Non-invasive electrode closed-loop feedback stellate ganglion block electrical stimulation device

Abstract

The embodiment of the invention relates to the technical field of instrument data control, and discloses a non-invasive electrode closed-loop feedback stellate ganglion block electrical stimulation device. According to the device, a control module carries out closed-loop control processing on initial stimulation parameters and carries out adjustment processing on stimulation frequency and intensity to obtain an optimal control parameter combination; the acquisition module performs multi-dimensional acquisition processing on the physiological parameters to obtain a monitoring data set and performs threshold judgment processing to obtain a stimulation control instruction; the analysis module performs dynamic analysis processing on the monitoring data in the stimulation process to obtain a parameter adjustment strategy, and performs optimization processing on the stimulation parameters according to the parameter adjustment strategy to obtain steady-state control parameters; and the evaluation module carries out integration analysis processing on the control process data to obtain a working state evaluation index, and carries out classified statistical processing according to the evaluation index to obtain a parameter optimization suggestion. According to the invention, adaptive adjustment of the stimulation parameters and intelligent evaluation of the system operation state are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of instrument data control, and particularly relates to a non-invasive electrode closed-loop feedback stellate ganglion block electric stimulation device. BACKGROUND

[0002] In the medical field, neural electrical stimulation technology is widely used in the treatment and rehabilitation of various diseases, especially in pain management, neuromodulation, and treatment of functional disorders. Stellate ganglion block (SGB) as a common neuromodulation technique is often used to treat diseases such as migraine, cervicogenic headache, and upper extremity sympathetic syndrome. The stellate ganglion is an important node of the sympathetic nervous system, and blocking this ganglion can effectively regulate the overexcitation of the sympathetic nervous system, thereby relieving related symptoms. However, traditional stellate ganglion block injection methods have many problems and deficiencies.

[0003] (1) Traditional stellate ganglion block often uses injection method, that is, under the guidance of imaging (such as X-ray or ultrasound), local anesthetic is injected near the stellate ganglion, thereby blocking the conduction of the sympathetic nervous system. Injection method is an invasive operation, which requires a needle to be inserted into the patient's body. This process not only increases the patient's pain and discomfort, but also may cause a series of complications such as bleeding, nerve damage, and infection. Especially for patients who need to perform block treatment repeatedly for a long time, the physical burden and psychological pressure brought by this invasive operation are particularly significant.

[0004] (2) The effect of injection block is often affected by many factors, such as the type, dose, and injection site of the injected drug. The uncertainty of these factors leads to the fact that the block effect may vary from person to person, and even in some cases, the expected therapeutic effect may not be achieved. In addition, the effect of injection block is usually short-term, and regular repeated treatment is needed, which further increases the patient's pain and medical costs.

[0005] (3) With the continuous development of medical technology, non-invasive neural electrical stimulation technology has gradually emerged and become an important choice to replace invasive stimulation methods. Non-invasive neural electrical stimulation devices transmit electrical stimulation signals to the target neural region through surface electrodes without the need for surgical implantation, greatly reducing the patient's pain and risk. However, existing non-invasive neural electrical stimulation devices still have many technical defects.

[0006] Firstly, existing non-invasive neural electrical stimulation devices mostly adopt open-loop control mode, that is, stimulation parameters (such as frequency, pulse width, intensity, etc.) are pre-set or adjusted according to a fixed program, lacking real-time adjustment mechanism, and unable to dynamically optimize according to the actual physiological response of the patient. This leads to the fact that the stimulation effect may vary from person to person, and even in some cases, the expected therapeutic effect may not be achieved. Secondly, electrode positioning and placement is also a big challenge faced by existing non-invasive neural electrical stimulation devices. Due to the lack of accurate positioning and guidance means, the placement of the electrode often depends on the experience and feeling of the doctor, increasing the complexity and uncertainty of the equipment debugging. This not only affects the accuracy and reliability of the stimulation effect, but also may increase the risk of the patient. In addition, existing non-invasive neural electrical stimulation devices also have deficiencies in monitoring. They can often only collect single-dimensional data (such as heart rate, temperature, etc.), and fail to achieve multi-parameter collaborative analysis and comprehensive judgment. This limits the system's ability to comprehensively evaluate and optimize the stimulation effect, and also affects the targeting and effectiveness of the treatment. Moreover, there is no electrical stimulation device on the market that uses kilohertz (KHz) frequency for nerve blockage.

[0007] In summary, both existing invasive and non-invasive neural electrical stimulation devices have many technical defects and deficiencies, and cannot meet the extensive needs and safety requirements of clinical applications. Therefore, developing a non-invasive neural electrical stimulation device with real-time closed-loop feedback control, accurate electrode positioning and placement, multi-dimensional parameter monitoring, and high-frequency electrical stimulation function has important clinical significance and application prospects. The present application is an innovative solution to this technical problem. SUMMARY

[0008] One object of the present application is to provide a non-invasive electrode closed-loop feedback stellate ganglion block electrical stimulation device, at least to realize adaptive adjustment of stimulation parameters and intelligent evaluation of system running state.

[0009] To achieve the above object, some embodiments of the present application provide the following technical solutions:

[0010] The present application provides a non-invasive electrode closed-loop feedback stellate ganglion block electrical stimulation device, comprising:

[0011] The processing module is configured to initialize the stimulation parameter and physiological parameter detection module, obtain a parameter set containing an initial stimulation frequency, an initial stimulation pulse width, and an initial stimulation current intensity, and a reference data set containing a basic heart rate value and an initial body surface temperature value.

[0012] The positioning module is configured to receive positioning data of the target region obtained by the external ultrasonic device through ultrasonic scanning, and perform position planning processing on the electrode according to the positioning data to obtain electrode placement information.

[0013] a control module for closed-loop control processing of the initial stimulation parameters, adjusting the stimulation frequency and intensity through real-time heart rate data and temperature data to obtain an optimal control parameter combination;

[0014] a collection module for multi-dimensional collection and processing of physiological parameters to obtain a monitoring data set containing real-time heart rate data and body surface temperature data, and performing threshold judgment processing on the monitoring data set to obtain a stimulation control instruction;

[0015] an analysis module for dynamic analysis and processing of monitoring data during stimulation to obtain a parameter adjustment strategy, and optimizing the stimulation parameters according to the parameter adjustment strategy to obtain a steady-state control parameter;

[0016] an evaluation module for integrated analysis and processing of control process data to obtain a working state evaluation index, and performing classified statistical processing on the evaluation index to obtain a parameter optimization suggestion.

[0017] Compared with the related art, in the scheme provided by the embodiment of the application, the initialization processing of the stimulation parameters and the physiological parameters is realized by the processing module, which can effectively establish the baseline parameter set and provide reliable reference basis for subsequent closed-loop control; the positioning module realizes accurate positioning and planning of electrode placement by performing ultrasonic scanning on the target region by an external ultrasonic device and performing positioning data analysis, which significantly improves the accuracy of electrode placement and the stability of system operation; the control module establishes a closed-loop control mechanism based on heart rate data and temperature data, realizes real-time optimization adjustment of the stimulation parameters, and enables the system to have self-adaptive control capability; the acquisition module realizes real-time acquisition of multi-dimensional physiological parameters such as heart rate and temperature, and forms a control instruction through threshold judgment, which enhances the safety and controllability of system operation; the analysis module dynamically analyzes the monitoring data and generates a parameter adjustment strategy, which realizes continuous optimization of the control parameters and improves the accuracy of system control; the evaluation module integrates and analyzes the control process data to form a working state evaluation index and a parameter optimization suggestion, which enables the system to have intelligent evaluation and decision-making capability. Overall, the application adopts a modular design idea, establishes a complete closed-loop control system through the collaborative work of multiple functional modules, the information interaction between the modules is smooth, the data analysis is comprehensive, the reliability of system operation is ensured while realizing accurate control; in addition, the control device of the application improves the control accuracy through multi-dimensional parameter acquisition, dynamic analysis and intelligent evaluation and other technical means, and also enhances the adaptability and scalability of the system, which provides technical support for the continuous optimization of the control device. The control device of the application not only solves the problems of inflexible parameter adjustment, single monitoring dimension and insufficient safety protection in the traditional open-loop control, but also realizes real-time monitoring and intelligent adjustment of the system operation state through the implementation of the closed-loop control strategy, which greatly improves the overall performance and working reliability of the control device. BRIEF DESCRIPTION OF DRAWINGS

[0018] One or more embodiments are illustrated by way of example in the drawings in which like reference numerals indicate like elements, and in which:

[0019] Figure 1 An embodiment of the non-invasive electrode closed-loop feedback stellate ganglion block electric stimulation device in the embodiment of the application is shown in the figure.

[0020] Figure 2 An embodiment of the non-invasive electrode closed-loop feedback stellate ganglion block electric stimulation device in the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0021] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the following will be combined with the accompanying drawings for the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0022] The present inventors found through previous in-depth research that kilohertz frequency electrical signals can block the conduction of nerves and do not have obvious effects on nerve structures, but different thicknesses of nerves require different blocking frequencies. Meanwhile, the research also found that non-invasive electrodes can achieve similar blocking effects of invasive needle electrodes by increasing current intensity. Therefore, the present application proposes a non-invasive electrode closed-loop feedback stellate ganglion block electrical stimulation device, which uses kilohertz frequency electrical signals for nerve block and achieves similar blocking effects of invasive needle electrodes by increasing current intensity, solving the deficiencies of traditional electrical stimulation devices in parameter adjustment, monitoring dimension, safety protection and the like and improving the safety and effectiveness of treatment.

[0023] Specifically, the present application provides a non-invasive electrode closed-loop feedback stellate ganglion block electrical stimulation device, which can realize adaptive adjustment of stimulation parameters and intelligent evaluation of system operation state, adopts a modular design idea, establishes a complete closed-loop control system through cooperative work of multiple functional modules. The positioning module realizes accurate positioning and planning of electrode placement through ultrasonic scanning of the target area by an external ultrasonic device, improving the accuracy of electrode placement and the stability of system operation. The control module establishes a closed-loop control mechanism based on heart rate data and temperature data, realizes real-time optimization adjustment of stimulation parameters, and enables the system to have adaptive control capability. The acquisition module realizes real-time acquisition of multi-dimensional physiological parameters such as heart rate and temperature, and forms control instructions through threshold judgment, enhancing the safety and controllability of system operation. The analysis module dynamically analyzes the monitoring data, generates parameter adjustment strategies, realizes continuous optimization of control parameters, and improves the accuracy of system control. The evaluation module integrates and analyzes the control process data, forms working state evaluation indexes and parameter optimization suggestions, and enables the system to have intelligent evaluation and decision-making capability.

[0024] First embodiment

[0025] The first embodiment of the present application relates to a non-invasive electrode closed-loop feedback stellate ganglion block electrical stimulation device. As shown in Figure 1 An embodiment of the non-invasive electrode closed-loop feedback stellate ganglion block electrical stimulation device includes:

[0026] The processing module 101 is configured to initialize the stimulation parameter and physiological parameter detection module, to obtain a parameter set containing an initial stimulation frequency, an initial stimulation pulse width, an initial stimulation current intensity, and a baseline data set containing a basic heart rate value and an initial body surface temperature value.

[0027] The positioning module 102 is configured to receive positioning data obtained by an external ultrasound device performing ultrasound scanning on a target region, and to perform position planning processing on the electrode based on the positioning data, to obtain electrode placement information.

[0028] The control module 103 is configured to perform closed-loop control processing on the initial stimulation parameters, to adjust the stimulation frequency and intensity based on real-time heart rate data and temperature data, and to obtain an optimal control parameter combination.

[0029] The acquisition module 104 is configured to perform multi-dimensional acquisition processing on physiological parameters, to obtain a monitoring data set containing real-time heart rate data and body surface temperature data, to perform threshold judgment processing based on the monitoring data set, and to obtain a stimulation control instruction.

[0030] The analysis module 105 is configured to perform dynamic analysis processing on the monitoring data during stimulation, to obtain a parameter adjustment strategy, to perform optimization processing on the stimulation parameters based on the parameter adjustment strategy, and to obtain a steady-state control parameter.

[0031] The evaluation module 106 is configured to perform integrated analysis processing on control process data, to obtain a working state evaluation index, to perform classified statistical processing based on the evaluation index, and to obtain a parameter optimization suggestion.

[0032] Specifically, the non-invasive electrode closed-loop feedback stellate ganglion block electric stimulation device realizes its functions through six core modules. The processing module 101 initializes the system, specifically including setting the initial stimulation frequency to 8000 Hz, the initial stimulation pulse width to 0.5 ms, and the initial stimulation current intensity to 0.5 mA, and recording the basic heart rate value and the initial body surface temperature value of the patient as baseline data. The positioning module 102 uses the ultrasound scanning technology of an external ultrasound device to locate the stellate ganglion region, obtains spatial structure data of the neck blood vessels and nerves, and plans the optimal attachment position of the electrode based on these data. The control module 103 executes a closed-loop control strategy, monitors the heart rate and temperature data in real time, and when the heart rate is reduced by less than 10%, increases the stimulation frequency by 10% every 10 minutes; when the temperature rises by less than 1℃, the corresponding stimulation frequency is increased. The acquisition module 104 continuously acquires multi-dimensional physiological parameters, including heart rate signals and body surface temperature, and sets the safe threshold range of heart rate to 60-100 times / minute.

[0033] The analysis module 105 dynamically analyzes the collected monitoring data, calculates the heart rate stability index and the temperature stability index, and determines the optimal parameter adjustment strategy when the heart rate variation is maintained within ±10% and the temperature rises steadily. The evaluation module 106 systematically analyzes the data of the entire control process, records the heart rate variation curve, temperature variation trend, and parameter adjustment process, and generates parameter optimization suggestions.

[0034] For example: In a certain use scenario, after the processing module 101 initially sets the stimulation parameters, the positioning module 102 uses ultrasonic positioning to determine the target ganglion position coordinates (x=45mm, y=32mm, z=28mm). After the control module 103 is started, it first outputs a rated frequency stimulation, for example 8000Hz, while monitoring the user's heart rate and facial temperature. If the facial temperature rises by less than 1℃ at this time, the stimulation frequency is increased by 10% every 5 minutes until the temperature rises by 1℃, at which point the stimulation frequency is no longer increased, at which point the purpose of blocking the conduction of the cardiac ganglion is achieved. During the increase in stimulation frequency and temperature rise, if the heart rate is monitored to be less than 50 times / minute, the current intensity is gradually reduced until it stops. The entire control process embodies the closed-loop regulation characteristics and safety protection mechanism of the system. The analysis module 105 records that the heart rate fluctuation is maintained within ±10% within 30 minutes.

[0035] In the embodiments of the application, the initialization processing of the stimulation parameters and the physiological parameters is realized by the processing module, which can effectively establish a set of reference parameters and provide reliable reference for subsequent closed-loop control; the positioning module realizes accurate positioning and planning of electrode placement by ultrasonic scanning of the target area by an external ultrasonic device and positioning data analysis, which significantly improves the accuracy of electrode placement and the stability of system operation; the control module establishes a closed-loop control mechanism based on heart rate data and temperature data, realizes real-time optimization and adjustment of the stimulation parameters, and enables the system to have adaptive control capability; the acquisition module realizes real-time acquisition of multi-dimensional physiological parameters such as heart rate and temperature, and forms control instructions through threshold judgment, which enhances the safety and controllability of system operation; the analysis module dynamically analyzes the monitoring data and generates parameter adjustment strategies, realizes continuous optimization of control parameters, and improves the accuracy of system control; the evaluation module integrates and analyzes the control process data to form working state evaluation indexes and parameter optimization suggestions, so that the system has intelligent evaluation and decision-making capability. Overall, the application adopts a modular design idea, establishes a complete closed-loop control system through the cooperative work of multiple functional modules, the information interaction between the modules is smooth, the data analysis is comprehensive, the reliability of system operation is ensured while realizing accurate control; in addition, the control device of the application introduces ultrasonic positioning, multi-dimensional parameter acquisition, dynamic analysis and intelligent evaluation and other technical means, which not only improves the control accuracy, but also enhances the adaptability and scalability of the system, providing technical support for the continuous optimization of the control device. The control device of the application not only solves the problems of inflexible parameter adjustment, single monitoring dimension and insufficient safety protection in traditional open-loop control, but also realizes real-time monitoring and intelligent adjustment of system operation state through the implementation of closed-loop control strategy, greatly improving the overall performance and working reliability of the control device.

[0036] Second embodiment

[0037] The processing module 101 is specifically configured to:

[0038] (1) set the initial stimulation frequency to obtain an initial stimulation frequency value of 8000 Hz, and set the initial stimulation pulse width to obtain an initial stimulation pulse width value of 0.5 ms;

[0039] (2) set the initial stimulation current intensity to obtain an initial stimulation current intensity value of 0.5 mA, and start the physiological parameter detection module to obtain the working state information of the detection module;

[0040] (3) collect the heart rate data to obtain a basic heart rate value, and collect the body surface temperature data to obtain an initial body surface temperature value;

[0041] (4) Threshold setting processing is performed on the basic heart rate value to obtain a lower threshold value of 50 beats per minute and an upper threshold value of 100 beats per minute, and baseline recording processing is performed on the initial body surface temperature value to obtain temperature baseline data;

[0042] (5) Setting processing is performed on the stimulation parameter adjustment interval to obtain an adjustment cycle value of 10 minutes, and setting processing is performed on the stimulation parameter adjustment amplitude to obtain an adjustment step value of 10%;

[0043] (6) Data integration processing is performed on the basic heart rate value, the initial body surface temperature value, the threshold value parameter, and the adjustment parameter to obtain a parameter set and a reference data set.

[0044] Specifically, the processing module 101 is responsible for performing the initialization operation of the system. The stimulation parameters are set based on the initial value of the stimulation frequency, which is set to 8000 Hz. This frequency value is a reference frequency determined based on the electrophysiological characteristics of the stellate ganglion. At the same time, the stimulation pulse width is set to 0.5 ms, which can ensure sufficient charge transfer efficiency while avoiding tissue damage. When setting the current parameter, the initial stimulation current intensity is set to 0.5 mA, which is a balance point between safety and effectiveness. Subsequently, the physiological parameter detection module is started, and the working state of each sensor is confirmed through the sampling circuit and the signal conditioning circuit. After the physiological parameter detection module is started, the heart rate data of 60 seconds is first collected for average calculation to obtain the basic heart rate value, and the body surface temperature readings of 30 seconds are recorded for average calculation as the initial body surface temperature value.

[0045] For the heart rate parameter, a strict threshold range is set based on clinical safety considerations: the lower threshold value is 50 beats per minute, and the upper threshold value is 100 beats per minute. Exceeding this range will trigger a safety protection mechanism. For the body surface temperature data, the initial body surface temperature value collected is used as a baseline for subsequent temperature change calculations. In terms of control parameters, the adjustment cycle of the stimulation parameter is set to 10 minutes, which is sufficient to observe the changes in physiological response. The amplitude of each adjustment is set to 10%, which balances the control accuracy and adjustment speed.

[0046] For example: the processing module 101 sets the initial frequency of 8000 Hz and the pulse width of 0.5 ms at startup, and sets the current intensity of 0.5 mA. Subsequently, the physiological parameter detection module starts to work, and collects the heart rate data points within 60 seconds, such as 6000 data points obtained when the sampling frequency is 100 Hz, and the basic heart rate value of 72 times per minute is obtained by averaging calculation; at the same time, 30 seconds of temperature data is collected, and 300 data points are obtained when the sampling frequency is 10 Hz, and the average value is calculated to obtain the initial body surface temperature of 36.5℃. The system automatically records these baseline data, and sets the heart rate threshold range (50-100 times / minute), the adjustment period (10 minutes) and the adjustment step (10%). Finally, all parameters are integrated into a data set, including stimulation parameter group (8000 Hz, 0.5 ms, 0.5 mA), baseline physiological value (72 times / minute, 36.5℃), threshold parameter (50-100 times / minute) and adjustment parameter (10 minutes, 10%), which provides a complete reference basis for subsequent closed-loop control.

[0047] Third embodiment

[0048] The positioning module 102 is specifically used for:

[0049] (1) The target area is scanned by an external ultrasonic device to obtain ultrasonic image data, and the ultrasonic image data is processed to identify the anatomical structure of the neck to obtain blood vessel and nerve marker data;

[0050] (2) The blood vessel and nerve marker data are processed to obtain spatial positioning data, and the target nerve ganglion three-dimensional coordinate data are processed to obtain fixed point marking data;

[0051] (3) The positioning data are processed to obtain electrode reference position data, and the electrode reference position data are processed to obtain electrode contact area data;

[0052] (4) The electrode contact area data are processed to obtain electrode contact pressure parameters, and the electrode contact pressure parameters are processed to obtain electrode conduction state data;

[0053] (5) The electrode conduction state data are processed to obtain electrode fixation parameters, and the electrode fixation parameters and electrode attachment position data are processed to obtain electrode placement information.

[0054] Specifically, the positioning module 102 is responsible for accurately positioning the stellate ganglion and planning the electrode placement. First, a high-frequency ultrasound probe (frequency range 4000-5000 Hz) is used to scan the target area of the neck, and a series of two-dimensional ultrasound slice images are obtained by emitting ultrasound waves and receiving echo signals. Image enhancement and noise filtering are performed on these raw ultrasound images to form clear anatomical structure images, and key tissue structures such as blood vessels and nerves are identified and labeled on the images. Multiple two-dimensional slice images are reconstructed to construct a three-dimensional stereoscopic structure model of the target area. Through feature point matching and spatial registration technology, the accurate spatial position of the stellate ganglion is determined, and its three-dimensional coordinate values (x, y, z) are obtained. After determining the position of the ganglion, the optimal attachment area is calculated according to the physical size of the electrode (2.5 cm x 1.0 cm x 0.5 cm), ensuring that the effective stimulation area of the electrode can completely cover the target ganglion.

[0055] The coverage area of the conductive gel layer is calculated based on the geometric parameters of the electrode, and considering the curved surface characteristics of the skin, the coverage area is appropriately expanded by 10-15%, ensuring good conductive contact. The contact pressure distribution between the electrode and the skin is calculated by a pressure sensor array, and the pressure value needs to be maintained within the range of 8-12 kPa, which ensures sufficient contact and avoids local compression. Combined with the conductive performance parameters of the electrode, including impedance value (less than 5 kΩ) and current density distribution uniformity (deviation less than ±10%), the conduction state of the electrode is evaluated. The conduction state of the electrode is continuously monitored, and when the state parameter fluctuation is less than 5%, it is recorded as a stable state parameter.

[0056] For example: In actual operation, the positioning module 102 first uses a 4500 Hz ultrasound probe to scan and obtain 100 continuous slice images with an interval of 0.5 mm. After image processing, the target ganglion position is identified, and its three-dimensional coordinates are (45 mm, 32 mm, 28 mm). According to this position, the optimal attachment area of the electrode is calculated, with the center point located at coordinates (45 mm, 32 mm), and the coverage area is 3 cm 2 . The actual coverage area of the conductive gel layer is expanded to 3.3 cm 2 , and the contact pressure is stabilized at 10 kPa. The electrode impedance measurement value is 3.5 kΩ, the current density distribution deviation is ±8%, and the parameter fluctuation within 5 minutes of continuous monitoring is less than 3%, confirming that the electrode placement state is good.

[0057] Fourth embodiment

[0058] The control module 103 is specifically configured to:

[0059] (1) Perform output control processing on the initial stimulation parameters to obtain a first set of stimulation waveform data, and perform baseline comparison processing on the real-time heart rate data to obtain heart rate change rate data;

[0060] (2) The heart rate change rate data is processed to obtain the heart rate drop amplitude value, and the heart rate drop amplitude value is processed to obtain the 10%-15% drop amplitude interval data;

[0061] (3) The baseline difference calculation processing is performed on the temperature data to obtain the temperature change value, and the target threshold judgment processing is performed on the temperature change value to obtain the 1℃ temperature rise judgment data;

[0062] (4) The adjustment interval calculation processing is performed on the stimulation frequency to obtain the 10-minute adjustment time point, and the 10% increment processing is performed on the stimulation frequency at the adjustment time point to obtain the stimulation frequency adjustment data;

[0063] (5) The double-target judgment processing is performed on the heart rate drop amplitude value and the temperature rise judgment data to obtain the parameter locking state data, and the parameter locking state data and the stimulation frequency adjustment data are combined to obtain the optimal control parameter combination.

[0064] Specifically, the control module 103 executes a closed-loop control strategy, outputs a first set of bidirectional rectangular wave stimulation waveform based on the initial parameter setting, the initial frequency is 8000Hz, the pulse width is 0.5ms, and the current intensity is 0.5mA. By real-time acquisition of heart rate data, the average value is calculated every 30 seconds, compared with the baseline heart rate, and the heart rate change trend is obtained. The heart rate change rate calculation uses the difference percentage of the current heart rate value and the baseline value, and the data update frequency is every 30 seconds. The target control interval of heart rate drop amplitude is set between 10%-15%, when the heart rate drop amplitude is lower than 10%, the parameter adjustment mechanism is triggered, and when the drop amplitude exceeds 15%, the protection mechanism is triggered. At the same time, the body surface temperature change is monitored, the difference between the current temperature value and the baseline temperature is calculated, and it is judged whether the target temperature rise value of 1℃ is reached. The temperature data sampling frequency is 10Hz, and the sliding window average processing is used to eliminate the instantaneous fluctuation, and the window length is set to 10 seconds.

[0065] The adjustment of the stimulation frequency adopts a fixed time interval strategy, and each adjustment cycle is 10 minutes. If the heart rate reduction at a certain adjustment time point is less than 10%, the stimulation frequency is increased by 10%. The frequency adjustment adopts a step-by-step incremental mode to ensure smooth transition of the stimulation intensity. When the heart rate reduction reaches the range of 10%-15% and the temperature rise reaches 1°C, the current stimulation parameter combination is locked. For example, the actual control process: the control module 103 first outputs a stimulation waveform with an initial frequency of 8000 Hz, and monitors that the baseline heart rate is 75 times per minute. After 10 minutes of stimulation, the heart rate is reduced to 68 times per minute, and the reduction is calculated to be 9.3% ((75-68) / 75 x 100% = 9.3%). The target value of 10% is not reached, so the frequency is increased to 8800 Hz (8000 x 110%) at the first adjustment time point. After 15 minutes of continuous monitoring, the heart rate is reduced to 65 times per minute, and the reduction reaches 13.3% ((75-65) / 75 x 100% = 13.3%). At the same time, the temperature rises from the initial 36.5°C to 37.6°C, and the temperature rise reaches 1.1°C, meeting the double target requirements. The control module 103 immediately locks the current parameter combination: frequency 8800 Hz, pulse width 0.5 ms, and current intensity 0.5 mA, and completes the determination of the optimal control parameters. The whole process fully embodies the closed-loop adjustment principle based on the double indicators of heart rate and temperature.

[0066] Fifth embodiment

[0067] The acquisition module 104 is specifically configured to:

[0068] (1) Real-time acquisition and processing of the heart rate signal to obtain original heart rate waveform data, and filtering processing of the original heart rate waveform data to obtain real-time heart rate data;

[0069] (2) Upper and lower limit judgment processing of the real-time heart rate data to obtain heart rate threshold data of 50 times per minute to 100 times per minute, and deviation analysis processing of the heart rate threshold data to obtain heart rate abnormality marker data;

[0070] (3) Data acquisition and processing of the body surface temperature sensor to obtain body surface temperature data, and baseline comparison processing of the body surface temperature data to obtain temperature change marker data;

[0071] (4) Comprehensive analysis processing of the heart rate abnormality marker data and the temperature change marker data to obtain alarm state data, and instruction generation processing of the alarm state data to obtain stimulation control instructions.

[0072] Specifically, the acquisition module 104 performs the acquisition and monitoring of the multi-dimensional physiological parameters. The heart rate signal acquisition uses standard electrocardiogram electrodes, with a sampling frequency set to 500 Hz. The analog signal is converted into a digital signal by a 16-bit A / D converter to obtain the original heart rate waveform data. The original data is first filtered to remove 50 Hz power frequency interference, and then a band-pass filter (cutoff frequency of 0.5-100 Hz) is used to remove baseline drift and high-frequency noise. Finally, the R-wave detection algorithm is used to extract the heart rate value, and the real-time heart rate data is updated every 30 seconds. The heart rate monitoring sets a strict safety threshold range: the lower limit is 50 beats per minute, and the upper limit is 100 beats per minute. When the real-time heart rate value is detected to be outside this range, an abnormality flag is triggered. The calculation of the abnormality flag uses a continuous three-sampling value determination method: if the heart rate readings of the last three times are all outside the threshold range, a heart rate abnormality flag is generated, and the flag value includes the abnormality type (too fast / too slow) and the duration information.

[0073] The body surface temperature acquisition uses a temperature sensor with an accuracy of 0.1℃, and the sampling frequency is set to 10 Hz. The temperature data is smoothed using a 10-second sliding window to eliminate the effects of transient fluctuations. The processed temperature value is compared with the initial baseline temperature, and a temperature change flag is generated when the temperature difference exceeds the set threshold (temperature rise of 1℃). For example, during actual operation of the acquisition module 104, the original heart rate signal is first acquired, and after filtering, the heart rate is 73 beats per minute, which is within the safe range. At the same time, it is monitored that the body surface temperature rises from the baseline of 36.5℃ to 37.2℃, with a temperature rise of 0.7℃, which has not yet reached the target value. After 5 minutes, the heart rate drops to 48 beats per minute, which is below the 50 beats per minute threshold, and after three consecutive confirmations, a heart rate abnormality flag is generated; the body temperature rises to 37.8℃, generating a temperature change flag. The acquisition module 104 analyzes the two abnormality flags comprehensively and generates an emergency alarm state, and immediately issues a control command to stop stimulation, realizing the multi-dimensional safety monitoring function.

[0074] Sixth embodiment

[0075] The analysis module 105 is specifically configured to:

[0076] (1) performing fluctuation analysis processing on the heart rate data in the monitoring data to obtain heart rate trend data, and performing target interval determination processing on the heart rate trend data to obtain a heart rate stability index;

[0077] (2) performing change rate calculation processing on the temperature data in the monitoring data to obtain temperature change curve data, and performing rise amplitude analysis processing on the temperature change curve data to obtain a temperature stability index;

[0078] (3) The heart rate stability index is analyzed in a range of ±5%, to obtain heart rate fine-tuning interval data, and the temperature stability index is processed for steady-state determination, to obtain temperature control interval data;

[0079] (4) The heart rate fine-tuning interval data and the temperature control interval data are analyzed for parameters, to obtain steady-state control parameters.

[0080] The analysis module 105 is also specifically used for:

[0081] (1) The heart rate fine-tuning interval data and the temperature control interval data are combined for processing, to obtain a parameter adjustment strategy;

[0082] (2) The stimulation frequency is adjusted in a small amount according to the parameter adjustment strategy, to obtain a frequency adjustment value;

[0083] (3) The frequency adjustment value is controlled for 30 minutes, to obtain frequency steady-state data;

[0084] (4) The frequency steady-state data is recorded for parameters, to obtain steady-state control parameters.

[0085] Specifically, the analysis module 105 dynamically analyzes and adjusts the monitoring data during the stimulation process. The heart rate data is analyzed for fluctuations, and the heart rate variability is calculated using a 5-minute sliding window, with data updated every 30 seconds. The heart rate change trend is compared with the target reduction interval (10%-15%), and when the heart rate change amplitude of 10 consecutive samples is maintained within the target interval, the heart rate stability index is calculated. At the same time, the temperature data is analyzed for change rate, and the temperature rise rate per minute is calculated. The temperature change curve is analyzed for slope, and the curve is divided into a rapid rise period and a stable period. When the temperature rise reaches 1°C and the temperature change rate of 5 consecutive minutes is less than 0.1°C / min, it is determined that the temperature stability index is reached.

[0086] The obtained heart rate stability index is analyzed in detail, and a fluctuation tolerance interval of ±5% is set. The specific operation is as follows: taking the current heart rate value as the reference, the allowed range of fluctuation is calculated. For example, when the heart rate drops to 65 times / minute, the allowed fluctuation range is 61.75-68.25 times / minute. The temperature control interval is set based on the 1°C target temperature rise value, and the allowed fluctuation range is 0.9-1.1°C. According to the combination of the heart rate fine-tuning interval and the temperature control interval, a parameter adjustment strategy is developed. When the heart rate or temperature exceeds the respective control interval, the stimulation frequency is adjusted in a small amount, and the adjustment step is 2% of the current frequency. The adjustment process uses a gradual approach to avoid parameter mutation.

[0087] For example: the analysis module 105 receives a set of monitoring data, the initial heart rate is 75 times / min, 15 minutes later the heart rate drops to 65 times / min (decrease 13.3%), the heart rate fluctuation is maintained in the range of 62-68 times / min (±5%) within 30 minutes of continuous monitoring. At the same time, it is recorded that the body surface temperature rises from 36.5℃ to 37.6℃ (rise 1.1℃), and the temperature change rate drops to 0.05℃ / min. Based on these data, the analysis module confirms that the parameters have reached a steady state, and records the current stimulation parameters (frequency 8800Hz, pulse width 0.5ms, current intensity 0.5mA) as the steady-state control parameters. The whole analysis process embodies the accurate control and dynamic optimization of the double indicators of heart rate and temperature.

[0088] Seventh embodiment

[0089] The evaluation module 106 is specifically used for:

[0090] (1) performing full-range recording processing on the heart rate change data in the control process data to obtain heart rate change curve data, and performing fluctuation analysis processing on the heart rate change curve data to obtain heart rate response characteristic data;

[0091] (2) performing full-range recording processing on the temperature change data in the control process data to obtain temperature change curve data, and performing trend analysis processing on the temperature change curve data to obtain temperature response characteristic data;

[0092] (3) performing serialization processing on the adjustment record of the stimulation frequency and intensity to obtain parameter adjustment process data, and performing change rule analysis processing on the parameter adjustment process data to obtain parameter response characteristic data;

[0093] (4) performing rule optimization analysis on the heart rate response characteristic data, the temperature response characteristic data and the parameter response characteristic data to obtain parameter optimization suggestions.

[0094] The evaluation module 106 is also specifically used for:

[0095] (1) performing correlation analysis processing on the heart rate response characteristic data, the temperature response characteristic data and the parameter response characteristic data to obtain working state evaluation indexes;

[0096] (2) performing feature classification processing on the working state evaluation indexes to obtain index category data;

[0097] (3) performing rule matching processing on the index category data to obtain parameter matching scheme data;

[0098] (4) performing recommendation generation processing on the parameter matching scheme data to obtain parameter optimization suggestions.

[0099] Specifically, the evaluation module 106 is responsible for comprehensive analysis and evaluation of the data of the entire control process. The heart rate variation data is collected and recorded throughout the process, with a sampling frequency of 100 Hz, and the average value is calculated every 5 seconds to form a complete heart rate variation curve. By analyzing the response time of heart rate reduction (the time required from the start of stimulation to reach the target reduction), stability (the maintenance time within the target interval), and fluctuation range (the maximum deviation value), the characteristic description of heart rate response is obtained. At the same time, the body surface temperature variation is continuously recorded, with a sampling frequency of 10 Hz, and the average value is calculated every 10 seconds to generate a temperature variation curve. The rate of temperature rise (temperature change per minute), the time to reach the standard (the time required to raise the temperature to 1°C), and the stability (standard deviation of temperature fluctuation) are analyzed to form temperature response characteristic data.

[0100] The adjustment process of the stimulation parameters is recorded in chronological order, including the time points of frequency adjustment, adjustment amplitude, and effect changes after adjustment. By analyzing the correspondence between parameter adjustment and physiological response, the regularity characteristics of parameter adjustment are summarized, such as the response delay of adjustment frequency and heart rate variation, the cumulative effect of temperature variation, etc. The correlation analysis is performed on the three groups of characteristic data to establish a parameter-effect correspondence matrix. According to the indicators such as heart rate reduction standard time, temperature rise rate, and parameter adjustment times, the control effect is divided into fast response type, slow response type, and insensitive type, etc., forming a classification evaluation result.

[0101] For example: The evaluation module 106 records a group of control process data, with an initial heart rate of 75 beats per minute, a temperature of 36.5°C, and a stimulation frequency of 8000 Hz. Within the first 10 minutes, the heart rate drops to 68 beats per minute (a reduction of 9.3%), the temperature rises to 37.1°C (an increase of 0.6°C), and the frequency is adjusted to 8800 Hz. After another 5 minutes, the heart rate drops to 65 beats per minute (a reduction of 13.3%), and the temperature rises to 37.6°C (an increase of 1.1°C). Analysis shows that the heart rate response time is 15 minutes, the temperature reaches the standard time is 15 minutes, and only one frequency adjustment is required to achieve the target effect. Based on these data characteristics, the evaluation module classifies the parameters as "fast response type" and generates optimization suggestions: the initial frequency can be set to 8800 Hz, the pulse width is 0.5 ms, the current intensity is 0.5 mA, and it is expected to achieve the ideal control effect within 15 minutes.

[0102] Eighth embodiment

[0103] As Figure 2As shown, some embodiments of the present application also provide a structural diagram of a non-invasive electrode closed-loop feedback stellate ganglion block electric stimulation device, which comprises a facial temperature sensor 201, an oxygen saturation clip 202, an electrode 203 and a controller 204; wherein the controller 204 comprises the above-mentioned processing module 101, positioning module 102, control module 103, acquisition module 104, analysis module 105 and evaluation module 106.

[0104] In specific application, the non-invasive electrode closed-loop feedback stellate ganglion block electric stimulation device monitors the facial temperature of the user through the facial temperature sensor 201, monitors the heart rate of the user through the oxygen saturation clip 202, performs closed-loop feedback control on the non-invasive electrode closed-loop feedback stellate ganglion block electric stimulation device through the controller 204, and outputs a predetermined electric stimulation signal to the stimulation area of the stellate ganglion of the user through the electrode 203, so as to realize real-time monitoring and intelligent adjustment of the running state of the electric stimulation device.

[0105] In summary, the non-invasive electrode closed-loop feedback stellate ganglion block electric stimulation device provided by the present application improves the control precision, enhances the adaptability and scalability of the system, and provides technical support for the continuous optimization of the control device by introducing ultrasonic positioning, multi-dimensional parameter acquisition, dynamic analysis and intelligent evaluation and other technical means.

[0106] The scope of the present application is defined by the appended claims rather than the description above, and therefore all changes that come within the meaning and range of equivalents of the claims are to be embraced within the scope of the present application. Any reference signs in the claims should not be construed as limiting the claims to the figures in which the reference signs are used. Furthermore, the words "comprise", "comprising", "comprises" and "comprising" should not be interpreted as being restricted to membership of a group, but on the contrary the words specifically declare possible non-membership. Multiple units or devices also recited in device claims can be replaced by one unit or device carrying out the same functions performed by said units or devices through software or hardware. The words "first", "second" and the like do not imply any particular order but are used to distinguish one element from another.

[0107] The above description is merely one specific implementation of the present application, but the protection scope of the present application is not limited thereto, and any skilled person in the art can easily make changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be limited by the protection scope of the claims, and the above-mentioned embodiments should be regarded as exemplary and non-limiting.

Claims

1. A non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device, comprising: The method comprises the following steps: A processing module is used to initialize the stimulation parameter and physiological parameter detection module, obtain a parameter set containing an initial stimulation frequency, an initial stimulation pulse width, and an initial stimulation current intensity, and a baseline data set containing a basic heart rate value and an initial body surface temperature value; A positioning module is used to receive positioning data obtained by an external ultrasound device performing ultrasound scanning on a target region, and perform position planning processing on the electrodes according to the positioning data to obtain electrode placement information; A control module is used to perform closed-loop control processing on the initial stimulation parameters, adjust the stimulation frequency and intensity through real-time heart rate data and temperature data, and obtain an optimal control parameter combination; A collection module is used to perform multi-dimensional collection processing on physiological parameters to obtain a monitoring data set containing real-time heart rate data and body surface temperature data, perform threshold judgment processing according to the monitoring data set, and obtain a stimulation control instruction; An analysis module is used to perform dynamic analysis processing on the monitoring data during stimulation to obtain a parameter adjustment strategy, perform optimization processing on the stimulation parameters according to the parameter adjustment strategy, and obtain a steady-state control parameter; An evaluation module is used to perform integrated analysis processing on control process data to obtain a working state evaluation index, perform classification statistical processing according to the evaluation index, and obtain a parameter optimization suggestion.

2. The non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device of claim 1, wherein, The processing module is used to: set the initial stimulation frequency to obtain an initial stimulation frequency value of 8000 Hz, and set the initial stimulation pulse width to obtain an initial stimulation pulse width value of 0.5 ms; set the initial stimulation current intensity to obtain an initial stimulation current intensity value of 0.5 mA, and start the physiological parameter detection module to obtain detection module working state information; collect heart rate data to obtain a basic heart rate value, and collect body surface temperature data to obtain an initial body surface temperature value; set a threshold value for the basic heart rate value to obtain a lower threshold value of 50 times per minute and an upper threshold value of 100 times per minute, and record a baseline for the initial body surface temperature value to obtain temperature baseline data; set a stimulation parameter adjustment interval to obtain an adjustment period value of 10 minutes, and set a stimulation parameter adjustment amplitude to obtain an adjustment step value of 10%; integrate the basic heart rate value, the initial body surface temperature value, the threshold value parameters, and the adjustment parameters to obtain the parameter set and the baseline data set.

3. The non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device of claim 1, wherein, The positioning module is used to: perform spatial positioning processing on the blood vessel and nerve marker data through an external ultrasound device to obtain target nerve ganglion three-dimensional coordinate data, and perform fixed-point marking processing on the target nerve ganglion three-dimensional coordinate data to obtain the positioning data; perform electrode attachment region planning processing on the positioning data to obtain electrode reference position data, and perform conductive gel layer coverage range calculation processing on the electrode reference position data to obtain electrode attachment area data; perform pressure distribution calculation processing on the electrode attachment area data to obtain electrode contact pressure parameters, and perform conductive performance evaluation processing on the electrode contact pressure parameters to obtain electrode conduction state data; The electrode conduction state data is subjected to stability analysis to obtain electrode fixing parameters. The electrode fixing parameters and electrode attachment position data are then aggregated to obtain electrode placement information.

4. The non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device of claim 1, wherein, The control module is used for: The initial stimulation parameters are processed by output control to obtain the first set of stimulation waveform data, and the real-time heart rate data is processed by baseline comparison to obtain heart rate change rate data. The heart rate change rate data is processed to calculate the decrease, and the heart rate decrease value is then processed to determine the target range, resulting in a decrease range of 10%-15%. The temperature data is processed by baseline difference calculation to obtain temperature change value, and the temperature change value is processed by target threshold judgment to obtain temperature rise judgment data of 1℃. The stimulation frequency is adjusted by an interval calculation to obtain a 10-minute adjustment time point, and the stimulation frequency is increased by 10% at the adjustment time point to obtain stimulation frequency adjustment data. The heart rate decrease value and temperature rise determination data are subjected to dual-target determination processing to obtain parameter lock state data. The parameter lock state data and stimulation frequency adjustment data are then combined to obtain the optimal control parameter combination.

5. The non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device of claim 1, wherein, The acquisition module is used for: The heart rate signal is acquired and processed in real time to obtain raw heart rate waveform data, and the raw heart rate waveform data is filtered to obtain the real-time heart rate data. The real-time heart rate data is subjected to upper and lower limit judgment processing to obtain heart rate threshold data of 50 beats / minute to 100 beats / minute, and the heart rate threshold data is subjected to deviation analysis processing to obtain heart rate abnormality marker data. Data acquisition and processing are performed on the body surface temperature sensor to obtain the body surface temperature data, and baseline comparison processing is performed on the body surface temperature data to obtain temperature change marker data. The heart rate abnormality marker data and temperature change marker data are comprehensively analyzed and processed to obtain alarm status data, and the alarm status data is then processed to generate the stimulus control command.

6. The non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device of claim 1, wherein, The analysis module is used for: The heart rate data in the monitoring data is subjected to fluctuation analysis to obtain heart rate change trend data, and the heart rate change trend data is subjected to target interval determination to obtain heart rate stability index. The temperature data in the monitoring data is processed by calculating the rate of change to obtain temperature change curve data, and the rise of the temperature change curve data is analyzed to obtain temperature stability index. The heart rate stability index is analyzed within a ±5% range to obtain heart rate fine-tuning interval data, and the temperature stability index is analyzed for steady-state determination to obtain temperature control interval data. The steady-state control parameters are obtained by performing parameter analysis on the heart rate fine-tuning interval data and temperature control interval data.

7. The non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device of claim 6, wherein, The analysis module is also used for: The heart rate fine-tuning interval data and temperature control interval data are combined and processed to obtain the parameter adjustment strategy. The stimulation frequency is slightly adjusted according to the parameter adjustment strategy to obtain the frequency adjustment value. The frequency adjustment value is controlled for 30 minutes to obtain frequency steady-state data; The steady-state control parameters are recorded by processing the frequency steady-state data.

8. The non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device of claim 1, wherein, The evaluation module is configured to: The heart rate change data in the control process data is recorded to obtain heart rate change curve data, and the heart rate change curve data is analyzed to obtain heart rate response characteristic data; The temperature change data in the control process data is recorded to obtain temperature change curve data, and the temperature change curve data is analyzed to obtain temperature response characteristic data; The adjustment of the stimulation frequency and intensity is recorded to obtain parameter adjustment process data, and the parameter adjustment process data is analyzed to obtain parameter response characteristic data; The parameter optimization suggestion is obtained by performing rule optimization analysis on the heart rate response characteristic data, the temperature response characteristic data, and the parameter response characteristic data.

9. The non-invasive electrode closed loop feedback stellate ganglion block electrical stimulation device of claim 8, wherein, The evaluation module is further configured to: The heart rate response characteristic data, the temperature response characteristic data, and the parameter response characteristic data are analyzed to obtain the working state evaluation index; The working state evaluation index is classified to obtain index category data; The index category data is matched to obtain parameter matching scheme data; The parameter matching scheme data is recommended to generate the parameter optimization suggestion.

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