Electroencephalogram signal-based nerve electrical stimulation method, device and system

Abstract

The invention provides a nerve electrical stimulation method, device and system based on electroencephalogram signals, and the method comprises the steps: obtaining pain related features in real time, the pain related features comprising electroencephalogram index features and heart rate variability features; generating a comprehensive pain score value in real time based on the pain related characteristics, and generating an electrical stimulation parameter in real time based on a target difference value between the comprehensive pain score value and the baseline score value; the vagus nerve of the patient is electrically stimulated based on the electrical stimulation parameters. The problem that in the prior art, due to immobilization of electrical stimulation parameters, dynamic adjustment cannot be conducted according to real-time neural activity of a patient, and therefore the treatment effect is affected is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of vagus nerve electrical stimulation, and in particular to a method, device and system for nerve electrical stimulation based on electroencephalogram signals. Background Art

[0002] In recent years, the application of neuroelectric stimulation technology in the medical field has become more and more extensive, especially in the treatment of chronic pain, rehabilitation of neurological diseases and management of mental illnesses, and has achieved remarkable therapeutic effects. Traditional neuroelectric stimulation equipment transmits electrical signals of specific frequencies to the target nerves to intervene in neural activity, thereby achieving therapeutic effects. At the same time, electroencephalogram (EEG) as a non-invasive, real-time neural activity monitoring technology can directly reflect the patient's neural activity status, and therefore has been widely recognized in clinical practice.

[0003] Driven by science and technology, combining EEG signals with neural electrical stimulation and regulating the parameters of electrical stimulation through real-time feedback has gradually become an important research direction for personalized treatment. Although neural electrical stimulation technology has made significant progress, the existing devices on the market cannot be dynamically adjusted according to the patient's real-time neural activity due to the fixed electrical stimulation parameters, which affects the treatment effect. At the same time, since the existing equipment fails to integrate the real-time acquisition and analysis functions of EEG signals, it is difficult to accurately monitor the changes in the patient's neural state, which may lead to the risk of insufficient stimulation intensity or over-stimulation, thereby affecting the safety and effectiveness of the treatment.

[0004] Therefore, it is necessary to propose a neural electrical stimulation scheme based on EEG signal control to solve the above technical problems. Summary of the invention

[0005] The purpose of the present invention is to provide a method, device and system for neural electrical stimulation based on EEG signals, so as to solve the problem in the prior art that the electrical stimulation parameters are fixed and cannot be dynamically adjusted according to the patient's real-time neural activity, thus affecting the treatment effect.

[0006] Furthermore, the present invention also solves the problem in the prior art that it is difficult to accurately monitor changes in the patient's neural state, which may lead to the risk of insufficient stimulation intensity or excessive stimulation, thereby affecting the safety and effectiveness of the treatment.

[0007] To achieve the above object, in a first aspect, a method for electrical stimulation of a nerve based on an electroencephalogram signal is provided, the method comprising:

[0008] Acquiring pain-related features in real time, wherein the pain-related features include EEG index features and heart rate variability features;

[0009] Generating a comprehensive pain score value in real time based on the pain-related characteristics, and generating electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and a baseline score value;

[0010] The patient's vagus nerve is electrically stimulated based on the electrical stimulation parameters.

[0011] As a further improvement of the present invention, a comprehensive pain score value is generated in real time based on the pain-related characteristics, including:

[0012] The sum of the first product of the EEG index feature and its coefficient and the second product of the heart rate variability feature and its coefficient is taken as the comprehensive pain score value.

[0013] As a further improvement of the present invention, the pain-related features further include a subjective pain score value, and a comprehensive pain score value is generated in real time based on the pain-related features, including:

[0014] The sum of the first product of the EEG index feature and its coefficient, the second product of the heart rate variability feature and its coefficient, and the third product of the subjective pain score value and its coefficient is taken as the comprehensive pain score value.

[0015] As a further improvement of the present invention, real-time acquisition of pain-related features includes:

[0016] Acquire alpha wave signals, beta wave signals and gamma wave signals in real time;

[0017] The EEG index characteristics were determined based on the ratio of α wave power to β wave power, and the ratio of γ wave power to baseline power.

[0018] As a further improvement of the present invention, the calculation formula of the EEG index feature is:

[0019]

[0020] Among them, EEG_score is the EEG index feature, k1 is the first weight coefficient, k2 is the second weight coefficient, P γ is the γ wave signal power, P baseline is the baseline power.

[0021] As a further improvement of the present invention, the electrical stimulation parameters include pulse intensity, stimulation frequency and pulse width.

[0022] As a further improvement of the present invention, the electrical stimulation parameters are generated in real time based on the target difference between the comprehensive pain score value and the baseline score value, including:

[0023] The sum of the minimum pulse intensity, the target difference and the product of the pulse intensity adjustment coefficient is used as the pulse intensity;

[0024] The sum of the baseline stimulation frequency, the target difference value and the product of the frequency adjustment coefficient is used as the stimulation frequency;

[0025] The sum of the minimum pulse width, the target difference and the product of the pulse width adjustment coefficient is used as the pulse width;

[0026] The target difference is the difference between the comprehensive pain score and the baseline pain score.

[0027] In a second aspect, the present invention further provides a neural electrical stimulation device based on EEG signals, comprising:

[0028] A pain data acquisition unit, used for acquiring pain-related features in real time, wherein the pain-related features include EEG index features and heart rate variability features;

[0029] a data processing unit, configured to generate a comprehensive pain score value in real time according to the pain-related characteristics, so as to generate electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and a baseline score value;

[0030] The electrical stimulation unit is used to electrically stimulate the patient's vagus nerve according to the electrical stimulation parameters.

[0031] In a third aspect, the present invention further provides a neural electrical stimulation system based on EEG signals, comprising:

[0032] EEG acquisition equipment, used to obtain EEG index data in real time;

[0033] A mobile device, used to generate a comprehensive pain score value according to the EEG index data and the heart rate variability characteristics, so as to generate electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and a baseline score value; and,

[0034] A neural electrical stimulation device is used to electrically stimulate the patient's vagus nerve according to the electrical stimulation parameters.

[0035] As a further improvement of the present invention, the mobile device comprises:

[0036] A signal processing unit, used for processing the EEG index data in real time to obtain EEG target data;

[0037] A data analysis unit is used to analyze the EEG target data in real time to obtain corresponding EEG index characteristics, and generate a comprehensive pain score value according to the EEG index characteristics, so as to generate electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and a baseline score value.

[0038] In a fourth aspect, the present invention provides a terminal device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described in the first aspect.

[0039] In a fifth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0040] The beneficial effects of the present invention are:

[0041] The neural electrical stimulation method based on EEG signals of the present invention generates a comprehensive pain score value in real time according to the pain-related features acquired in real time, and generates electrical stimulation parameters in real time according to the target difference between the comprehensive pain score value and the baseline score value, so as to electrically stimulate the patient's vagus nerve according to the electrical stimulation parameters. In this way, the neural electrical stimulation method of the present invention can generate a comprehensive pain score value in real time according to the acquired pain-related features, so as to generate electrical stimulation parameters in real time, so as to be able to dynamically adjust according to the patient's real-time neural activity, thereby improving the overall treatment effect. Therefore, the problem in the prior art that the electrical stimulation parameters cannot be dynamically adjusted according to the patient's real-time neural activity due to the fixation of the electrical stimulation parameters, thereby affecting the treatment effect, is solved.

[0042] Furthermore, the neural electrical stimulation device of the present invention electrically stimulates the patient's vagus nerve according to the electrical stimulation parameters generated by the mobile device processing and analyzing the real-time collected EEG signals, that is, the neural electrical stimulation device integrates the real-time collection and analysis functions of EEG signals to accurately monitor the changes in the patient's neural state, thereby further improving the safety and effectiveness of the treatment. Therefore, the problem in the prior art that it is difficult to accurately monitor the changes in the patient's neural state may lead to the risk of insufficient stimulation intensity or excessive stimulation, thereby affecting the safety and effectiveness of the treatment is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic flow chart of a method for electrical stimulation of a nerve based on an electroencephalogram signal according to an embodiment of the present invention;

[0044] Figure 2 A schematic flow chart of a method for electrical stimulation of nerves based on EEG signals according to another embodiment of the present invention;

[0045] Figure 3 is a schematic flow chart of a neural electrical stimulation device based on EEG signals according to an embodiment of the present invention;

[0046] Figure 4A schematic flow chart of a neural electrical stimulation system based on EEG signals according to another embodiment of the present invention;

[0047] Figure 5 It is a schematic diagram of a display interface 1 of a neural electrical stimulation system based on EEG signals of the present invention;

[0048] Figure 6 It is a schematic diagram of the display interface 2 of the neural electrical stimulation system based on EEG signals of the present invention;

[0049] Figure 7 It is a schematic diagram of display interface 3 of the neural electrical stimulation system based on EEG signals of the present invention;

[0050] Figure 8 Schematic diagram of display interface 4 of the neural electrical stimulation system based on EEG signals of the present invention;

[0051] Fig. 9 A topological structure diagram of a computer-readable storage medium disclosed in the present invention. DETAILED DESCRIPTION

[0052] The present invention is described in detail below in conjunction with the various embodiments shown in the accompanying drawings, but it should be noted that these embodiments are not limitations of the present invention, and any equivalent transformations or substitutions in functions, methods, or structures made by ordinary technicians in the field based on these embodiments are all within the scope of protection of the present invention.

[0053] The technical solutions provided by various embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0054] Embodiment 1:

[0055] Figure 1 This is a neural electrical stimulation method based on EEG signals (hereinafter referred to as "neural electrical stimulation method" or "electrical stimulation method" or "method"), which solves the problem in the prior art that the electrical stimulation parameters are fixed and cannot be dynamically adjusted according to the patient's real-time neural activity, thereby affecting the treatment effect. The method of this embodiment includes:

[0056] Step 102: Obtain pain-related features in real time, where the pain-related features include EEG index features and heart rate variability features.

[0057] like Figure 2 As shown in FIG. 1 , the specific operation process of obtaining EEG index characteristics in real time includes:

[0058] Step 202: Acquire α wave signals, β wave signals and γ wave signals in real time.

[0059] Step 204. Based on the ratio of α wave power to β wave power, and the ratio of γ wave power to baseline power, determine the EEG index feature EEG_score. The calculation process of the EEG index feature EEG_score is shown in Formula 1:

[0060] EEG_score = k1·(P γ / P baseline )+k2·(1-α / β) (Formula 1)

[0061] Among them, k1 is the first weight coefficient, k2 is the second weight coefficient, P γ is the γ wave signal power, P baseline is the baseline power (indicates the gamma band power of the patient in a pain-free or resting state, used to calculate the amplitude of the change in gamma band power in a painful state). α / β is used to measure the state of relaxation and pain. When the α / β ratio decreases, it means that the pain level has increased; conversely, when the α / β ratio increases, it means that the pain has been relieved.

[0062] Step 104: Generate a comprehensive pain score value in real time based on the pain-related features, and generate electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and the baseline score value.

[0063] In one embodiment, the specific operation process of "generating a comprehensive pain score value in real time based on pain-related features" in step 104 includes:

[0064] The sum of the first product of the EEG index feature EEG_score and its coefficient w1 and the second product of the heart rate variability feature HPV_score and its coefficient w2 is taken as the comprehensive pain score value Pain_score. The calculation process of the comprehensive pain score value Pain_score is shown in Formula 2:

[0065] Pain_score=w1·EEG_score+w2·HPV_score (Formula 2)

[0066] In another embodiment, the pain-related features further include a subjective pain score value, and the specific operation process of "generating a comprehensive pain score value in real time based on the pain-related features" in step 104 includes:

[0067] The sum of the first product of the EEG index feature EEG_score and its coefficient w1, the second product of the heart rate variability feature HPV_score and its coefficient w2, and the third product of the subjective pain score value VAS_score and its coefficient w3 is taken as the comprehensive pain score value Pain_score. The calculation process of the comprehensive pain score value Pain_score is shown in Formula 2:

[0068] Pain_score=w1·EEG_score+w3·VAS_score+w2·HPV_score (Formula 3)

[0069] In the above embodiment, the electrical stimulation parameters include pulse intensity I, stimulation frequency f and pulse width PWM. The specific content of "generating electrical stimulation parameters in real time based on the target difference between the comprehensive pain score value and the baseline score value" in step 104 includes:

[0070] (1) The sum of the minimum pulse intensity, the target difference and the product of the pulse intensity adjustment coefficient is taken as the pulse intensity I (mA), as shown in Formula 4:

[0071] I=I min +k3·(Pain_score-Pain_baseline) (Formula 4)

[0072] Among them, I min is the minimum pulse intensity, usually set to about 0.5mA, and its value is not limited to the range defined in this embodiment, and is set according to actual needs and working conditions. Pain_score is the comprehensive pain score value, and Pain_baseline is the baseline pain score value, which represents the pain of the patient in the absence of stimulation or in the initial state (for example, 4 points). k3 is the adjustment coefficient of the pulse intensity I (used to represent the pulse intensity increment caused by the pain change every minute, the increment unit is mA / minute, and it is assumed that its value is set to 0.1). The target difference is the difference between the comprehensive pain score value Pain_score and the baseline pain score value Pain_baseline.

[0073] Example: If I min =0.5mA, Pain_score=7, Pain_baseline=4, k3=0.1, then according to formula 4, the currently calculated pulse intensity I is 0.8mA. That is, when the patient's pain score rises from 4 to 7, the pulse intensity I will be automatically adjusted to 0.8mA to achieve the effect of enhanced stimulation.

[0074] (2) The sum of the baseline stimulation frequency, the target difference and the product of the frequency adjustment coefficient is taken as the stimulation frequency f, as shown in Formula 5:

[0075] f=f baseline +k4·(Pain_score-Pain_baseline) (Formula 5)

[0076] Among them, f baselineis the baseline stimulation frequency, generally used for the initial pain state, and is usually set to 20 Hz. Of course, its value is not limited to the range specified in this embodiment and is set according to actual needs and working conditions. k4 is the frequency adjustment coefficient, which represents the frequency increment caused by the pain change every 1 minute (unit: Hz / minute).

[0077] Example: If f baseline =20Hz, Pain_score=7, Pain_baseline=4, k4=5Hz, then according to Formula 5, the currently calculated stimulation frequency f is 35Hz. That is, when the pain score rises from 4 to 7, the stimulation frequency f will automatically adjust from 20Hz to 35Hz to cope with the increased pain.

[0078] (3) The sum of the minimum pulse width, the target difference and the product of the pulse width adjustment coefficient is taken as the pulse width PWM, as shown in Formula 6:

[0079] PWM=PWM min +k5·(Pain_score-Pain_baseline) (Formula 6)

[0080] Among them, PWM min is the minimum pulse width, and its value is usually set to 200 μs. Of course, its value is not limited to the range defined in this embodiment and is set according to actual needs and working conditions. k5 is the pulse width adjustment coefficient, which represents the pulse width increment caused by the pain change every 1 minute (unit: μs / minute).

[0081] Example: If PWM is set min =200μs, Pain_score=7, Pain_baseline=4, k5=50μs, then the currently calculated pulse width PWM is 350μs according to Formula 6. That is, when the pain score rises from 4 to 7, the pulse width is automatically adjusted to 350μs to increase the depth and coverage of the stimulation, thereby enhancing the pain relief effect.

[0082] Step 106: Electrically stimulate the patient's vagus nerve based on the electrical stimulation parameters.

[0083] The neural electrical stimulation method based on EEG signals of the present embodiment generates a comprehensive pain score value in real time according to the pain-related features acquired in real time, and generates electrical stimulation parameters in real time according to the target difference between the comprehensive pain score value and the baseline score value, so as to electrically stimulate the patient's vagus nerve according to the electrical stimulation parameters. In this way, the neural electrical stimulation method of the present embodiment can generate a comprehensive pain score value in real time according to the acquired pain-related features, so as to generate electrical stimulation parameters in real time, so as to be able to dynamically adjust according to the patient's real-time neural activity, thereby improving the overall treatment effect. Therefore, the problem in the prior art that the electrical stimulation parameters cannot be dynamically adjusted according to the patient's real-time neural activity due to the fixation of the electrical stimulation parameters, thereby affecting the treatment effect, is solved.

[0084] Furthermore, the neural electrical stimulation device of this embodiment electrically stimulates the patient's vagus nerve according to the electrical stimulation parameters generated by the mobile device processing and analyzing the real-time collected EEG signals, that is, the neural electrical stimulation device integrates the real-time collection and analysis functions of EEG signals to accurately monitor the changes in the patient's neural state, thereby further improving the safety and effectiveness of the treatment. Therefore, the problem in the prior art that it is difficult to accurately monitor the changes in the patient's neural state may lead to the risk of insufficient stimulation intensity or excessive stimulation, thereby affecting the safety and effectiveness of the treatment is solved.

[0085] Embodiment 2:

[0086] like Figure 3 As shown, this embodiment provides a neural electrical stimulation device 300 based on EEG signals, including a pain data acquisition unit 301, which is used to acquire pain-related characteristics in real time, and the pain-related characteristics include EEG index characteristics and heart rate variability characteristics; a data processing unit 302, which is used to generate a comprehensive pain score value in real time according to the pain-related characteristics, so as to generate electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and the baseline score value; an electrical stimulation unit 303, which is used to electrically stimulate the patient's vagus nerve according to the electrical stimulation parameters.

[0087] The neuroelectric stimulation device 300 based on EEG signals of this embodiment generates a comprehensive pain score value in real time according to the pain-related features acquired in real time by the pain data acquisition unit 301 through the data processing unit 302, and generates electrical stimulation parameters in real time according to the target difference between the comprehensive pain score value and the baseline score value, so as to electrically stimulate the patient's vagus nerve according to the electrical stimulation parameters through the electrical stimulation unit 303. In this way, the neuroelectric stimulation device 300 of this embodiment can generate a comprehensive pain score value in real time according to the acquired pain-related features, so as to generate electrical stimulation parameters in real time, so as to be able to dynamically adjust according to the patient's real-time neural activity, thereby improving the overall treatment effect. Therefore, the problem in the prior art that the electrical stimulation parameters cannot be dynamically adjusted according to the patient's real-time neural activity due to the fixation of the electrical stimulation parameters, thereby affecting the treatment effect, is solved.

[0088] It should be noted that, for the technical solutions of the electroencephalographic signal-based neural electrical stimulation device of this embodiment and the same parts as those in the first embodiment, please refer to the first embodiment, which will not be described in detail here.

[0089] Embodiment three:

[0090] like Figure 4 As shown, the present embodiment further provides a neuroelectric stimulation system 400 based on EEG signals, comprising: an EEG acquisition device 41, for acquiring EEG index data in real time; a mobile device 42 (referred to as "PAD" or "PAD device"), for generating a comprehensive pain score value based on the EEG index data and heart rate variability characteristics, so as to generate electrical stimulation parameters in real time based on the target difference between the comprehensive pain score value and the baseline score value; and a neuroelectric stimulation device 43, for electrically stimulating the patient's vagus nerve according to the electrical stimulation parameters.

[0091] It should be noted that the EEG acquisition device 41 uses dry electrodes or wet electrodes attached to the forehead, parietal lobe or temporal lobe of the patient's scalp and other suitable parts to record brain electrical signals in real time. It includes an EEG signal acquisition module 412 for collecting EEG signals and a wireless communication module 411 connected to the mobile device 42. Among them, the collected EEG signals (EEG) mainly include δ (0.5-4Hz), θ (4-8Hz), α (8-13Hz), β (13-30Hz), and γ (30-50Hz) frequency bands. Alpha waves and beta waves are closely related to relaxation and pain perception; gamma waves will be significantly enhanced during pain perception. Specifically, the acquisition frequency range of the EEG acquisition device 41 is 0.5-50Hz; the wireless transmission rate is not less than 1Mbps to ensure real-time performance. The EEG signal processing process collected by the EEG acquisition device 41 is as follows.

[0092] EEG signal amplification and preprocessing:

[0093] Low noise amplifier: improves EEG signal strength;

[0094] Bandpass filtering (0.5-50 Hz): removes power frequency (50 Hz) interference and low-frequency drift noise to extract pain-related feature values ​​through FFT or time domain analysis.

[0095] Wireless transmission: Use Bluetooth 5.0 or Wi-Fi low-power communication module to transmit EEG data to the PAD device in real time.

[0096] The high sensitivity of signal acquisition and the stability of wireless data transmission technology achieved by the EEG acquisition device 41 directly determine the response speed and treatment effect of the entire neural electrical stimulation system 400.

[0097] In the above embodiment, the mobile device 42 includes a signal processing unit 421, which is used to process the EEG index data in real time to obtain EEG target data. Specifically, it includes:

[0098] EEG signal processing and data analysis:

[0099] Noise removal: ICA (independent component analysis) is used to separate artifacts such as electromyography and eye blinking;

[0100] Adaptive filtering: further optimizes signal quality.

[0101] Pain-related EEG target data extraction:

[0102] α / β ratio: measures relaxation and tension;

[0103] Changes in γ-band power: reflects pain intensity;

[0104] ERP indicators (such as P300, N100): monitor event-related potentials to reflect the intensity of pain perception.

[0105] The signal processing unit 421 filters, denoises and extracts features of the EEG signal, accurately analyzes the EEG signal, and identifies feature values ​​related to pain.

[0106] The mobile device 42 also includes a data analysis unit 422, which is used to analyze EEG target data in real time to obtain corresponding EEG index characteristics, and generate a comprehensive pain score value based on the EEG index characteristics, so as to generate electrical stimulation parameters in real time based on the target difference between the comprehensive pain score value and the baseline score value. In this way, the data analysis unit 422 can dynamically generate personalized stimulation parameters according to the patient's real-time pain state to further improve the treatment effect. Among them, the process of obtaining EEG index characteristics refers to the calculation process of formula 1 in Example 1, and the process of generating a comprehensive pain score value based on EEG index characteristics refers to the calculation process of formula 2 in Example 1, which will not be repeated here. In a specific embodiment, the stimulation parameters generated by the mobile device 42 are as follows.

[0107] Stimulation parameters

[0108] Pulse intensity: adjusted according to the patient's sensitivity, ranging from 0.5 to 3 mA;

[0109] Stimulation frequency: 10-100 Hz;

[0110] Pulse width: 200~500μs.

[0111] The neural electrical stimulation system 400 of this embodiment implements closed-loop control, collects EEG signals every 100 milliseconds, continuously adjusts stimulation parameters, and generates corresponding electrical stimulation signals based on the stimulation parameters transmitted by the PAD to ensure that they are accurately applied to the patient's vagus nerve. Its response speed and accuracy of signal output directly affect the treatment effect.

[0112] The mobile device also includes a data display unit 423 for displaying data such as EEG changes, pain index and treatment progress, such as Figures 5 to 7 The figure shows a graphical interface for doctors or patients, and the stimulation scheme can be adjusted manually or automatically, supporting treatment scheme selection and parameter adjustment. The mobile device 42 also includes an electrical stimulation instruction generation unit 424 to generate electrical stimulation parameters in real time based on the target difference between the comprehensive pain score value and the baseline score value. The details are as follows:

[0113] Display and interaction (PAD displays real-time data in a graphical interface)

[0114] EEG waveform (by frequency band);

[0115] Pain index (calculated based on EEG characteristics);

[0116] Current stimulation parameters (frequency, pulse width, intensity).

[0117] User Operation Mode

[0118] Automatic mode: the system automatically adjusts stimulation parameters based on pain scores;

[0119] Manual mode: Users can fine-tune parameters based on their subjective feelings.

[0120] Vagus nerve stimulation (VNS) and closed-loop control

[0121] Stimulation Target: Non-invasive vagus nerve stimulation (tVNS) modulates the cerebral cortex's perception of pain via branches of the vagus nerve in the cavum concha or tragus.

[0122] Stimulation signal output: PAD sends the calculated stimulation parameters via Bluetooth / Wi-Fi;

[0123] The neuroelectric stimulation device generates corresponding pulse current and acts on the patient's vagus nerve through electrodes.

[0124] Closed-loop control mechanism

[0125] Real-time monitoring: continuously collect EEG and analyze EEG changes before and after stimulation;

[0126] Dynamic adjustment: If pain scores or EEG indicators do not improve, stimulation parameters are automatically adjusted;

[0127] Safety mechanism: If abnormal fluctuations in EEG occur (such as overexcitement), the system reduces the stimulation intensity or suspends treatment.

[0128] The neural electrical stimulation device 43 includes a wireless communication module 431 (communicating with the wireless communication module 425 of the mobile device 42) and an electrical stimulation signal generating unit 432, which is used to generate an electrical stimulation signal according to the electrical stimulation parameters to electrically stimulate the patient's vagus nerve. Specifically, the electrical stimulation signal generating unit 432 includes a stimulation signal generator (used to receive a software drive signal from the mobile device and generate a stimulation signal of a specific frequency, intensity and pulse width according to the instruction) and a stimulation electrode (contacting the patient's target nerve and transmitting the electrical stimulation signal to apply precise electrical stimulation to the patient's vagus nerve).

[0129] In this embodiment, the EEG acquisition device 42 and the neural electrical stimulation device 43 are both lightweight and easy to carry and wear, and wireless communication such as Bluetooth or Wi-Fi is used to achieve seamless connection between the PAD and other devices, reducing cable interference. The system 400 of this embodiment can be used for professional treatment in medical institutions and can also be conveniently operated in a home environment, achieving multi-scenario applicability.

[0130] It should be understood that this embodiment introduces a real-time EEG data feedback mechanism in the management of chronic pain and nerve-related diseases to achieve accurate and efficient pain relief. The system of this embodiment can capture the changes in the patient's EEG signals in real time, dynamically generate stimulation parameters suitable for the patient's individual needs, relieve pain while reducing the patient's psychological burden, and create favorable conditions for subsequent rehabilitation treatment.

[0131] During the treatment process, the patient's perception of pain and the electrical stimulation intensity of the device need to be effectively matched. The system of this embodiment analyzes EEG signals, dynamically monitors the patient's pain state and neural activity pattern, and forms a closed-loop control mechanism. This mechanism can significantly reduce the side effects caused by fixed stimulation parameters, while helping patients establish a correct understanding of pain, reduce fear of pain, and improve tolerance and trust in treatment.

[0132] Through the friendly interactive interface on the PAD, patients can intuitively view their pain status and treatment process, and participate in the selection and adjustment of treatment parameters, which enhances the patient's sense of participation and trust. By dynamically adjusting treatment parameters, the patient's discomfort with electrical stimulation is also reduced, thereby improving treatment compliance.

[0133] This embodiment connects the EEG acquisition device and the neural electrical stimulation device to a mobile device (such as a PAD) through wireless communication, which greatly reduces the complex cable connections and redundant hardware configurations in traditional devices. The miniaturized and lightweight design makes the device easy to carry and deploy, especially suitable for convenient clinical operations and home rehabilitation scenarios.

[0134] In order to further improve the patient's rehabilitation experience, this embodiment integrates the EEG signal acquisition, analysis and electrical stimulation control system into an integrated device through an integrated module design, thereby reducing the complexity of the equipment and improving operational efficiency. At the same time, combined with personalized treatment modes and safe and reliable operating procedures, patients can complete pain management in a more comfortable treatment environment, thereby promoting the overall rehabilitation process. At the same time, the equipment uses reusable electrodes and a standardized modular design, which is easy to disassemble and clean, and meets the cleaning and disinfection requirements of medical equipment. It supports the access of a variety of EEG signal acquisition devices and neural electrical stimulation modules, with strong compatibility and a wide range of applications.

[0135] In response to the diverse needs of medical institutions and personal use scenarios, this embodiment ensures that the device is easy to carry and easy to operate through miniaturization and intelligent design. At the same time, the device has highly integrated functions and can be quickly deployed and put into use in different environments. This not only helps to expand the application scope of the device in chronic pain management, but also provides a new solution for acute pain treatment and postoperative rehabilitation.

[0136] It should be noted that, for the technical solutions of the neural electrical stimulation system based on EEG signals in this embodiment and the same parts as those in the first embodiment, please refer to the first embodiment, which will not be described in detail here.

[0137] Embodiment 4:

[0138] The embodiment of the present invention further provides a terminal device, which may include a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program is executed by the processor to implement the above Figure 1 The various processes of the embodiment of the neural electrical stimulation method based on EEG signals shown in the figure can achieve the same technical effect, and will not be described again here to avoid repetition.

[0139] Embodiment five:

[0140] Combination Fig. 9 As shown, this embodiment also discloses a specific implementation of a computer-readable storage medium 900. The computer-readable storage medium 900 can be configured in whole or in part in a physical computer, server, cluster server or data center.

[0141] In this embodiment, the computer-readable storage medium 900 stores computer program instructions 901. When the computer program instructions 901 are read and executed by a processor 902, the steps of the neural electrical stimulation method based on EEG signals disclosed in the first embodiment are executed.

[0142] Optionally, the computer-readable storage medium 900 can be configured as a server, and the server runs on a physical device for building a private cloud, a hybrid cloud, or a public cloud. At the same time, the computer-readable storage medium 900 can also be configured as a random access memory (Random Access Memory, RAM), a read-only memory (Read Only Memory, ROM), a programmable read-only memory (Programmable Read-Only Memory, PROM), an erasable read-only memory (ErasableProgrammable Read-Only Memory, EPROM), an electrically erasable read-only memory (Electric ErasableProgrammable Read-Only Memory, EEPROM), etc.

[0143] The computer-readable storage medium 900 is used to store programs. After receiving the execution instruction, the processor 902 executes the neural electrical stimulation method based on EEG signals disclosed in the first embodiment.

[0144] At the same time, the processor 902 disclosed in this embodiment may be an integrated circuit chip with signal processing capabilities. The processor 902 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention may be implemented or executed. The general-purpose processor may be a microprocessor or the general-purpose processor may also be any conventional processor.

[0145] For the technical solutions of the computer-readable storage medium 900 disclosed in this embodiment that are the same as those in Embodiment 1 and / or Embodiment 2, please refer to Embodiment 1 and / or Embodiment 2, which will not be repeated here.

[0146] The series of detailed descriptions listed above are only specific descriptions of feasible implementation methods of the present invention. They are not intended to limit the scope of protection of the present invention. Any equivalent implementation methods or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

[0147] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0148] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A method for neural electrical stimulation based on EEG signals, characterized in that: The method comprises: Acquiring pain-related features in real time, wherein the pain-related features include EEG index features and heart rate variability features; Generating a comprehensive pain score value in real time based on the pain-related characteristics, and generating electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and a baseline score value; The patient's vagus nerve is electrically stimulated based on the electrical stimulation parameters.

2. The method for electrical stimulation of nerves according to claim 1, characterized in that: Generating a comprehensive pain score value in real time based on the pain-related characteristics, including: The sum of the first product of the EEG index feature and its coefficient and the second product of the heart rate variability feature and its coefficient is taken as the comprehensive pain score value.

3. The method for electrical stimulation of nerves according to claim 1, characterized in that: The pain-related features also include a subjective pain score value, and a comprehensive pain score value is generated in real time based on the pain-related features, including: The sum of the first product of the EEG index feature and its coefficient, the second product of the heart rate variability feature and its coefficient, and the third product of the subjective pain score value and its coefficient is taken as the comprehensive pain score value.

4. The method for electrical stimulation of nerves according to claim 1, characterized in that: Real-time acquisition of pain-related features, including: Acquire alpha wave signals, beta wave signals and gamma wave signals in real time; The EEG index characteristics were determined based on the ratio of α wave power to β wave power, and the ratio of γ wave power to baseline power.

5. The method for electrical nerve stimulation according to claim 4, characterized in that: The calculation formula of the EEG index feature is: Among them, EEG_score is the EEG index feature, k1 is the first weight coefficient, k2 is the second weight coefficient, P γ is the γ wave signal power, P baseline is the baseline power.

6. The method for electrical stimulation of nerves according to any one of claims 1 to 5, characterized in that: The electrical stimulation parameters include pulse intensity, stimulation frequency and pulse width.

7. The method for electrical stimulation of nerves according to claim 6, characterized in that: Generating electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and the baseline score value, including: The sum of the minimum pulse intensity, the target difference and the product of the pulse intensity adjustment coefficient is used as the pulse intensity; The sum of the baseline stimulation frequency, the target difference value and the product of the frequency adjustment coefficient is used as the stimulation frequency; The sum of the minimum pulse width, the target difference and the product of the pulse width adjustment coefficient is used as the pulse width; The target difference is the difference between the comprehensive pain score and the baseline pain score.

8. A neural electrical stimulation device based on EEG signals, characterized in that: include: A pain data acquisition unit, used for acquiring pain-related features in real time, wherein the pain-related features include EEG index features and heart rate variability features; a data processing unit, configured to generate a comprehensive pain score value in real time according to the pain-related characteristics, so as to generate an electrical stimulation parameter in real time based on a target difference between the comprehensive pain score value and a baseline score value; The electrical stimulation unit is used to electrically stimulate the patient's vagus nerve according to the electrical stimulation parameters.

9. A neural electrical stimulation system based on EEG signals, characterized in that: include: EEG acquisition equipment, used to obtain EEG index data in real time; A mobile device, used to generate a comprehensive pain score value according to the EEG index data and the heart rate variability characteristics, so as to generate electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and a baseline score value; and, A neural electrical stimulation device is used to electrically stimulate the patient's vagus nerve according to the electrical stimulation parameters.

10. The neural electrical stimulation system according to claim 9, characterized in that: The mobile device comprises: A signal processing unit, used for processing the EEG index data in real time to obtain EEG target data; A data analysis unit is used to analyze the EEG target data in real time to obtain corresponding EEG index characteristics, and generate a comprehensive pain score value according to the EEG index characteristics, so as to generate electrical stimulation parameters in real time based on a target difference between the comprehensive pain score value and a baseline score value.

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