recognition rule 2, feature matching of the collected neuroelectrophysiological signal potential difference feature with the neuroelectrophysiological signal potential difference feature of the epilepsy recognition model, when the matching degree is higher than the matching degree threshold, it is judged as positive and regarded as an epileptic seizure; optionally, the matching degree threshold is 80%;

[0085] Optionally, the above-mentioned epilepsy identification rule 1 and / or one or more epilepsy identification rules 2 are selected and combined according to clinical experience, and the probability of epilepsy occurrence is calculated by weighted average method to improve the accuracy of epilepsy diagnosis;

[0086] See also Figure 1 In this embodiment, optionally, the boot time setting value in S5 is 0.1 seconds.

[0087] Figure 2 is a schematic structural diagram of an inductive program-controlled electric guidance device in one embodiment of the present application;

[0088] like Figure 2 The inductive programmable electric guidance device shown includes:

[0089] An electric guidance device body 1, an in vitro programmable control module 6, at least one guiding electrode terminal 2, at least one guiding electrode connecting wire 3, and at least one guiding electrode 4; the guiding electrode 4 is connected to the guiding electrode terminal 2 via the guiding electrode connecting wire 3, and is used to guide the neuro-electrophysiological signal to the electric guidance device body 1; the number of the guiding electrode connecting wires 3 and the guiding electrodes 4 is consistent with the number of epilepsy origin areas to be guided.

[0090] Optionally, the inductive programmable electric guiding device may further include a guiding electrode terminal soft cover 5, which is used to insulate and seal the guiding electrode terminal 2 when the guiding electrode terminal 2 is not fully used.

[0091] Figure 3 It is a schematic diagram of the internal module connection of the guiding device body in one embodiment of the present application.

[0092] like Figure 3 As shown, the present application also discloses that the main body 1 of the electric guidance device includes: an electric signal acquisition module 7, a core processing control module 8, a wireless communication and energy transmission module 9, a low potential generation module 10, and a battery module 11; the main body 1 of the electric guidance device is set under the scalp when used;

[0093] The electric signal acquisition module 7 is connected to the guiding electrode terminal 2, and is used to collect the neuro-electrophysiological signal of the epilepsy origin area, and output the neuro-electrophysiological signal to the core processing control module 8; the number of the electric signal acquisition modules 7 is the same as the number of the guiding electrode terminal 2, and they are connected accordingly;

[0094] The core processing control module 8 is used to receive the neuroelectrophysiological signal of the epilepsy origin area output by the electrical signal acquisition module 7, and perform small signal amplification, filtering, and AD conversion on the neuroelectrophysiological signal, and input the digital signal into the microprocessor to perform potential difference calculation and feature extraction; the core processing control module 8 adopts an epilepsy prediction model based on potential difference characteristics, and predicts epileptic seizures based on potential difference characteristics. If epileptic seizures occur, the core processing control module 8 sends a low potential start instruction to the low potential generation module 10 to establish a current path from the guide electrode 4 to the low potential electrode; if epilepsy does not occur, the core processing control module 8 stops sending the low potential start instruction to the low potential generation module 10, and disconnects the current path from the guide electrode 4 to the low potential electrode; the steps of establishing the epilepsy prediction model based on potential difference characteristics include:

[0095] Summarize the laws and relationships between neuroelectrophysiological signal characteristics and clinical epileptic seizures, wherein the neuroelectrophysiological signal characteristics are not limited to the magnitude, frequency, and time width of the potential difference E;

[0096] The machine learning method is used to train the big data of neurophysiological signals of historical epileptic seizures to form an epilepsy recognition model;

[0097] The epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is:

[0098] Epilepsy identification rule 1: collect neuroelectrophysiological signals. When the potential difference is higher than the potential difference setting value and the number of consecutive occurrences is greater than the number of setting values, it is judged as positive and regarded as an epileptic seizure.

[0099] Optionally, the potential difference setting value is 100uV-500uV; Optionally, the number setting value is 10 times;

[0100] Optionally, the epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is:

[0101] Epilepsy recognition rule 2, feature matching of the collected neuroelectrophysiological signal potential difference feature with the neuroelectrophysiological signal potential difference feature of the epilepsy recognition model, when the matching degree is higher than the matching degree threshold, it is judged as positive and regarded as an epileptic seizure; optionally, the matching degree threshold is 80%;

[0102] Optionally, the above-mentioned epilepsy identification rule 1 and / or one or more epilepsy identification rules 2 are selected and combined according to clinical experience, and the probability of epilepsy occurrence is calculated by weighted average method to improve the accuracy of epilepsy diagnosis;

[0103] The wireless communication and energy transmission module 9 is used to establish information communication and energy transmission with the external program control module 6. On the one hand, the wireless communication and energy transmission module 9 obtains the working parameters input by the external program control module 6 by wireless transmission; the working parameters are not limited to the monitoring frequency of the neuroelectrophysiological signal, the low potential value of different guiding electrode pathways, the potential difference setting value, and the number of setting values; the output data of the core processing control module 8 is sent to the external program control module 6, and the output data of the core processing control module 8 is not limited to the terminal number of the collected neuroelectrophysiological signal and the potential difference characteristics of the neuroelectrophysiological signal; on the other hand, the wireless communication and energy transmission module 9 establishes a wireless energy transmission connection with the external program control module 6, and stores the acquired electric energy in the battery module 11 to realize wireless energy transmission charging;

[0104] The low potential generating module 10 is provided with a low potential electrode sheet 101 on the outside, and the low potential electrode sheet 101 is connected to the guiding electrode terminal 2; the low potential generating module 10 is used to receive the low potential start instruction issued by the core processing control module 8, and when the low potential generating module 10 receives the low potential start instruction, the low potential generated by the module is connected to the low potential electrode sheet 101, thereby establishing a stable neuro-electrophysiological signal potential difference between the guiding electrode 4 and the low potential electrode sheet 101, and realizing current guidance; when the low potential generating module 10 does not receive the low potential start instruction, the low potential generated by the module is disconnected from the low potential electrode sheet 101, and the state of neuro-electrophysiological signal monitoring of the epilepsy origin area of ​​the guiding device body is restored; the number of the low potential generating modules 10 is the same as the number of the guiding electrode terminal 2, and they are connected accordingly;

[0105] The battery module 11 is used to store the electric energy obtained by the wireless communication and energy transmission module 9 from the external program control module 6, and to provide the electric energy required for the operation of other modules of the electric guidance device body 1.

[0106] Optionally, the extracorporeal programmable control module 6 includes an information communication module and a wireless power output module; the information communication module is used to transmit working parameters to the wireless communication and energy transmission module 9 of the electric guidance device body 1, and obtain the output data of the core processing control module 8, and send it to the computer for data storage and analysis; the wireless power output module is used to transmit electric energy to the wireless communication and energy transmission module 9 of the electric guidance device body 1, so as to realize charging of the battery module 11 of the guidance device body.

[0107] For the convenience of description, the above devices are described in modules according to their functions. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0108] Those skilled in the art will appreciate that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined.

[0109] For the method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An inductive programmable electric guidance method for stably deriving neurophysiological signals from the epilepsy origin area, characterized in that: The inductive program-controlled electric guidance method comprises: S1. Obtaining neuroelectrophysiological signals from the epileptic origin area; S2, calculating the potential difference characteristics of the neural electrophysiological signal; S3, calculating epilepsy recognition prediction results based on the potential difference characteristics of neuroelectrophysiological signals; S4. When the epilepsy identification prediction result does not show an epileptic seizure, obtain the external program control connection state. If it is in the program control connection state and the working parameter data is obtained, correct the system operation parameters and return to S1; if it is not in the program control connection state, return to S1; S5. When the epilepsy identification result shows an epileptic seizure, start the low potential, establish the potential difference between the epilepsy origin area and the low potential electrode, and form a guiding current; wait for the guiding time setting value to end, terminate the low potential, and return to S1.

2. The inductive program-controlled electric guidance method according to claim 1, characterized in that: The S1 acquires the neurophysiological signal of the epilepsy origin area, including: Setting up nerve electrophysiological signal guiding electrodes in the epileptic origin area; Monitor the potential difference of the guiding electrode, which is the neurophysiological signal of the epileptic origin area; The S2 calculates the potential difference characteristics of the neural electrophysiological signal, including: Extract the potential difference features from neural electrophysiological signals; The potential difference characteristics are not limited to the size, frequency, and time width of the potential difference.

3. The inductive program-controlled electric guidance method according to claim 1, characterized in that: The S3 calculates the epilepsy recognition prediction result based on the potential difference characteristics of the neuroelectrophysiological signal, including: Inputting the potential difference feature of the neuroelectrophysiological signal into an epilepsy prediction model based on the potential difference feature to obtain a recognition result; The step of inputting the potential difference feature of the neuroelectrophysiological signal into an epilepsy prediction model based on the potential difference feature to obtain a recognition result includes: inputting the potential difference feature into an epilepsy prediction model based on the potential difference feature; The epilepsy prediction model based on potential difference features is based on epilepsy recognition rules and outputs epilepsy recognition prediction results; The steps of establishing the epilepsy prediction model based on potential difference characteristics include: Summarize the laws and relationships between neuroelectrophysiological signal characteristics and clinical epileptic seizures, wherein the neuroelectrophysiological signal characteristics are not limited to the magnitude, frequency, and time width of the potential difference; The machine learning method is used to train the big data of neurophysiological signals of historical epileptic seizures to form an epilepsy recognition model; The epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is: Epilepsy identification rule 1: collect neuroelectrophysiological signals. When the potential difference is higher than the potential difference setting value and the number of consecutive occurrences is greater than the number of setting values, it is judged as positive and regarded as an epileptic seizure. The potential difference setting value is 100uV-500uV; the number setting value is 10 times; The epilepsy recognition rules used by the epilepsy prediction model based on potential difference characteristics are: Epilepsy recognition rule 2, feature matching is performed on the collected neuroelectrophysiological signal potential difference feature and the neuroelectrophysiological signal potential difference feature of the epilepsy recognition model. When the matching degree is higher than the matching degree threshold, it is judged as positive and regarded as an epileptic seizure; the matching degree threshold is 80%; Based on clinical experience, the above-mentioned epilepsy identification rule 1 and / or one or more epilepsy identification rules 2 are selected for combination, and the probability of epilepsy occurrence is calculated using a weighted average method to improve the accuracy of epilepsy diagnosis.

4. The inductive program-controlled electric guidance method according to claim 1, characterized in that: The guide time setting value in S5 is 0.1 second.

5. An inductive program-controlled electric guidance device for stably deriving neurophysiological signals from the epilepsy origin area, characterized in that: The inductive program-controlled electric guidance device comprises: An electric guidance device body, an in vitro programmable control module, at least one guiding electrode terminal, at least one guiding electrode connecting wire, and at least one guiding electrode; the guiding electrode is connected to the guiding electrode terminal through the guiding electrode connecting wire, and is used to guide the neural electrophysiological signal to the electric guidance device body; the number of the guiding electrode connecting wires and the guiding electrodes is consistent with the number of epilepsy origin areas to be guided.

6. The inductive program-controlled electric guidance device according to claim 5, characterized in that: The inductive program-controlled electric guiding device also includes a soft cover for the guiding electrode terminal, which is used to insulate and seal the guiding electrode terminal when the guiding electrode terminal is not fully used.

7. The inductive program-controlled electric guidance device according to claim 5, characterized in that: The main body of the electric guidance device includes: an electric signal acquisition module, a core processing control module, a wireless communication and energy transmission module, a low potential generation module, and a battery module; the main body of the electric guidance device is set under the scalp when used.

8. The inductive program-controlled electric guidance device according to claim 7, characterized in that: The electrical signal acquisition module is connected to the guide electrode terminal, and is used to acquire the neuro-electrophysiological signals of the epilepsy origin area, and output the neuro-electrophysiological signals to the core processing control module; The number of the electrical signal acquisition modules is the same as the number of the guide electrode wiring terminals, and they are connected correspondingly; The core processing control module is used to receive the neuroelectrophysiological signal of the epilepsy origin area output by the electrical signal acquisition module, and perform small signal amplification, filtering, and AD conversion on the neuroelectrophysiological signal, and input the digital signal into the microprocessor to perform potential difference calculation and feature extraction; the core processing control module adopts an epilepsy prediction model based on potential difference characteristics, and predicts epileptic seizures based on the potential difference characteristics. If an epileptic seizure occurs, the core processing control module sends a low potential start instruction to the low potential generation module to establish a current path from the guide electrode to the low potential electrode; If the epileptic seizure does not occur, the core processing control module stops sending the low potential start instruction to the low potential generation module, and disconnects the current path from the guide electrode to the low potential electrode; The step of establishing an epilepsy prediction model based on potential difference characteristics comprises: Summarize the laws and relationships between the characteristics of neuroelectrophysiological signals and clinical epileptic seizures, wherein the characteristics of neuroelectrophysiological signals are not limited to the magnitude, frequency, and time width of the potential difference E; The machine learning method is used to train the big data of neurophysiological signals of historical epileptic seizures to form an epilepsy recognition model; The epilepsy recognition rule adopted by the epilepsy prediction model based on potential difference characteristics is: Epilepsy identification rule 1: collect neuroelectrophysiological signals. When the potential difference is higher than the potential difference setting value and the number of consecutive occurrences is greater than the number of setting values, it is judged as positive and regarded as an epileptic seizure. Epilepsy recognition rule 2: feature matching is performed between the collected neuroelectrophysiological signal potential difference feature and the neuroelectrophysiological signal potential difference feature of the epilepsy recognition model. When the matching degree is higher than the matching degree threshold, it is judged as positive and regarded as an epileptic seizure. According to clinical experience, the above-mentioned epilepsy identification rule 1 and / or one or more epilepsy identification rules 2 are selected and combined, and the probability of epilepsy occurrence is calculated by weighted average method to improve the accuracy of epilepsy diagnosis; The wireless communication and energy transmission module is used to establish information communication and energy transmission with the external program control module. On the one hand, the wireless communication and energy transmission module obtains the working parameters input by the external program control module by wireless transmission; the working parameters are not limited to the monitoring frequency of the neuroelectrophysiological signal, the low potential value of different guiding electrode pathways, the potential difference setting value, and the number of setting values; the output data of the core processing control module is sent to the external program control module, and the output data of the core processing control module is not limited to the terminal number of the collected neuroelectrophysiological signal and the potential difference characteristics of the neuroelectrophysiological signal; on the other hand, the wireless communication and energy transmission module establishes a wireless power transmission connection with the external program control module, and stores the acquired electric energy in the battery module to realize wireless power transmission charging; The low potential generating module is provided with a low potential electrode sheet on the outside, and the low potential electrode sheet is connected to the guiding electrode terminal; the low potential generating module is used to receive the low potential start instruction issued by the core processing control module, and when the low potential generating module receives the low potential start instruction, the low potential generated by the module is connected to the low potential electrode sheet, thereby establishing a stable neuroelectrophysiological signal potential difference between the guiding electrode and the low potential electrode sheet, and realizing current guidance; when the low potential generating module does not receive the low potential start instruction, the low potential generated by the module is disconnected from the low potential electrode sheet, and the neuroelectrophysiological signal monitoring state of the epilepsy origin area of ​​the guiding device body is restored; the number of the low potential generating modules is the same as the number of the guiding electrode terminal, and they are connected accordingly; The battery module is used to store the electric energy obtained by the wireless communication and energy transmission module from the external programmable control module, and to provide the electric energy required for the operation of other modules of the electric guidance device body.

9. The inductive program-controlled electric guidance device according to claim 5, characterized in that: The in vitro programmable control module includes an information communication module and a wireless power output module; the information communication module is used to transmit working parameters to the wireless communication and energy transmission module of the electric guidance device body, and obtain the output data of the core processing control module, and send it to the computer for data storage and analysis; the wireless power output module is used to transmit electric energy to the wireless communication and energy transmission module of the electric guidance device body to realize charging of the battery module of the guidance device body.

10. The inductive program-controlled electric guidance device according to claim 8, characterized in that: The potential difference setting value is 100uV-500uV, the number setting value is 10 times, and the matching degree threshold is 80%.

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