Current stimulation parameter control device and electronic equipment

Abstract

The present invention discloses a current stimulation parameter control device and an electronic device, the device comprising: an acquisition unit and a processing unit; determining a first current stimulation parameter corresponding to an electroencephalogram signal at a preset position of a target object and a preset brain working state; performing electrical stimulation at a preset position of the target object according to the first current stimulation parameter by a transcranial electrical stimulation device; determining the corresponding first potential change data by an electroencephalogram device; determining a target error value between the preset potential change data and the first potential change data; when the target error value is greater than the preset error value, adjusting the first current stimulation parameter based on the target error value to obtain a target current stimulation parameter; performing electrical stimulation at a preset position of the target object according to the target current stimulation parameter by a transcranial electrical stimulation device, so that the preset position enters a preset brain working state. By adopting the embodiments of the present application, the current stimulation parameters can be precisely controlled to put the brain in an expected working state.

Description

Technical Field

[0001] The present invention relates to the field of nerve regulation technology, and in particular to a current stimulation parameter regulation device and electronic equipment. Background Art

[0002] In the process of studying the brain, people will use various technical means to intervene in brain activities and change the brain's working state.

[0003] Currently, the brain's working state can be changed by applying electrical stimulation to the human scalp through a transcranial electrical stimulation device. However, this method has certain shortcomings and often fails to achieve the expected effect. The brain's working state is still different from the expected working state, so how to accurately control the current stimulation parameters to keep the brain in the expected working state is a problem to be solved. Summary of the invention

[0004] The embodiments of the present application provide a current stimulation parameter control device and an electronic device, which determine the first potential change data corresponding to the EEG signal at a preset position through an electroencephalogram device, and then determine the target error value between the preset potential change data and the first potential change data. When the target error value is greater than the preset error value, the current stimulation parameters of the transcranial electrical stimulation device when performing electrical stimulation on the target object are adjusted based on the target error value, thereby achieving precise control of the current stimulation parameters and putting the brain in an expected working state.

[0005] In a first aspect, an embodiment of the present application provides a current stimulation parameter control device, which is applied to a controller of a neural regulation system, wherein the neural regulation system further includes: a transcranial electrical stimulation device and an electroencephalogram device; the current stimulation parameter control device includes: an acquisition unit and a processing unit;

[0006] An acquisition unit, used for acquiring an electroencephalogram signal of a preset position of a target object through an electroencephalogram device;

[0007] A processing unit, used to determine a current stimulation parameter corresponding to the EEG signal and a preset brain working state, and obtain a first current stimulation parameter;

[0008] Performing electrical stimulation at a preset position of the target object according to a first current stimulation parameter by a transcranial electrical stimulation device;

[0009] Determine the electric potential change data corresponding to the electroencephalogram signal at the preset position by an electroencephalogram device to obtain first electric potential change data;

[0010] An acquisition unit, used for acquiring preset electric potential change data of a preset position of a target object for a preset brain working state;

[0011] a processing unit, configured to determine an error value between the preset potential change data and the first potential change data, and obtain a target error value;

[0012] When the target error value is greater than the preset error value, adjusting the first current stimulation parameter based on the target error value to obtain the target current stimulation parameter;

[0013] Electrical stimulation is performed at a preset position of the target object according to target current stimulation parameters through a transcranial electrical stimulation device, so that the preset position enters a preset brain working state.

[0014] In a second aspect, an embodiment of the present invention provides an electronic device, comprising: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor so that the electronic device executes the method of the first aspect.

[0015] The implementation of the present invention has the following beneficial effects:

[0016] It can be seen that the current stimulation parameter control device described in the embodiment of the present invention is applied to the controller of the neural regulation system, and the neural regulation system also includes: a transcranial electrical stimulation device and an electroencephalogram device. First, the EEG signal of the preset position of the target object is obtained, and the first current stimulation parameter corresponding to the EEG signal and the preset brain working state is determined. Then, the transcranial electrical stimulation device is used to perform electrical stimulation at the preset position of the target object according to the first current stimulation parameter. Then, the electroencephalogram device is used to determine the first electric potential change data corresponding to the EEG signal at the preset position, and at the same time, the preset electric potential change data corresponding to the preset brain working state is obtained. Then, the preset electric potential change data and the first electric potential change data are fitted respectively to obtain two corresponding fitted data. A straight line is formed, and the error value between the preset potential change data and the first potential change data is determined by the difference in the slopes of the two straight lines. When the slope of the two straight lines is greater than the preset slope threshold, n potential values ​​in the first potential change data are determined, and then the n potential values ​​are divided into different intervals, and different weights are assigned to each interval. A weighted operation is performed based on the weight of each interval to obtain a target deviation parameter, and then the difference in the slopes of the two straight lines is adjusted by the target deviation parameter to determine the error value between the preset potential change data and the first potential change data. Finally, the first current stimulation parameter is adjusted based on the target error value to obtain the target current stimulation parameter, so that the preset position enters the preset brain working state. The implementation mode of the present invention is used to achieve precise control of the current stimulation parameters and put the brain in the expected working state. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the implementation methods of the present application or the background technology, the drawings required for use in the implementation methods of the present application or the background technology will be described below.

[0018] Figure 1 It is a schematic diagram of the structure of a neural regulation system provided in an embodiment of the present application;

[0019] Figure 2 It is a flow chart of a method for regulating current stimulation parameters provided in an embodiment of the present application;

[0020] Figure 3 is a flow chart for determining a target error value provided by an embodiment of the present application;

[0021] Figure 4 It is a structural schematic diagram of a current stimulation parameter control device provided in an embodiment of the present application;

[0022] Figure 5 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the implementation mode of the present application will be clearly and completely described below in conjunction with the drawings in the implementation mode of the present application. Obviously, the described implementation mode is only a part of the implementation mode of the present application, not all the implementation modes. Based on the implementation mode in the present application, all other implementation modes obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0024] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0025] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0026] See also Figure 1 , Figure 1 is a schematic diagram of the structure of a neural regulation system provided in an embodiment of the present application, such as Figure 1 As shown, the neuroregulatory system 10 includes a controller 101 , a transcranial electrical stimulation device 102 and an electroencephalogram device 103 .

[0027] In this embodiment, the neuroregulatory system 10 can stimulate the damaged brain area through a transcranial electrical stimulation device to promote nerve regeneration and functional recovery. In brain injury rehabilitation, the neuroregulatory system 10 can regulate brain nerve activity and improve cognitive function, attention, memory and other issues. The neuroregulatory system 10 provides researchers with a non-invasive means to study brain function. By precisely controlling the parameters of transcranial electrical stimulation, the changes in brain activity under different stimulation conditions can be observed, revealing the functional connections and information transfer mechanisms between brain regions.

[0028] The controller 101 is the core control unit of the neuroregulatory system 10, which coordinates and manages the operation of the entire neuroregulatory system 10. The controller 101 receives the EEG signal data from the electroencephalogram device 103, and issues instructions to the transcranial electrical stimulation device 102 to achieve precise control of parameters such as stimulation mode, stimulation intensity, and stimulation frequency to meet different treatment needs. The transcranial electrical stimulation device 102 is a device for non-invasive stimulation of the brain. Through electrodes placed on the scalp, a specific current or electric field is applied to a specific area of ​​the brain to regulate the activity of neurons. The electroencephalogram device 103 is used to record the electrical activity of the brain. Through electrodes placed on the scalp, the weak electrical signals generated by brain neurons are detected, and these signals are amplified and recorded. It should be explained that the stimulation parameters may include current stimulation parameters, magnetic field stimulation parameters, light stimulation parameters, ultrasonic stimulation parameters, temperature stimulation parameters, mechanical stimulation parameters, chemical stimulation parameters, etc. In this embodiment, the current stimulation parameters are mainly used as an example to electrically stimulate the target object.

[0029] In this embodiment, the EEG signal of the preset position of the target object is first obtained by the EEG device 103, and then the current stimulation parameters corresponding to the EEG signal and the preset brain working state are determined by the controller 101 to obtain the first current stimulation parameters. Then, the transcranial electrical stimulation device 102 performs electrical stimulation at the preset position of the target object according to the first current stimulation parameters, and then the potential change data corresponding to the EEG signal at the preset position is determined by the EEG device 103 to obtain the first potential change data. The preset potential change data of the preset brain working state at the preset position of the target object is obtained by the controller 101, and then the error value between the preset potential change data and the first potential change data is determined to obtain the target error value. When the target error value is greater than the preset error value, the first current stimulation parameter is adjusted based on the target error value to obtain the target current stimulation parameter. Finally, the transcranial electrical stimulation device 102 performs electrical stimulation at the preset position of the target object according to the target current stimulation parameters, so that the preset position enters the preset brain working state, and the current stimulation parameters are precisely controlled to put the brain in the expected working state.

[0030] See also Figure 2 , Figure 2 This is a flow chart of a current stimulation parameter control method provided in an embodiment of the present application. The method can be applied to a controller of a neural control system. The neural control system also includes: a transcranial electrical stimulation device and an electroencephalogram device. The method includes but is not limited to the following steps:

[0031] S201: Acquire an electroencephalogram (EEG) signal of a preset position of a target object through an EEG device.

[0032] In this embodiment, first ensure that the EEG device has good performance and accuracy and can accurately detect EEG signals, then select the electrode type suitable for the target object, such as scalp electrodes, and select a quiet, comfortable, and electromagnetic interference-free environment for detection. Ensure that the target object remains relaxed and quiet during the detection process to avoid interference from external factors on the EEG signal. Then determine the preset position for obtaining the EEG signal, place the electrode at the preset position, and connect the electrode to the EEG device through a wire, and then obtain the EEG signal of the preset position of the target object through the EEG device.

[0033] S202: Determine current stimulation parameters corresponding to the EEG signal and the preset brain working state, and obtain first current stimulation parameters.

[0034] In this embodiment, an experimental paradigm library is first obtained. The experimental paradigm library is a resource library that stores multiple paradigms. It should be explained that a paradigm refers to the sum of a set of theories, methods, techniques and practices that are widely accepted in a specific subject area. The paradigm in this embodiment is the sum of the correspondences between a large number of current stimulation parameters, EEG signals and brain working states obtained after multiple electrical stimulation experiments. According to the existing paradigms in the paradigm library, when conducting a new electrical stimulation experiment, appropriate current stimulation parameters can be selected according to the existing correspondences in the paradigm to achieve the desired brain working state.

[0035] Specifically, after obtaining the EEG signal of the preset position of the target object and determining the preset brain working state, the EEG signal and the preset brain working state are matched in the experimental paradigm library to obtain the target paradigm, and the current stimulation parameters corresponding to the EEG signal and the preset brain working state are determined according to the corresponding relationship in the target paradigm to obtain the first current stimulation parameters.

[0036] It should be explained that the first current stimulation parameters include but are not limited to the following: current intensity, current frequency, and current duration.

[0037] It can be seen that by using the existing paradigm for matching, blindly trying various different combinations of current stimulation parameters can be avoided, which greatly reduces the trial and error process in the experiment and saves time and resources.

[0038] S203: Performing electrical stimulation at a preset position of the target object according to the first current stimulation parameters using a transcranial electrical stimulation device.

[0039] In this embodiment, first ensure that the selected device has good performance and accuracy, and can accurately output the required current stimulation parameters. Transcranial electrical stimulation devices usually require the use of electrodes to transmit current to the brain of the target object, so the electrodes at the preset position are connected to the transcranial electrical stimulation device through wires. It should be explained that before placing the electrodes, the scalp at the preset position of the target object is cleaned to remove factors such as grease, dirt and hair that may affect the contact of the electrodes. Use electrode patches or other fixing devices to accurately place the electrodes at the preset positions. It is also necessary to ensure that there is good contact between the electrodes and the scalp. Conductive paste can be used to reduce the resistance between the electrodes and the scalp to improve the stimulation effect. In the process of placing the electrodes, care should also be taken to avoid short circuits and interference between the electrodes.

[0040] Specifically, the determined first current stimulation parameters are first input into the transcranial electrical stimulation device, and then the transcranial electrical stimulation device outputs current according to the input first current stimulation parameters to electrically stimulate the brain of the target object. After reaching a predetermined stimulation duration, the electrical stimulation operation is stopped.

[0041] S204: Determine the potential change data corresponding to the EEG signal at the preset position through the EEG device to obtain first potential change data.

[0042] In this embodiment, after the transcranial electrical stimulation device performs electrical stimulation at a preset position of the target object according to the first current stimulation parameters, the electroencephalogram device can determine the potential change data corresponding to the EEG signal at the preset position to obtain the first potential change data.

[0043] It should be explained that the first potential change data represents the potential values ​​of the EEG signal at different time points after the preset position is electrically stimulated.

[0044] S205: Obtaining preset potential change data of a preset position of the target object for a preset brain working state.

[0045] In this embodiment, preset potential change data for a preset brain working state at a preset position of the target object can be obtained from the experimental paradigm library, and the preset potential change data represents the expected potential values ​​of the EEG signal at different time points.

[0046] S206: Determine an error value between the preset potential change data and the first potential change data to obtain a target error value.

[0047] In this implementation, see Figure 3 , Figure 3 This is a flow chart of determining a target error value provided by an embodiment of the present application, and the method includes but is not limited to the following steps:

[0048] S301: Fitting is performed according to preset potential change data to obtain a preset potential change straight line.

[0049] In this embodiment, after obtaining the preset potential change data, a fitting method is used to fit the preset potential change data. After the fitting is completed, a preset potential change straight line can be obtained. The preset potential change straight line obtained by the fitting method can simply and intuitively highlight the overall change direction of the potential value.

[0050] S302: Determine the slope corresponding to the preset potential change straight line to obtain the preset slope.

[0051] In this embodiment, any two points in the preset potential change straight line are selected, and the slope corresponding to the preset potential change straight line can be calculated to obtain the preset slope.

[0052] S303: Perform fitting according to the first potential change data to obtain a first potential change straight line.

[0053] In this embodiment, it is first checked whether there are abnormal values ​​or errors in the first potential change data. If there is a potential value that differs too much from other data, data cleaning can be performed to delete the potential value.

[0054] Exemplarily, after determining the first electric potential change data, a fitting method is used to fit the first electric potential change data. The fitting method can be linear regression or polynomial fitting. After the fitting is completed, the first electric potential change straight line can be obtained. The first electric potential change straight line obtained by the fitting method can simply and intuitively highlight the overall change direction of the electric potential value corresponding to the EEG signal at the preset position of the target object after electrical stimulation.

[0055] S304: Determine the slope corresponding to the first potential change straight line to obtain a first slope.

[0056] In this embodiment, any two points in the first potential change straight line are selected to calculate the slope corresponding to the first potential change straight line to obtain the first slope.

[0057] It should be noted that if the first slope is greater than the preset slope threshold, it means that the determined first slope is inaccurate and the first slope needs to be adjusted. Exemplarily, n potential values ​​in the first potential change data are obtained, where n is an integer greater than 1, the maximum potential value and the minimum potential value among the n potential values ​​are determined, and the potential difference between the minimum potential value and the maximum potential value is determined to obtain the target potential difference value, which reflects the amplitude range of the potential change. Exemplarily, based on the minimum potential value and the maximum potential value, k interval ranges corresponding to the target potential difference value are determined, where k is an integer greater than 1, and the n potential values ​​fall into the k interval ranges, which is convenient for counting the number of potential values ​​in different interval ranges. Exemplarily, the number of potential values ​​in k intervals is counted to obtain the number of k potential values, and the weight corresponding to each interval in the k intervals is obtained to obtain k weights, wherein the sum of the k weights is 1, and the weight of the interval closer to the minimum potential value is smaller. It is generally believed that the closer the interval to the minimum potential value is, the smaller the degree of deviation from the normal range is, so the weight is smaller. Exemplarily, the number proportion corresponding to each interval is determined according to the number of k potential values ​​to obtain k number proportions, and a weighted operation is performed according to the k number proportions and the k weights to obtain the target deviation parameter. Specifically, the k number proportions are multiplied by the corresponding weights in the k weights, and then all the products are added to obtain the target deviation parameter. Exemplarily, the target optimization factor corresponding to the target deviation parameter is determined. Specifically, the mapping relationship between the preset deviation parameter and the optimization factor can be pre-stored, and the target optimization factor corresponding to the deviation parameter is determined based on the mapping relationship. Exemplarily, the first slope is optimized according to the target optimization factor to obtain the third slope. Specifically, the first slope can be optimized according to the target optimization factor. The specific calculation formula is as follows:

[0058] The third slope = the first slope × (1 + target optimization factor);

[0059] The third slope can be obtained according to the above formula.

[0060] Exemplarily, a difference between the preset slope and the third slope is determined to obtain a target difference.

[0061] If the first slope is less than or equal to the preset slope threshold, the difference between the preset slope and the first slope is directly determined to obtain the target difference.

[0062] It can be seen that multi-dimensional analysis of the potential value, such as maximum value, minimum value, and interval division, can provide a more comprehensive understanding of the distribution of potential changes. By performing a weighted operation on the quantity proportion and the weight to obtain the target deviation parameter, the distribution of potential values ​​in different intervals can be comprehensively considered. When the first slope is greater than the preset slope threshold, it indicates that there may be large fluctuations or anomalies in the potential change. By performing detailed analysis and processing on the potential value, these anomalies can be identified and corresponding optimization measures can be taken to improve the accuracy of the data.

[0063] S305: Determine the difference between the preset slope and the first slope to obtain a target difference.

[0064] In this embodiment, the difference between the preset slope and the first slope can be used to measure the degree of deviation between the actual potential change and the expected potential change, so the difference between the preset slope and the first slope is determined to obtain the target difference. If the target difference is zero, it means that the actual situation is completely consistent with the expectation. If the target difference is large, it means that the actual situation is greatly different from the expectation. Exemplarily, the reference difference between the preset slope and the first slope is determined. Specifically, the difference between the preset slope and the first slope is first calculated to obtain the reference difference. Exemplarily, the skin impedance corresponding to the preset position is obtained to obtain the target skin impedance, and the target influence coefficient corresponding to the target skin impedance is determined. Specifically, since the higher skin impedance will weaken the intensity of the EEG signal detected by the scalp electrode, this means that the amplitude of the potential change data may be reduced, so that the originally large potential change becomes less obvious after being affected by the skin impedance, and the skin impedance at different positions may be different, which will cause the EEG signals detected at different electrode positions to be affected to different degrees. Therefore, when determining the difference between the preset slope and the first slope, the influence of the skin impedance corresponding to the preset position should be considered. The mapping relationship between the preset skin impedance and the influence coefficient may be pre-stored, and the target influence coefficient corresponding to the target skin impedance is determined based on the mapping relationship. Exemplarily, the reference difference value is adjusted according to the target influence coefficient to obtain the target difference value. Specifically, the reference difference value may be optimized according to the target influence coefficient. The specific calculation formula is as follows:

[0065] Target difference = reference difference × (1 + target influence coefficient);

[0066] The target difference can be obtained according to the above formula.

[0067] It can be seen that by obtaining the skin impedance at a preset position and determining the corresponding target influence coefficient, the influence of skin impedance on the potential change data can be taken into consideration. By introducing the target influence coefficient to adjust the reference difference, the obtained target difference can better reflect the actual changes in the EEG signal.

[0068] S306: Determine a target error value based on the target difference value.

[0069] In this embodiment, illustratively, a reference error value corresponding to a target difference is determined. Specifically, a mapping relationship between a preset difference and an error value may be pre-stored, and a reference error value corresponding to the target difference is determined based on the mapping relationship.

[0070] Exemplarily, historical error values ​​within a preset time period are obtained to obtain m historical error values, where m is a positive integer, and each historical error value corresponds to an error value detection moment. Specifically, the historical error value may be error data recorded during a similar experiment or monitoring process within a previous preset time period.

[0071] Exemplarily, fitting is performed based on m historical error values ​​and corresponding error value detection moments to obtain a target fitting straight line, wherein the horizontal axis of the target fitting straight line is time and the vertical axis is the historical error value. Specifically, the m historical error values ​​and the corresponding error value detection moments are used as data points for fitting operation. Fitting can be performed using a linear regression method or a polynomial fitting method. The purpose of fitting is to find a straight line that can better describe the trend of historical error values ​​changing over time. The horizontal axis of the obtained target fitting straight line is time, and the vertical axis is the historical error value.

[0072] Exemplarily, the slope corresponding to the target fitting line is obtained to obtain the second slope. Specifically, by arbitrarily selecting two points on the target fitting line, the slope corresponding to the target fitting line can be calculated to obtain the second slope.

[0073] Exemplarily, the target fine-tuning parameter corresponding to the second slope is determined. Specifically, a mapping relationship between a preset slope and a fine-tuning parameter may be pre-stored, and the target fine-tuning parameter corresponding to the second slope is determined based on the mapping relationship.

[0074] Exemplarily, the reference error value is fine-tuned based on the target fine-tuning parameter to obtain the target error value. Specifically, the reference error value can be optimized according to the target fine-tuning parameter. The specific calculation formula is as follows:

[0075] Target error value = reference error value × (1 + target fine-tuning parameter);

[0076] The target error value can be obtained according to the above formula.

[0077] It can be seen that by obtaining the historical error values ​​within a preset time period, past experience can be used to assist in determining the current error value. The historical error values ​​and the corresponding detection moments are fitted to obtain the target fitting straight line, which can reveal the changing trend of the error value over time. The target fine-tuning parameters are determined according to the slope of the target fitting straight line, and the reference error value is fine-tuned to further improve the accuracy of the error value.

[0078] S207: When the target error value is greater than the preset error value, adjusting the first current stimulation parameter based on the target error value to obtain the target current stimulation parameter.

[0079] In this embodiment, when the target error value is less than or equal to the preset error value, it means that after the transcranial electrical stimulation device performs electrical stimulation at the preset position of the target object according to the first current stimulation parameter, the preset position can enter the preset brain working state, so the first current stimulation parameter is directly determined as the target current stimulation parameter.

[0080] When the target error value is greater than the preset error value, it means that after the transcranial electrical stimulation device performs electrical stimulation at the preset position of the target object according to the first current stimulation parameters, the preset position cannot enter the preset brain working state, so the first current stimulation parameters need to be adjusted.

[0081] Exemplarily, the first current frequency, first current intensity and first current duration corresponding to the first current stimulation parameters are obtained. Specifically, the current stimulation parameters of the transcranial electrical stimulation device currently in use include three key aspects: frequency, intensity and duration of the current. These parameters determine the characteristics of electrical stimulation to the brain, so the first current frequency, first current intensity and first current duration corresponding to the first current stimulation parameters are obtained.

[0082] Exemplarily, a reference current frequency adjustment coefficient, a reference current intensity adjustment coefficient, and a reference current duration adjustment coefficient corresponding to the target error value are determined.

[0083] Exemplarily, the skin temperature corresponding to the preset position is obtained to obtain the target skin temperature, and the first optimization factor corresponding to the target skin temperature is determined. The reference current frequency adjustment coefficient is optimized according to the first optimization factor to obtain the target current frequency adjustment coefficient. Specifically, a higher skin temperature may make neurons more sensitive, and the response to current stimulation is enhanced. The response of the nerves to the current frequency may be more obvious, and the frequency may need to be adjusted to avoid overstimulation. The mapping relationship between the preset temperature and the optimization factor can be pre-stored, and the first optimization factor corresponding to the target temperature is determined based on the mapping relationship. The reference current frequency adjustment coefficient can be optimized according to the first optimization factor, and the specific calculation formula is as follows: target current frequency adjustment coefficient = reference current frequency adjustment coefficient × (1 + first optimization factor); the target current frequency adjustment coefficient can be obtained according to the above formula.

[0084] Exemplarily, the hair density at a preset position is obtained to obtain a target hair density, a second optimization factor corresponding to the target hair density is determined, and the reference current intensity adjustment coefficient is optimized according to the second optimization factor to obtain the target current intensity adjustment coefficient. Specifically, because hair can cause the current to scatter and disperse during the conduction process, when the current passes through the hair, it will deviate to a certain extent along the direction of the hair, rather than directly penetrating the scalp vertically into the brain, which will cause the current to weaken when it reaches the target area, so the current intensity needs to be adjusted. The mapping relationship between the preset hair density and the optimization factor can be pre-stored, and the second optimization factor corresponding to the target hair density is determined based on the mapping relationship. The reference current intensity adjustment coefficient can be optimized according to the second optimization factor, and the specific calculation formula is as follows: target current intensity adjustment coefficient = reference current intensity adjustment coefficient × (1 + second optimization factor); the target current intensity adjustment coefficient can be obtained according to the above formula.

[0085] Exemplarily, the area of ​​the preset position is obtained, the target area is obtained, the third optimization factor corresponding to the target area is determined, and the reference current duration adjustment coefficient is optimized according to the third optimization factor to obtain the target current duration adjustment coefficient. Specifically, when the area of ​​the preset position is large, the distribution of the applied current in the area will be more dispersed. In order to ensure that the entire area can receive sufficient stimulation, a longer current duration is required. This is because the current takes a certain amount of time to fully diffuse into a larger area to achieve the expected stimulation effect; when the area of ​​the preset position is small, the distribution of the current is relatively concentrated. In this case, a shorter current duration may be sufficient to allow the area to receive sufficient stimulation. The mapping relationship between the preset area and the optimization factor can be pre-stored, and the third optimization factor corresponding to the target area is determined based on the mapping relationship. The reference current duration adjustment coefficient can be optimized according to the third optimization factor, and the specific calculation formula is as follows: target current duration adjustment coefficient = reference current duration adjustment coefficient × (1 + third optimization factor); the target current duration adjustment coefficient can be obtained according to the above formula.

[0086] Exemplarily, the target adjustment coefficient is determined based on the target current frequency adjustment coefficient, the target current intensity adjustment coefficient and the target current duration adjustment coefficient. First, multiple potential values ​​in the preset potential change data are obtained, and the target mean square deviation of the multiple potential values ​​is determined. Specifically, the corresponding potential value is obtained from the preset potential change data to obtain multiple potential values. The mean square deviation of the multiple potential values ​​reflects the dispersion degree of these potential values. Therefore, the obtained multiple potential values ​​are statistically analyzed, and their mean square deviation is calculated to obtain the target mean square deviation. Then, a target weight corresponding to the target mean square error is determined, wherein the target weight includes a first weight, a second weight, and a third weight. A weighted operation is performed according to the first weight, the second weight, the third weight, the target current frequency adjustment coefficient, the target current intensity adjustment coefficient, and the target current duration adjustment coefficient to obtain the target adjustment coefficient. Specifically, a mapping relationship between a preset mean square error and a weight may be pre-stored. Based on the mapping relationship, the first weight, the second weight, and the third weight corresponding to the target mean square error are determined, wherein the first weight corresponds to the target current frequency adjustment coefficient, the second weight corresponds to the target current intensity adjustment coefficient, and the third weight corresponds to the target current duration adjustment coefficient. Then, a weighted operation is performed according to the first weight, the second weight, the third weight, the target current frequency adjustment coefficient, the target current intensity adjustment coefficient, and the target current duration adjustment coefficient to obtain the target adjustment coefficient. Specifically, the target adjustment coefficient is calculated according to the following formula:

[0087]

[0088] Where F is the target adjustment coefficient, is the target current frequency adjustment coefficient, is the target current intensity adjustment coefficient, is the target current duration adjustment coefficient, is the first weight, is the second weight, is the third weight.

[0089] Exemplarily, the first current stimulation parameter is adjusted based on the target adjustment coefficient to obtain the target current stimulation parameter. Specifically, the target adjustment coefficient is a coefficient for adjusting the first current stimulation parameter obtained by comprehensively considering the target current frequency adjustment coefficient, the target current intensity adjustment coefficient, the target current duration adjustment coefficient, and the first weight, the second weight, and the third weight. The first current frequency, the first current intensity, and the first current duration corresponding to the first current stimulation parameter are adjusted by the target adjustment coefficient to obtain the target current frequency, the target current intensity, and the target current duration. Then, the target current frequency, the target current intensity, and the target current duration are combined to obtain the target current stimulation parameter.

[0090] It should be noted that if the error value between the obtained potential change data and the preset potential change data is still greater than the preset error value after the preset position of the target object is electrically stimulated by the current stimulation parameters composed of the adjusted current frequency, current intensity and current duration, the adjusted current stimulation parameters will continue to be adjusted. There is no limit to the number of adjustments, and the adjustments can be made indefinitely until the error value corresponding to the current stimulation parameters is less than or equal to the preset error value, and the current stimulation parameters are used as the target current stimulation parameters.

[0091] It can be seen that whether the current stimulation parameters need to be adjusted is determined according to the target error value to ensure that the stimulation can make the preset position enter the preset brain working state. The effects of factors such as skin temperature, hair density, and preset position area on the current stimulation parameters are comprehensively considered, which can better adapt to specific situations and improve the pertinence and effectiveness of stimulation. The error value between the potential change data and the preset potential change data is used as the basis for adjustment, forming a closed-loop feedback system. By continuously adjusting the current stimulation parameters, the actual potential change gradually approaches the preset value, thereby improving the accuracy of the stimulation. It allows unlimited adjustments until the error value meets the requirements, ensuring that the final target current stimulation parameters can achieve the expected effect to the greatest extent.

[0092] S208: Performing electrical stimulation at a preset position of the target object according to target current stimulation parameters through a transcranial electrical stimulation device, so that the preset position enters a preset brain working state.

[0093] In this embodiment, after obtaining the target current stimulation parameters, since the error value between the potential change data corresponding to the target stimulation parameters and the preset potential change data is less than or equal to the preset error value, electrical stimulation is performed at the preset position of the target object according to the target current stimulation parameters by the transcranial electrical stimulation device, so that the preset position can enter the preset brain working state.

[0094] In summary, the implementation of the present invention has the following beneficial effects:

[0095] It can be seen that the current stimulation parameter control device described in the embodiment of the present invention is applied to the controller of the neural regulation system, and the neural regulation system also includes: a transcranial electrical stimulation device, an electroencephalogram device, and the electroencephalogram device is used to obtain the electroencephalogram signal of the preset position of the target object; determine the current stimulation parameter corresponding to the electroencephalogram signal and the preset brain working state to obtain the first current stimulation parameter; perform electrical stimulation at the preset position of the target object according to the first current stimulation parameter through the transcranial electrical stimulation device; determine the potential change data corresponding to the electroencephalogram signal at the preset position through the electroencephalogram device to obtain the first potential change data; obtain the preset potential change data of the preset position of the target object for the preset brain working state; determine the error value between the preset potential change data and the first potential change data to obtain the target error value; when the target error value is greater than the preset error value, adjust the first current stimulation parameter based on the target error value to obtain the target current stimulation parameter; perform electrical stimulation at the preset position of the target object according to the target current stimulation parameter through the transcranial electrical stimulation device, so that the preset position enters the preset brain working state. The embodiment of the present invention is adopted to achieve precise control of the current stimulation parameters and put the brain in the expected working state.

[0096] See also Figure 4 , Figure 4 It is a structural schematic diagram of a current stimulation parameter control device provided in an embodiment of the present application, which is applied to a controller of a neural control system, and the neural control system also includes: a transcranial electrical stimulation device and an electroencephalogram device; the current stimulation parameter control device 400 includes: an acquisition unit 401 and a processing unit 402;

[0097] An acquisition unit 401 is used to acquire an EEG signal of a preset position of a target object through an EEG device;

[0098] The processing unit 402 is used to determine the current stimulation parameter corresponding to the EEG signal and the preset brain working state, and obtain the first current stimulation parameter;

[0099] Performing electrical stimulation at a preset position of the target object according to a first current stimulation parameter by a transcranial electrical stimulation device;

[0100] Determine the electric potential change data corresponding to the electroencephalogram signal at the preset position by an electroencephalogram device to obtain first electric potential change data;

[0101] An acquisition unit 401 is used to acquire preset potential change data of a preset position of a target object for a preset brain working state;

[0102] The processing unit 402 is used to determine an error value between the preset potential change data and the first potential change data to obtain a target error value;

[0103] When the target error value is greater than the preset error value, adjusting the first current stimulation parameter based on the target error value to obtain the target current stimulation parameter;

[0104] Electrical stimulation is performed at a preset position of the target object according to target current stimulation parameters through a transcranial electrical stimulation device, so that the preset position enters a preset brain working state.

[0105] In some possible implementations, in determining the error value between the preset potential change data and the first potential change data to obtain the target error value, the processing unit 402 is specifically configured to:

[0106] Fitting is performed according to the preset potential change data to obtain a preset potential change straight line;

[0107] Determine the slope corresponding to the preset potential change straight line to obtain a preset slope;

[0108] Perform fitting according to the first potential change data to obtain a first potential change straight line;

[0109] Determine the slope corresponding to the first potential change straight line to obtain a first slope;

[0110] Determine the difference between the preset slope and the first slope to obtain a target difference;

[0111] A target error value is determined based on the target difference value.

[0112] In some possible implementations, in determining the difference between the preset slope and the first slope to obtain the target difference, the processing unit 402 is specifically configured to:

[0113] determining a reference difference between the preset slope and the first slope;

[0114] Obtaining the skin impedance corresponding to the preset position to obtain the target skin impedance;

[0115] determining a target influence coefficient corresponding to a target skin impedance;

[0116] The reference difference is adjusted according to the target influence coefficient to obtain the target difference.

[0117] In some possible implementations, in determining the target error value based on the target difference value, the processing unit 402 is specifically configured to:

[0118] Determine a reference error value corresponding to the target difference value;

[0119] Obtain historical error values ​​within a preset time period to obtain m historical error values; m is a positive integer, and each historical error value corresponds to an error value detection moment;

[0120] Fitting is performed according to m historical error values ​​and corresponding error value detection moments to obtain a target fitting straight line; the horizontal axis of the target fitting straight line is time and the vertical axis is the historical error value;

[0121] Obtain the slope corresponding to the target fitting straight line to obtain the second slope;

[0122] determining a target fine-tuning parameter corresponding to the second slope;

[0123] The reference error value is fine-tuned based on the target fine-tuning parameter to obtain a target error value.

[0124] In some possible implementations, the processing unit 402 is further specifically configured to:

[0125] If the first slope is greater than a preset slope threshold, obtaining n potential values ​​in the first potential change data; n is an integer greater than 1;

[0126] Determine the maximum potential and the minimum potential among the n potential values;

[0127] Determine the potential difference between the minimum potential value and the maximum potential value to obtain a target potential difference value;

[0128] According to the minimum potential value and the maximum potential value, k interval ranges corresponding to the target potential difference value are determined; k is an integer greater than 1;

[0129] The n potential values ​​fall into k intervals;

[0130] Count the number of potential values ​​in k intervals to obtain the number of k potential values;

[0131] Obtain the weight corresponding to each of the k intervals to obtain k weights; the sum of the k weights is 1, and the weight of the interval closer to the minimum potential value is smaller;

[0132] Determine the quantity proportion corresponding to each interval range according to the number of k potential values, and obtain k quantity proportions;

[0133] Perform a weighted operation based on the k quantity proportions and k weights to obtain the target deviation parameter;

[0134] determining a target optimization factor corresponding to the target deviation parameter;

[0135] Optimizing the first slope according to the target optimization factor to obtain a third slope;

[0136] The difference between the preset slope and the third slope is determined to obtain a target difference.

[0137] In some possible implementations, in adjusting the first current stimulation parameter based on the target error value to obtain the target current stimulation parameter, the processing unit 402 is specifically configured to:

[0138] Acquire a first current frequency, a first current intensity, and a first current duration corresponding to a first current stimulation parameter;

[0139] Determine a reference current frequency adjustment coefficient, a reference current intensity adjustment coefficient, and a reference current duration adjustment coefficient corresponding to the target error value;

[0140] Obtaining the skin temperature corresponding to the preset position to obtain the target skin temperature;

[0141] determining a first optimization factor corresponding to a target skin temperature;

[0142] Optimizing the reference current frequency adjustment coefficient according to the first optimization factor to obtain a target current frequency adjustment coefficient;

[0143] Obtaining the hair density at a preset position to obtain a target hair density;

[0144] determining a second optimization factor corresponding to the target hair density;

[0145] Optimizing the reference current intensity adjustment coefficient according to the second optimization factor to obtain a target current intensity adjustment coefficient;

[0146] Get the area of ​​the preset position to obtain the target area;

[0147] determining a third optimization factor corresponding to the target area;

[0148] Optimizing the reference current duration adjustment coefficient according to the third optimization factor to obtain the target current duration adjustment coefficient;

[0149] Determine a target adjustment coefficient based on a target current frequency adjustment coefficient, a target current intensity adjustment coefficient, and a target current duration adjustment coefficient;

[0150] The first current stimulation parameter is adjusted based on the target adjustment coefficient to obtain the target current stimulation parameter.

[0151] In some possible implementations, in determining the target adjustment coefficient based on the target current frequency adjustment coefficient, the target current intensity adjustment coefficient, and the target current duration adjustment coefficient, the processing unit 402 is specifically configured to:

[0152] Acquire multiple potential values ​​in preset potential change data;

[0153] determining a target mean square error for a plurality of potential values;

[0154] Determine a target weight corresponding to the target mean square error; the target weight includes a first weight, a second weight, and a third weight;

[0155] A weighted operation is performed according to the first weight, the second weight, the third weight, the target current frequency adjustment coefficient, the target current intensity adjustment coefficient and the target current duration adjustment coefficient to obtain the target adjustment coefficient.

[0156] See also Figure 5 , Figure 5 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 5 As shown, the electronic device 500 includes a transceiver 501, a processor 502 and a memory 503. They are connected via a bus 504. The memory 503 is used to store computer programs and data, and the transceiver 501 is used to transmit the data stored in the memory 503 to the processor 502. The electronic device 500 includes a controller of a neural regulation system, and the neural regulation system also includes: a transcranial electrical stimulation device and an electroencephalogram device. The above program includes instructions for executing the following steps:

[0157] Acquiring an electroencephalogram signal of a preset position of a target object through an electroencephalogram device;

[0158] Determine a current stimulation parameter corresponding to the EEG signal and a preset brain working state to obtain a first current stimulation parameter;

[0159] Performing electrical stimulation at a preset position of the target object according to a first current stimulation parameter by a transcranial electrical stimulation device;

[0160] Determine the electric potential change data corresponding to the electroencephalogram signal at the preset position by an electroencephalogram device to obtain first electric potential change data;

[0161] Acquiring preset electric potential change data at a preset position of the target object for a preset brain working state;

[0162] Determine an error value between the preset potential change data and the first potential change data to obtain a target error value;

[0163] When the target error value is greater than the preset error value, adjusting the first current stimulation parameter based on the target error value to obtain the target current stimulation parameter;

[0164] Electrical stimulation is performed at a preset position of the target object according to target current stimulation parameters through a transcranial electrical stimulation device, so that the preset position enters a preset brain working state.

[0165] In some possible implementations, in determining the error value between the preset potential change data and the first potential change data to obtain the target error value, the program includes instructions for executing the following steps:

[0166] Fitting is performed according to the preset potential change data to obtain a preset potential change straight line;

[0167] Determine the slope corresponding to the preset potential change straight line to obtain a preset slope;

[0168] Perform fitting according to the first potential change data to obtain a first potential change straight line;

[0169] Determine the slope corresponding to the first potential change straight line to obtain a first slope;

[0170] Determine the difference between the preset slope and the first slope to obtain a target difference;

[0171] A target error value is determined based on the target difference value.

[0172] In some possible implementations, in terms of determining the difference between the preset slope and the first slope to obtain the target difference, the program includes instructions for executing the following steps:

[0173] determining a reference difference between the preset slope and the first slope;

[0174] Obtaining the skin impedance corresponding to the preset position to obtain the target skin impedance;

[0175] determining a target influence coefficient corresponding to a target skin impedance;

[0176] The reference difference is adjusted according to the target influence coefficient to obtain the target difference.

[0177] In some possible implementations, in determining the target error value based on the target difference value, the program includes instructions for performing the following steps:

[0178] Determine a reference error value corresponding to the target difference value;

[0179] Obtain historical error values ​​within a preset time period to obtain m historical error values; m is a positive integer, and each historical error value corresponds to an error value detection moment;

[0180] Fitting is performed according to m historical error values ​​and corresponding error value detection moments to obtain a target fitting straight line; the horizontal axis of the target fitting straight line is time and the vertical axis is the historical error value;

[0181] Obtain the slope corresponding to the target fitting straight line to obtain the second slope;

[0182] determining a target fine-tuning parameter corresponding to the second slope;

[0183] The reference error value is fine-tuned based on the target fine-tuning parameter to obtain a target error value.

[0184] In some possible implementations, the above program includes instructions for performing the following steps:

[0185] If the first slope is greater than a preset slope threshold, obtaining n potential values ​​in the first potential change data; n is an integer greater than 1;

[0186] Determine the maximum potential and the minimum potential among the n potential values;

[0187] Determine the potential difference between the minimum potential value and the maximum potential value to obtain a target potential difference value;

[0188] According to the minimum potential value and the maximum potential value, k interval ranges corresponding to the target potential difference value are determined; k is an integer greater than 1;

[0189] The n potential values ​​fall into k intervals;

[0190] Count the number of potential values ​​in k intervals to obtain the number of k potential values;

[0191] Obtain the weight corresponding to each of the k intervals to obtain k weights; the sum of the k weights is 1, and the weight of the interval closer to the minimum potential value is smaller;

[0192] Determine the quantity proportion corresponding to each interval range according to the number of k potential values, and obtain k quantity proportions;

[0193] Perform a weighted operation based on the k quantity proportions and k weights to obtain the target deviation parameter;

[0194] determining a target optimization factor corresponding to the target deviation parameter;

[0195] Optimizing the first slope according to the target optimization factor to obtain a third slope;

[0196] The difference between the preset slope and the third slope is determined to obtain a target difference.

[0197] In some possible implementations, in terms of adjusting the first current stimulation parameter based on the target error value to obtain the target current stimulation parameter, the program includes instructions for performing the following steps:

[0198] Acquire a first current frequency, a first current intensity, and a first current duration corresponding to a first current stimulation parameter;

[0199] Determine a reference current frequency adjustment coefficient, a reference current intensity adjustment coefficient, and a reference current duration adjustment coefficient corresponding to the target error value;

[0200] Obtaining the skin temperature corresponding to the preset position to obtain the target skin temperature;

[0201] determining a first optimization factor corresponding to a target skin temperature;

[0202] Optimizing the reference current frequency adjustment coefficient according to the first optimization factor to obtain a target current frequency adjustment coefficient;

[0203] Obtaining the hair density at a preset position to obtain a target hair density;

[0204] determining a second optimization factor corresponding to the target hair density;

[0205] Optimizing the reference current intensity adjustment coefficient according to the second optimization factor to obtain a target current intensity adjustment coefficient;

[0206] Get the area of ​​the preset position to obtain the target area;

[0207] determining a third optimization factor corresponding to the target area;

[0208] Optimizing the reference current duration adjustment coefficient according to the third optimization factor to obtain the target current duration adjustment coefficient;

[0209] Determine a target adjustment coefficient based on a target current frequency adjustment coefficient, a target current intensity adjustment coefficient, and a target current duration adjustment coefficient;

[0210] The first current stimulation parameter is adjusted based on the target adjustment coefficient to obtain the target current stimulation parameter.

[0211] In some possible implementations, in determining the target adjustment coefficient based on the target current frequency adjustment coefficient, the target current intensity adjustment coefficient, and the target current duration adjustment coefficient, the program includes instructions for performing the following steps:

[0212] Acquire multiple potential values ​​in preset potential change data;

[0213] determining a target mean square error for a plurality of potential values;

[0214] Determine a target weight corresponding to the target mean square error; the target weight includes a first weight, a second weight, and a third weight;

[0215] A weighted operation is performed according to the first weight, the second weight, the third weight, the target current frequency adjustment coefficient, the target current intensity adjustment coefficient and the target current duration adjustment coefficient to obtain the target adjustment coefficient.

[0216] It should be understood that the electronic devices in this application may include smart phones (such as Android phones, iOS phones, Windows Phone phones, etc.), tablet computers, PDAs, laptops, mobile Internet devices MID (Mobile Internet Devices, referred to as: MID) or wearable devices or servers, edge computing nodes, etc. The above electronic devices are only examples, not exhaustive, and include but are not limited to the above electronic devices.

[0217] It should be noted that, for the above-mentioned various method implementations, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the implementations described in the specification are all optional implementations, and the actions and modules involved are not necessarily required by this application.

[0218] In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0219] In the several embodiments provided in this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device implementation described above is only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0220] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0221] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software program module.

[0222] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of each implementation method of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0223] A person skilled in the art may understand that all or part of the steps in the various methods of the above-mentioned embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable memory, and the memory may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0224] The above is a detailed introduction to the implementation methods of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above implementation methods is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A current stimulation parameter control device, characterized in that: A controller applied to a neural regulation system, wherein the neural regulation system further comprises: a transcranial electrical stimulation device, an electroencephalogram device, and the current stimulation parameter control device comprises: an acquisition unit and a processing unit, wherein: The acquisition unit is used to acquire an electroencephalogram signal of a preset position of a target object through the electroencephalogram device; The processing unit is used to determine the current stimulation parameter corresponding to the EEG signal and the preset brain working state to obtain the first current stimulation parameter; Performing electrical stimulation at the preset position of the target object according to the first current stimulation parameter by the transcranial electrical stimulation device; Determine the potential change data corresponding to the EEG signal at the preset position by the EEG device to obtain first potential change data; The acquisition unit is used to acquire preset electric potential change data of the preset position of the target object for the preset brain working state; The processing unit is used to determine an error value between the preset potential change data and the first potential change data to obtain a target error value; When the target error value is greater than a preset error value, adjusting the first current stimulation parameter based on the target error value to obtain a target current stimulation parameter; Performing electrical stimulation at the preset position of the target object according to the target current stimulation parameters by the transcranial electrical stimulation device, so that the preset position enters the preset brain working state; Wherein, in determining the error value between the preset potential change data and the first potential change data to obtain the target error value, the processing unit is specifically used for: Perform fitting according to the preset potential change data to obtain a preset potential change straight line; Determine the slope corresponding to the preset potential change straight line to obtain a preset slope; Perform fitting according to the first potential change data to obtain a first potential change straight line; Determine the slope corresponding to the first potential change straight line to obtain a first slope; Determine a difference between the preset slope and the first slope to obtain a target difference; determining the target error value based on the target difference value; If the first slope is greater than a preset slope threshold, obtaining n potential values ​​in the first potential change data; n is an integer greater than 1; Determining a maximum potential value and a minimum potential value among the n potential values; Determine a potential difference between the minimum potential value and the maximum potential value to obtain a target potential difference value; According to the minimum potential value and the maximum potential value, k interval ranges corresponding to the target potential difference value are determined; k is an integer greater than 1; The n potential values ​​fall into the k interval ranges; Counting the number of potential values ​​in the k intervals to obtain k number of potential values; Obtaining a weight corresponding to each of the k intervals to obtain k weights; the sum of the k weights is 1, and the weight of an interval closer to the minimum potential value is smaller; Determine the quantity proportion corresponding to each interval range according to the number of k potential values, and obtain k quantity proportions; Performing a weighted operation according to the k quantity proportions and the k weights to obtain a target deviation parameter; determining a target optimization factor corresponding to the target deviation parameter; Optimizing the first slope according to the target optimization factor to obtain a third slope; A difference between the preset slope and the third slope is determined to obtain the target difference.

2. The device according to claim 1, characterized in that In determining the difference between the preset slope and the first slope to obtain a target difference, the processing unit is specifically configured to: determining a reference difference between the preset slope and the first slope; Acquire the skin impedance corresponding to the preset position to obtain the target skin impedance; determining a target influence coefficient corresponding to the target skin impedance; The reference difference is adjusted according to the target influence coefficient to obtain the target difference.

3. The device according to claim 1, characterized in that In determining the target error value based on the target difference value, the processing unit is specifically configured to: Determining a reference error value corresponding to the target difference; Obtain historical error values ​​within a preset time period to obtain m historical error values; m is a positive integer, and each historical error value corresponds to an error value detection moment; Fitting is performed according to the m historical error values ​​and the corresponding error value detection moments to obtain a target fitting straight line; the horizontal axis of the target fitting straight line is time and the vertical axis is the historical error value; Obtaining the slope corresponding to the target fitting straight line to obtain a second slope; determining a target fine-tuning parameter corresponding to the second slope; The reference error value is fine-tuned based on the target fine-tuning parameter to obtain the target error value.

4. The device according to claim 3, characterized in that In the aspect of adjusting the first current stimulation parameter based on the target error value to obtain the target current stimulation parameter, the processing unit is specifically used for: Acquire a first current frequency, a first current intensity, and a first current duration corresponding to the first current stimulation parameter; Determine a reference current frequency adjustment coefficient, a reference current intensity adjustment coefficient, and a reference current duration adjustment coefficient corresponding to the target error value; Acquire the skin temperature corresponding to the preset position to obtain the target skin temperature; determining a first optimization factor corresponding to the target skin temperature; Optimizing the reference current frequency adjustment coefficient according to the first optimization factor to obtain a target current frequency adjustment coefficient; Acquiring the hair density at the preset position to obtain a target hair density; determining a second optimization factor corresponding to the target hair density; Optimizing the reference current intensity adjustment coefficient according to the second optimization factor to obtain a target current intensity adjustment coefficient; Acquire the area of ​​the preset position to obtain a target area; determining a third optimization factor corresponding to the target area; Optimizing the reference current duration adjustment coefficient according to the third optimization factor to obtain a target current duration adjustment coefficient; Determine a target adjustment coefficient based on the target current frequency adjustment coefficient, the target current intensity adjustment coefficient, and the target current duration adjustment coefficient; The first current stimulation parameter is adjusted based on the target adjustment coefficient to obtain the target current stimulation parameter.

5. The device according to claim 4, characterized in that In determining the target adjustment coefficient based on the target current frequency adjustment coefficient, the target current intensity adjustment coefficient, and the target current duration adjustment coefficient, the processing unit is specifically configured to: Acquiring a plurality of potential values ​​in the preset potential change data; determining a target mean square error for the plurality of potential values; Determining a target weight corresponding to the target mean square error; The target weight includes a first weight, a second weight and a third weight; The target adjustment coefficient is obtained by performing a weighted operation based on the first weight, the second weight, the third weight, the target current frequency adjustment coefficient, the target current intensity adjustment coefficient, and the target current duration adjustment coefficient.

6. An electronic device, characterized in that: It comprises the current stimulation parameter control device as described in any one of claims 1-5.

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