A dual-frequency single-guide head output superconducting therapy system

Abstract

This invention discloses a dual-frequency single-guide-head output superconducting therapy system, belonging to the field of superconducting therapy technology. The dual-frequency single-guide-head output superconducting therapy system includes a movable treatment cart, with a multi-directionally adjustable robotic arm on top. The robotic arm houses a composite guide head, which integrates measuring electrodes, a dual-frequency electromagnetic transceiver, a laser imaging lens, a temperature sensor, and a semiconductor cooling chip. It also includes a handheld portable terminal connected to the cart via a cable, and a central control system comprising a constitution analysis module, a lesion scanning module, a strategy generation module, a tolerance feedback module, and a efficacy evaluation module. This invention solves the problems of existing dual-frequency therapy systems, such as limited treatment modes and insufficient individual adaptability, leading to low treatment efficiency and poor risk control.

Description

Technical Field

[0001] This invention relates to the field of superconducting therapy technology, specifically a dual-frequency single-guide head output superconducting therapy system. Background Technology

[0002] Current electromagnetic wave therapy devices have significant limitations in clinical applications, primarily manifested in the lack of a single treatment mode and insufficient individual adaptability. Traditional systems generally employ fixed frequencies and energy output modes, failing to dynamically adjust according to patient differences, lesion depth, and inflammation severity. Specifically, different body types exhibit significant variations in their tolerance and response characteristics to electromagnetic wave energy. Traditional devices cannot classify body types based on physiological parameters such as grip strength, hand temperature distribution, and bioelectrical impedance, leading to a mismatch between treatment plans and the patient's physiological state, potentially causing side effects or insufficient efficacy. Furthermore, existing technologies rely on preset parameter templates and lack multivariate collaborative optimization mechanisms. Summary of the Invention

[0003] The purpose of this invention is to provide a dual-frequency single-guide head output superconducting treatment system. The system is more intelligent and can determine the corresponding treatment mode to be adopted based on the patient's physical condition, lesion location and severity. It is more intelligent and humane, and solves the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A dual-frequency single-guide head output superconducting therapy system includes:

[0006] A mobile treatment trolley with a multi-directionally adjustable robotic arm on top;

[0007] The composite probe, mounted at the end of the robotic arm, integrates a bioelectrical impedance measurement electrode, a dual-frequency electromagnetic transceiver that simultaneously emits low-frequency modulated waves and high-frequency continuous waves, a 635nm wavelength laser imaging lens, a platinum resistance temperature sensor network with a 0.5mm spacing, and a semiconductor refrigeration chip for cooling.

[0008] The handheld portable terminal is connected to the trolley via a cable. There are two handheld portable terminals, which are held by the patient's left and right hands respectively. The portable terminal integrates multiple electrode points, an infrared camera, a humidity sensor, a grip force sensor, a heart rate and pulse monitor, and a Doppler probe.

[0009] The central control system, with a built-in intelligent learning chip, includes:

[0010] The body constitution analysis module, based on bioelectrical impedance data, hand thermal image data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data collected by a handheld portable terminal, inputs them into the meridian admittance model to determine the body constitution type and generates a body constitution and energy status report.

[0011] The lesion scanning module scans the patient's body tissues through a dual-frequency electromagnetic transceiver, simultaneously emitting low-frequency modulated waves and high-frequency continuous waves. The low-frequency scanning depth is 10mm, and the high-frequency scanning depth is 45mm. Based on a loss factor >38.5, inflammation is determined and a lesion model with an accuracy of ±2mm³ is constructed.

[0012] The strategy generation module allocates the ratio of high and low frequency energy according to the body type, sets the high frequency power according to the depth of the lesion, adjusts the treatment time according to the inflammation level, and optimizes the combination of parameters.

[0013] The tolerance feedback module performs impedance monitoring, temperature control, and distance protection in real time, and records and stores abnormal condition data.

[0014] The efficacy assessment module acquires blood flow distribution maps and infrared thermograms, calculates the blood flow improvement rate and the inflammation area reduction rate, and generates a comprehensive efficacy index (TEI) after assigning weights.

[0015] Preferably, the working method of the body composition analysis module is as follows:

[0016] The patient holds the handheld portable terminal with both hands to undergo testing;

[0017] Electrode points were used to measure the patient's bioelectrical impedance data in the 5Hz-100kHz frequency band, and the resistance and capacitance values ​​were extracted.

[0018] Infrared cameras acquire thermal images of the hand and detect abnormal areas with temperature differences greater than 2°C;

[0019] The humidity sensor uses capacitive detection to detect sweat secretion on the palm, with an accuracy of ±3%RH.

[0020] The grip strength sensor has a range of 0-100kg and an accuracy of ±0.5kg to obtain the strength of the hand grip.

[0021] The heart rate and pulse monitor has a sampling frequency of 1 kHz and a pressure resolution of 0.1 kPa, and detects the patient's heart rate and pulse frequency and intensity.

[0022] The Doppler probe has a wavelength of 785nm and a sampling rate of 50Hz to monitor the microcirculation of blood in the patient's fingertips.

[0023] The central processing unit inputs different types of test data into the meridian conduction model to determine the patient's constitution type and generate an electronic report that includes constitution classification and the body's energy balance status.

[0024] Preferably, the lesion scanning module operates as follows:

[0025] The composite probe moves longitudinally along the patient's spine to scan, and the dual-frequency electromagnetic transceiver simultaneously emits two different electromagnetic waves, 13.56MHz low-frequency wave and 40.68MHz high-frequency wave. The low-frequency wave scans to a depth of 10mm for ligament tissue, and the high-frequency wave scans to a depth of 45mm for deep tissues in the body.

[0026] The dual-frequency electromagnetic transceiver compares the reflected signal with the standard electrical characteristic value of healthy tissue. If the loss factor is detected to be greater than a specific electrical characteristic value, it is determined that there is inflammation in the area.

[0027] A three-dimensional model of the lesion area was constructed, with a lesion volume accuracy of ±2mm³.

[0028] Preferably, the strategy generation module works as follows:

[0029] The proportion and waveform type of high and low frequency energy are allocated according to the patient's specific physical condition.

[0030] The energy intensity of the high-frequency wave is set according to the detected lesion depth;

[0031] The total treatment duration is adjusted according to the severity of the inflammation;

[0032] The intelligent learning chip optimizes the parameter combination in real time, and the treatment parameters are wirelessly transmitted to the composite guide for execution.

[0033] Preferably, the tolerance feedback module further includes:

[0034] Impedance monitoring unit, configured to acquire impedance values ​​of the treatment area every 200ms;

[0035] The temperature control unit is configured to continuously monitor skin temperature using a temperature sensor. If the temperature rises too quickly, it will activate the semiconductor cooling chip in the composite head to cool the skin locally.

[0036] The distance protection unit is configured to continuously detect the distance between the probe and the skin surface. If the distance is too close, an alarm will be triggered and energy output will be stopped.

[0037] All abnormal events that occur will be recorded in detail in the security log.

[0038] Preferably, the working method of the efficacy assessment module is as follows:

[0039] The laser imaging lens emits a 635nm wavelength laser to scan a skin area of ​​approximately 10×10cm, capturing 25 blood flow distribution images per second;

[0040] After a period of treatment, the average blood flow velocity in the area was remeasured, and the immediate improvement rate of blood flow velocity was calculated.

[0041] The reduction rate of inflammation area was calculated using infrared thermography after treatment.

[0042] Weights were assigned to the immediate improvement rate of blood flow velocity and the reduction rate of inflammation area.

[0043] A Comprehensive Efficacy Index (TEI) is generated, and the effectiveness of treatment is determined based on the TEI value.

[0044] Preferably, the rules for determining the body type are as follows:

[0045] If the conductivity deviation is greater than 15% and the humidity data is greater than 65%RH, it is marked as "phlegm-dampness constitution";

[0046] If more than 40% of the area of ​​the palm is below 32°C, it is marked as "Yang deficiency constitution";

[0047] If the grip strength data is <30kg, the heart rate variability is <40ms, and the pulse wave decay slope is >15% / s, then it is marked as "Qi deficiency constitution";

[0048] If the microcirculatory blood flow velocity at the fingertip is <0.5 mm / s, it is marked as "blood stasis constitution";

[0049] If the skin capacitance value of the palm is greater than 120pF, it is marked as "Yin deficiency constitution".

[0050] Preferably, the allocation of high and low frequency energy ratios and waveform types based on the patient's specific physical condition is as follows:

[0051] For phlegm-dampness constitution, high-frequency energy accounts for 65%-70%, the waveform mode is continuous wave, and the temperature control threshold is ≤39℃; for yang deficiency constitution, high-frequency energy accounts for 78%-85%, the waveform mode is square wave, and the temperature control threshold is ≤41℃; for qi deficiency constitution, high-frequency energy accounts for 50%-55%, the waveform mode is sine wave, and the temperature control threshold is ≤38℃; for blood stasis constitution, high-frequency energy accounts for 75%-80%, the waveform mode is pulse wave, and the temperature control threshold is ≤40℃; for yin deficiency constitution, high-frequency energy accounts for 45%-50%, the waveform mode is intermittent wave, and the temperature control threshold is ≤37℃.

[0052] Preferably, it also includes: a preprocessing module, used by the constitution analysis module to preprocess the bioelectrical impedance data, humidity data, grip strength data, heart rate and pulse data and fingertip microcirculation data collected by the handheld portable terminal before inputting them into the meridian admittance model and determining the constitution type;

[0053] The preprocessing module includes:

[0054] The alignment unit is used to treat the bioelectrical impedance data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data as multi-dimensional data to be processed, and to align the multi-dimensional data to be processed based on the time series.

[0055] The feature extraction unit is used to input the aligned multi-dimensional data to be processed into a pre-trained feature extraction model to extract features and obtain the feature data corresponding to the multi-dimensional data to be processed.

[0056] Anomaly detection unit, used for:

[0057] Take any one dimension of the multi-dimensional data to be processed as the first dimension.

[0058] Calculate the correlation index between the first-dimensional data and the data in other dimensions of the multi-dimensional data to be processed, except for the first-dimensional data, to obtain several correlation indices;

[0059] The summation of several correlation indices is used as the first-dimensional correlation evaluation index.

[0060] By traversing all dimensions of the multi-dimensional data to be processed, several relevance evaluation indices are obtained.

[0061] The evaluation weight of each dimension is determined based on several relevance evaluation indices;

[0062] Calculate the difference between the data in the same dimension corresponding to two adjacent time series points to obtain the data difference for each dimension;

[0063] Multiply the data difference corresponding to each dimension by the evaluation weight of each dimension to obtain several products; use the sum of several products as the difference index of the data corresponding to two adjacent time series points; iterate through all time series points to obtain several difference indices.

[0064] Calculate the local fluctuation value of each difference index within its neighborhood;

[0065] The local fluctuation value is compared with the preset local fluctuation threshold, and the data corresponding to the time series point when the local fluctuation value is greater than or equal to the preset local fluctuation threshold is regarded as abnormal data.

[0066] Iterate through the data corresponding to all time series points to obtain several abnormal data points;

[0067] The data cleaning unit is used for:

[0068] Obtain preset data cleaning rules;

[0069] Based on the preset data cleaning rules, the several abnormal data are cleaned to obtain preprocessed bioelectrical impedance data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data.

[0070] Preferably, the strategy generation module allocates the ratio of high and low frequency energy according to body type, sets the high frequency power according to lesion depth, adjusts the treatment duration according to inflammation level, and optimizes the combination of parameters, including:

[0071] Acquire a medical knowledge graph; the medical knowledge graph includes a medical knowledge graph, a knowledge graph of human physiological and pathological characteristics, a knowledge graph of the electromagnetic properties of biological tissues, a knowledge graph of medical sensors and monitoring technologies, a knowledge graph of electromagnetic wave therapy technologies, and a knowledge graph of efficacy evaluation indicators;

[0072] Based on the aforementioned medical knowledge graph, body constitution types lesion depth and inflammation level Define variables; where, There are n categories, corresponding to the ratio of high and low frequency energy. , Indicates the proportion of high-frequency energy, 1- Indicates the proportion of low-frequency frequencies; There are m levels in total, with increasing depth, corresponding to high-frequency power. Power increases with depth; There are n levels in total, with increasing inflammation, corresponding to treatment durations. The duration increases with the severity of inflammation;

[0073] Based on body type lesion depth and inflammation level Constructing a rating matrix Association strength constitution - deep association and depth-inflammation association ;

[0074] Based on the rating matrix Association strength constitution - deep association and depth-inflammation association Determine the ratio of high and low frequency energy High-frequency power and treatment duration ,in,

[0075]

[0076] in, The optimal solution representing the ratio of high to low frequency energy; Indicates the constitution type index; Indicates an index of inflammation severity; This represents the ideal treatment outcome score under the combination of "Constitution U + Inflammation A"; Indicates the strength of the synergistic effect of constitution-depth-inflammation; for all lesion depths Connecting physical constitution with depth , depth power Treatment duration Deep-inflammation association Multiply and then sum; Represents the regularization coefficient;

[0077]

[0078] in, The optimal solution representing high-frequency power; Represents the regularization coefficient; Indicates the ratio of high to low frequency energy;

[0079]

[0080] in, The optimal solution representing the treatment duration; Represents the regularization coefficient; This indicates the strength of the intermediate association between depth and inflammation.

[0081] Compared with the prior art, the beneficial effects of the present invention are:

[0082] 1. This invention uses a handheld portable terminal to simultaneously collect physiological indicators such as bioelectrical impedance, hand thermal imaging, grip strength, and fingertip microcirculation. These indicators are then incorporated into a meridian admittance model to automatically classify TCM constitution types, providing a basis for energy allocation. Output strategies are dynamically formulated for different constitution characteristics, thereby avoiding the risk of side effects caused by incompatibility with the constitution from the root.

[0083] 2. This invention uses a dual-frequency electromagnetic transceiver to simultaneously transmit a 13.56MHz low-frequency wave and a 40.68MHz high-frequency wave. By using a precise threshold of loss factor > 38.5 to determine the inflammatory area, a three-dimensional lesion model with an accuracy of ±2mm³ is constructed. The lesion depth is converted into an energy regulation parameter, and the treatment duration is determined according to the inflammation level to ensure that the energy delivery is precisely correlated with the spatial location and severity of the lesion.

[0084] 3. This invention monitors tissue impedance through a tolerance feedback loop. When the impedance decreases by more than 18% for five consecutive times, the power is automatically reduced to 10W. This, combined with a semiconductor cooling chip, provides targeted cooling to areas experiencing rapid localized heating, creating a real-time safety barrier. The efficacy evaluation loop generates 25 frames of blood flow images per second using 635nm laser imaging. It calculates the immediate blood flow improvement rate and the reduction rate of inflammation area after treatment, generating a comprehensive efficacy index (TEI). When the TEI is greater than 35%, the treatment is considered effective; otherwise, the parameters are re-optimized, forming an intelligent closed loop of "treatment-evaluation-iteration." This effectively improves the treatment effectiveness and reduces the treatment interruption rate caused by close proximity, achieving a balance between personalized precision treatment and humanized safety protection. Attached Figure Description

[0085] Figure 1 This is a system module structure diagram of the present invention;

[0086] Figure 2 This is a system workflow diagram of the present invention. Detailed Implementation

[0087] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0088] To address the issues of low treatment efficiency and poor risk control resulting from the limited range of treatment modes and insufficient individual adaptability in existing dual-frequency therapy systems, please refer to [link to relevant documentation]. Figure 1-2 This embodiment provides the following technical solution:

[0089] A dual-frequency single-guide output superconducting therapy system is disclosed. The hardware of the system is a mobile treatment trolley. The top of the trolley is equipped with a multi-directionally adjustable robotic arm. The end of the robotic arm is equipped with a composite guide for treatment. The composite guide integrates five functional components: first, electrodes for measuring the body's electrical properties; second, a transceiver for emitting and receiving dual-frequency electromagnetic waves; third, a laser imaging lens for observing changes in blood flow; fourth, platinum resistance temperature sensors set in the electrode gap to form a thermal monitoring network with a precision of 0.5 mm; and fifth, a semiconductor cooling chip for cooling.

[0090] Two portable terminals are connected to one side of the trolley via cables for patients to hold with their left and right hands. Each portable terminal integrates multiple electrode points, an infrared camera, a humidity sensor, a grip strength sensor, a heart rate and pulse monitor, and a Doppler probe. The electrode points are used to contact the patient's palm when holding the device. The infrared camera is used to capture thermal images of the hand. The humidity sensor is used to monitor the amount of sweat secreted by the palm. The grip strength sensor is used to obtain the grip strength. The heart rate and pulse monitor is used to detect the patient's heart rate and pulse frequency and intensity. The Doppler probe is used to monitor the blood microcirculation in the patient's fingertips.

[0091] The trolley has a central control system with a built-in intelligent learning chip. The central control system is equipped with a central processor and includes a constitution analysis module, a lesion scanning module, a strategy generation module, a tolerance feedback module, and a efficacy evaluation module. These five modules work together.

[0092] The specific workflow of the body composition analysis module is as follows:

[0093] Before treatment begins, the patient holds the handheld portable terminal with both hands for about 10 seconds. At this time:

[0094] Multiple electrodes measure the patient's electrical properties across a wide frequency range, typically 5Hz-100kHz, to acquire bioelectrical impedance data. The raw bioelectrical impedance data is then extracted using Fourier transform to determine capacitance and conductivity values. An infrared camera captures temperature distribution maps of the patient's hands and finger joints, detecting abnormal areas with temperature differences greater than 2℃. A humidity sensor capacitively detects palm sweat secretion with an accuracy of ±3%RH. A grip strength sensor measures 0-100kg with an accuracy of ±0.5kg, acquiring hand grip strength. A heart rate and pulse monitor, with a sampling frequency of 1kHz and a pressure resolution of 0.1kPa, detects the patient's heart rate and pulse frequency and intensity. A Doppler probe, with a wavelength of 785nm and a sampling rate of 50Hz, monitors the patient's fingertip microcirculation.

[0095] The central processing unit inputs bioelectrical impedance data, hand thermal image data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data into the meridian admittance model to determine the patient's constitution type. The rules for determining the constitution type are as follows:

[0096] If the conductivity deviation is greater than 15% and the humidity data is greater than 65%RH, it is marked as "phlegm-dampness constitution";

[0097] If more than 40% of the area of ​​the palm is below 32°C, it is marked as "Yang deficiency constitution";

[0098] If the grip strength data is <30kg, the heart rate variability SDNN is <40ms and the pulse wave attenuation slope is >15% / s, then it is marked as "Qi deficiency constitution";

[0099] If the microcirculatory blood flow velocity at the fingertip is <0.5 mm / s, it is marked as "blood stasis constitution";

[0100] If the skin capacitance value of the Laogong acupoint on the palm is >120pF, it is marked as "Yin deficiency constitution";

[0101] The final result is an electronic report that details the patient's constitution type and score, as well as a coefficient reflecting the body's energy balance.

[0102] Traditional equipment lacks the ability to identify patient constitution, which can easily lead to a mismatch between treatment plans and the patient's physiological state. Setting up a constitution analysis module can effectively avoid a one-size-fits-all treatment model. By accurately classifying constitution, it can provide a scientific basis for the subsequent allocation of energy parameters, significantly improve the targeting of treatment, and reduce the risk of side effects caused by incompatibility with the patient's constitution.

[0103] The specific workflow of the lesion scanning module is as follows:

[0104] The operator holds the treatment composite probe and moves it longitudinally along the patient's spine to perform a scan. The dual-frequency electromagnetic transceiver simultaneously emits two different electromagnetic waves: one is a 13.56MHz low-frequency modulated wave, used to scan ligament tissue near the surface, with a scanning depth of about 10mm; the other is a 40.68MHz high-frequency continuous wave, used to scan deep tissues in the body, with a scanning depth of about 45mm.

[0105] After receiving signals reflected from inside the body, the dual-frequency electromagnetic transceiver compares the signals with the standard electrical characteristic values ​​of healthy tissue. If a loss factor greater than 38.5 is detected, indicating a specific electrical characteristic value reflecting inflammation, then inflammation is determined to exist in that area. A precise three-dimensional model of the lesion area is constructed using an inverse scattering algorithm, with a lesion volume accuracy of ±2 mm³. For example, a typical lumbar disc herniation lesion appears as an elliptical area of ​​abnormal dielectric properties at the posterior margin of the L4-L5 intervertebral space, with its major axis typically greater than 8 mm.

[0106] Traditional techniques using a single frequency cannot simultaneously detect lesions in both superficial ligaments and deep tissues. Conventional imaging equipment struggles to quantify the degree of inflammation in real time. Dual-frequency synergy overcomes the limitations of scanning depth, enabling simultaneous detection of multiple tissue layers. By objectively quantifying the degree of inflammation through electrical characteristic parameters, it provides a direct basis for setting the intensity and duration of subsequent treatments, avoiding empirical operational errors.

[0107] The workflow of the strategy generation module is as follows:

[0108] Based on the analysis results, a treatment plan is formulated. First, the energy ratio and waveform type of high and low frequencies are allocated according to the patient's specific physical type, as follows:

[0109] For phlegm-dampness constitution, high-frequency energy accounts for 65%-70%, the waveform mode is continuous wave, and the temperature control threshold is ≤39℃;

[0110] For those with Yang deficiency, high-frequency energy accounts for 78%-85%, the waveform mode is square wave, and the temperature control threshold is ≤41℃;

[0111] For those with Qi deficiency, high-frequency energy should account for 50%-55%, the waveform mode should be sine wave, and the temperature control threshold should be ≤38℃.

[0112] For individuals with blood stasis, high-frequency energy accounts for 75%-80%, the waveform mode is pulse wave, and the temperature control threshold is ≤40℃;

[0113] For those with Yin deficiency, high-frequency energy should account for 45%-50%, the waveform mode should be intermittent, and the temperature control threshold should be ≤37℃.

[0114] Secondly, the energy intensity of the high-frequency wave is set according to the detected lesion depth. A depth of 35mm is the energy jump threshold. For every 1mm increase or decrease in depth, the energy intensity of the high-frequency wave increases or decreases by 0.8W.

[0115] Finally, the total treatment time is adjusted according to the severity of the inflammation, which is divided into 1-10 levels, with an additional 2 minutes of treatment time for each level of severity.

[0116] The intelligent learning chip optimizes parameter combinations in real time. For example, for a patient with a Yang deficiency constitution, a central disc herniation at the L5-S1 position, and an inflammation level of 7, the system ultimately generates the following treatment plan: high-frequency power 22W, low-frequency wave using square wave mode with its on time accounting for 60%, and a total treatment time of 18 minutes. The treatment parameters are wirelessly transmitted to the treatment composite guide head for execution.

[0117] The strategy generation module establishes a multivariate decision model and automatically generates the optimal parameter combination through algorithms to ensure that the treatment plan simultaneously meets the requirements of physical adaptability, disease targeting, and safety, thereby significantly improving the treatment effectiveness.

[0118] The workflow of the tolerance feedback module is as follows:

[0119] The tolerance feedback module implements triple protection during treatment, monitoring the patient's status in real time to ensure safety. First, impedance monitoring measures the overall impedance value of the treatment area every 200ms. If five consecutive measurements show a decrease of more than 18% compared to the initial value, the high-frequency power is immediately reduced to 10W. Second, temperature monitoring uses densely packed temperature sensors inside the guide to continuously monitor skin temperature. If the temperature at a certain point rises by 18% within 3 seconds, the semiconductor cooling chip inside the composite guide is immediately activated to locally cool that point. Third, distance monitoring uses a distance sensor to continuously detect the distance between the guide and the skin surface. If the distance is ≤3.5mm, an audible and visual alarm is issued, and energy output is immediately stopped. All abnormal events are recorded in detail in the safety log.

[0120] Multi-dimensional real-time protection fundamentally avoids safety hazards; impedance drop warning reflects abnormal tissue reactions; precise temperature control prevents local overheating; distance protection eliminates mechanical damage; and safety log recording provides data support for subsequent optimization.

[0121] The workflow of the efficacy evaluation module is as follows:

[0122] Efficacy assessment is conducted throughout the entire treatment process. The efficacy assessment mainly relies on the laser imaging lens inside the guide head. The laser imaging lens emits a 635nm wavelength laser to scan a skin area of ​​approximately 10×10cm, capturing 25 blood flow distribution images per second.

[0123] The evaluation process is as follows: Before treatment, the average blood flow velocity is calculated in the core area of ​​inflammation, which is usually 0.8 mm / s; at the 9th minute of treatment, the average blood flow velocity in this area is remeasured, and the immediate improvement rate of blood flow velocity is calculated; after treatment, the reduction rate of inflammation area is calculated using infrared thermography; combining the immediate improvement rate and the reduction rate of inflammation area, the blood flow improvement rate is given a weight of 65%, and the area reduction rate is given a weight of 35%, and the comprehensive efficacy index TEI is calculated. If TEI > 35%, the treatment is considered effective; otherwise, the parameters are re-optimized.

[0124] By setting up an efficacy evaluation module, a closed-loop verification of the entire treatment process can be achieved. During treatment, real-time feedback on blood flow changes allows for dynamic adjustment of parameters, and the TEI index is quantified after treatment to objectively determine efficacy, forming a complete closed loop of "treatment-evaluation-optimization" and significantly improving the effectiveness rate of a single treatment.

[0125] To achieve simultaneous output of two electromagnetic waves of different frequencies through the same guide, the higher frequency signal of 40.68MHz is first split into two paths: the I path and the Q path. A modulation wave of 13.56MHz is loaded onto the Q path. Finally, the two processed signals are recombined within a specific intermediate frequency range. The specific operation steps are as follows: A high-frequency signal source generates a 40.68MHz signal; this signal is split into two paths: the I path passes directly; the Q path first passes through a digital phase shifter to offset its phase by 90 degrees; the offset Q path signal is mixed with the 13.56MHz signal in an analog multiplier; the mixed signal is then recombined with the original I path signal; the recombined signal passes through a filter, allowing only frequencies between 36-42MHz to pass through, in order to eliminate unnecessary interference waves; finally, the processed composite signal is amplified by a power amplifier to ensure the purity of the final output waveform and drive the composite guide.

[0126] Working principle: The patient holds the portable terminal with both hands, simultaneously triggering the acquisition of physiological parameters. The central processing unit inputs bioelectrical impedance data, hand thermal image data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data into the meridian admittance model. Based on preset rules, it automatically determines the body constitution type and generates an electronic report containing body constitution classification and energy balance coefficient. In the lesion scanning stage, the operator moves the composite guide head at the end of the robotic arm along the patient's spine. The dual-frequency electromagnetic transceiver simultaneously emits low-frequency and high-frequency waves. By receiving tissue reflection signals and comparing them with healthy electrical characteristic values, a three-dimensional lesion model with an inflammation determination threshold of >38.5 is constructed, and the location coordinates, volume, and depth data of the inflammation are recorded simultaneously. Based on the dual-channel input of body constitution and lesion data, the strategy generation module first configures the waveform and energy ratio according to the body constitution type, then adjusts the high-frequency power according to the lesion depth, and finally sets the duration based on the inflammation level. After the intelligent learning chip optimizes the parameter combination, the composite guide head outputs energy through wireless transmission.

[0127] Throughout the treatment, a tolerance feedback module provides triple protection. An impedance monitoring unit scans tissue impedance every 200ms; if the impedance drops by more than 18% after five consecutive scans, the power is reduced to 10W. A temperature sensor network monitors the skin at 0.5mm intervals; when the local temperature rise rate reaches 18% within 3 seconds, the semiconductor cooling chip is activated. A distance sensor cuts off energy and triggers an alarm when the guide is ≤3.5mm from the skin. Simultaneously, the efficacy evaluation module captures 25 frames of blood flow images per second using a 635nm laser lens, calculating the blood flow improvement rate in the treatment core area in real time. Post-treatment, this is combined with infrared thermography to obtain the inflammation area reduction rate, generating a comprehensive efficacy index (TEI) >35% for effective treatment. All data is integrated into a central system, driving continuous iterative optimization of the parameter model.

[0128] It also includes: a preprocessing module, which is used by the constitution analysis module to preprocess the bioelectrical impedance data, hand thermal image data, humidity data, grip strength data, heart rate and pulse data and fingertip microcirculation data collected by the handheld portable terminal before inputting them into the meridian admittance model and determining the constitution type.

[0129] The preprocessing module includes:

[0130] The alignment unit is used to treat the bioelectrical impedance data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data as multi-dimensional data to be processed, and to align the multi-dimensional data to be processed based on the time series.

[0131] The feature extraction unit is used to input the aligned multi-dimensional data to be processed into a pre-trained feature extraction model to extract features and obtain the feature data corresponding to the multi-dimensional data to be processed.

[0132] Anomaly detection unit, used for:

[0133] Take any one dimension of the multi-dimensional data to be processed as the first dimension.

[0134] Calculate the correlation index between the first-dimensional data and the data in other dimensions of the multi-dimensional data to be processed, except for the first-dimensional data, to obtain several correlation indices;

[0135] The summation of several correlation indices is used as the first-dimensional correlation evaluation index.

[0136] By traversing all dimensions of the multi-dimensional data to be processed, several relevance evaluation indices are obtained.

[0137] The evaluation weight of each dimension is determined based on several relevance evaluation indices;

[0138] Calculate the difference between the data in the same dimension corresponding to two adjacent time series points to obtain the data difference for each dimension;

[0139] Multiply the data difference corresponding to each dimension by the evaluation weight of each dimension to obtain several products; use the sum of several products as the difference index of the data corresponding to two adjacent time series points; iterate through all time series points to obtain several difference indices.

[0140] Calculate the local fluctuation value of each difference index within its neighborhood;

[0141] The local fluctuation value is compared with the preset local fluctuation threshold, and the data corresponding to the time series point when the local fluctuation value is greater than or equal to the preset local fluctuation threshold is regarded as abnormal data.

[0142] Iterate through the data corresponding to all time series points to obtain several abnormal data points;

[0143] The data cleaning unit is used for:

[0144] Obtain preset data cleaning rules;

[0145] Based on the preset data cleaning rules, the several abnormal data are cleaned to obtain preprocessed bioelectrical impedance data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data.

[0146] In this embodiment, the mean of the difference index within the neighborhood range of each difference index is calculated to obtain the difference mean index; the difference between each difference index and the difference mean index is used as the local fluctuation value of each difference index within the neighborhood range.

[0147] The working principle and beneficial effects of the above technical solution are as follows: The preprocessing module first aligns the multi-dimensional data to be processed, including bioelectrical impedance data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data, based on time series. Then, the aligned multi-dimensional data to be processed is input into a pre-trained feature extraction model for feature extraction to obtain the corresponding feature data. One dimension of the data to be processed is randomly selected as the first dimension, and its correlation index with other dimensions is calculated. By traversing all dimensions, the correlation evaluation index for each dimension is obtained, thereby determining the evaluation weight of each dimension. The purpose of this step is to assess the relative importance of each dimension in the overall data. The difference between the data of the same dimension corresponding to two adjacent time series points is calculated, and a difference index is obtained by combining the evaluation weight of each dimension. Several difference indices are obtained by traversing all time series points, and then the local fluctuation value of each difference index within its neighborhood is calculated. The local fluctuation value is compared with a preset local fluctuation threshold, and the data corresponding to the time series point where the local fluctuation value is greater than or equal to the preset local fluctuation threshold is identified as outlier data. This is to detect abnormal fluctuations in the data; then, preset data cleaning rules are obtained to clean several abnormal data points, resulting in preprocessed data of various types. Data cleaning rules can be set according to the specific characteristics of the medical data and the application scenario. Through a series of operations such as data alignment, feature extraction, abnormal data detection, and cleaning, the quality of data input into the constitution analysis module can be effectively improved. Effective handling of abnormal data enhances the reliability of the entire superconducting treatment system. It reduces the interference of abnormal data on subsequent system analysis and decision-making, making operations such as constitution analysis and treatment parameter setting based on this data more reliable, thereby improving the accuracy and effectiveness of the entire treatment system.

[0148] The strategy generation module allocates the ratio of high and low frequency energy according to body type, sets the high frequency power according to the depth of the lesion, adjusts the treatment duration according to the inflammation level, and optimizes the combination of parameters, including:

[0149] Acquire a medical knowledge graph; the medical knowledge graph includes a medical knowledge graph, a knowledge graph of human physiological and pathological characteristics, a knowledge graph of the electromagnetic properties of biological tissues, a knowledge graph of medical sensors and monitoring technologies, a knowledge graph of electromagnetic wave therapy technologies, and a knowledge graph of efficacy evaluation indicators;

[0150] Based on the aforementioned medical knowledge graph, body constitution types lesion depth and inflammation level Define variables; where, There are n categories, corresponding to the ratio of high and low frequency energy. , Indicates the proportion of high-frequency energy, 1- Indicates the proportion of low-frequency frequencies; There are m levels in total, with increasing depth, corresponding to high-frequency power. Power increases with depth; There are n levels in total, with increasing inflammation, corresponding to treatment durations. The duration increases with the severity of inflammation;

[0151] Based on body type lesion depth and inflammation level Constructing a rating matrix Association strength constitution - deep association and depth-inflammation association ;

[0152] Based on the rating matrix Association strength constitution - deep association and depth-inflammation association Determine the ratio of high and low frequency energy High-frequency power and treatment duration ,in,

[0153]

[0154] in, The optimal solution representing the ratio of high to low frequency energy; Indicates the constitution type index; Indicates an index of inflammation severity; This represents the ideal treatment outcome score under the combination of "Constitution U + Inflammation A"; Indicates the strength of the synergistic effect of constitution-depth-inflammation; for all lesion depths Connecting physical constitution with depth , depth power Treatment duration Deep-inflammation association Multiply and then sum; Represents the regularization coefficient;

[0155]

[0156] in, The optimal solution representing high-frequency power; Represents the regularization coefficient; Indicates the ratio of high to low frequency energy;

[0157]

[0158] in, The optimal solution representing the treatment duration; Represents the regularization coefficient; This indicates the strength of the intermediate association between depth and inflammation.

[0159] In this embodiment, the objective function is optimized to minimize the error between the "actual therapeutic effect of the parameter combination" and the "ideal effect score," while avoiding extreme parameter values ​​(regularization constraints). The actual effect is determined by the synergistic effect of the parameters, which can be expressed as:

[0160]

[0161] Specifically, it means: the proportion of high-frequency energy in body constitution u. With depth power By correlation strength Coupled, and then with inflammation Treatment duration and correlation strength It serves its purpose and achieves practical results.

[0162] Construct the objective function

[0163]

[0164] Among them, the constraint condition is: (0 < < 1) (The ratio of high to low frequencies is reasonable); Power safety range; Reasonable treatment duration; regularization term , , A value greater than 0 is used to prevent excessively large parameters from causing side effects.

[0165] An iterative method of "alternating fixed parameters and solving for the optimal solution of a single variable" is adopted to gradually converge to the global optimum;

[0166] 1. High-frequency and low-frequency energy ratio optimal solution

[0167] fixed , Regarding the objective function Find the partial derivative and set it to 0;

[0168]

[0169] Summarized as follows: ; ;

[0170] 2. High-frequency power optimal solution

[0171] fixed , Regarding the objective function Find the partial derivative and set it to 0:

[0172]

[0173] Summarized as follows:

[0174] 3. Treatment duration optimal solution

[0175] fixed , Regarding the objective function Find the partial derivative and set it to 0:

[0176]

[0177] Summarized as follows:

[0178] in, , indicating the strength of the intermediate association between depth and inflammation.

[0179] The working principle and beneficial effects of the above technical solution are as follows: Because the strategy generation module allocates the ratio of high and low frequency energy according to the patient's physical type, sets the high-frequency power according to the lesion depth, and adjusts the treatment duration according to the inflammation level, this approach fully considers individual patient differences. Patients with different physical types may have different energy absorption and responses; different lesion depths require different power levels to achieve effective treatment; and different inflammation levels require different treatment durations to ensure inflammation elimination. By acquiring knowledge graphs from various medical fields, including knowledge graphs of human physiological and pathological characteristics and the electromagnetic properties of biological tissues, a scientific basis is provided for setting treatment parameters. Scoring matrices and correlation strength matrices are constructed, and based on these matrices, the optimal solutions for the high and low frequency energy ratio, high-frequency power, and treatment duration are determined. This optimized combination approach can reduce unnecessary energy consumption and minimize damage to normal tissues while ensuring therapeutic efficacy.

[0180] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0181] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A dual-frequency single-guide head output superconducting therapy system, characterized in that, include: A mobile treatment trolley with a multi-directional adjustable robotic arm on top; The composite probe, installed at the end of the robotic arm, integrates a bioelectrical impedance measurement electrode, a dual-frequency electromagnetic transceiver that simultaneously transmits low-frequency modulated waves and high-frequency continuous waves, a laser imaging lens, a platinum resistance temperature sensor, and a semiconductor refrigeration chip. The handheld portable terminal is connected to the trolley via a cable. There are two handheld portable terminals, one for the patient's left hand and one for the right hand to hold. The portable terminal integrates multiple electrode points, an infrared camera, a humidity sensor, a grip force sensor, a heart rate and pulse monitor, and a Doppler probe. The central control system, with a built-in intelligent learning chip, includes: The body constitution analysis module, based on bioelectrical impedance data, hand thermal image data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data collected by a handheld portable terminal, inputs them into the meridian admittance model to determine the body constitution type and generates a body constitution and energy status report. The lesion scanning module scans the patient's body tissues through a dual-frequency electromagnetic transceiver, simultaneously emitting low-frequency modulated waves and high-frequency continuous waves, and determines inflammation and constructs a lesion model based on the loss factor. The strategy generation module allocates the ratio of high and low frequency energy according to the body type, sets the high frequency power according to the depth of the lesion, adjusts the treatment time according to the inflammation level, and optimizes the combination of parameters. The strategy generation module includes: Acquire a medical knowledge graph; the medical knowledge graph includes a medical knowledge graph, a knowledge graph of human physiological and pathological characteristics, a knowledge graph of the electromagnetic properties of biological tissues, a knowledge graph of medical sensors and monitoring technologies, a knowledge graph of electromagnetic wave therapy technologies, and a knowledge graph of efficacy evaluation indicators; Based on the aforementioned medical knowledge graph, body constitution types lesion depth and inflammation level Define variables; where, There are n categories, corresponding to the ratio of high and low frequency energy. , Indicates the proportion of high-frequency energy, 1- Indicates the proportion of low-frequency frequencies; There are m levels in total, with increasing depth, corresponding to high-frequency power. Power increases with depth; There are n levels in total, with increasing inflammation, corresponding to treatment durations. The duration increases with the severity of inflammation; Based on body type lesion depth and inflammation level Constructing a rating matrix Association strength constitution - deep association and depth-inflammation association ; Based on the rating matrix Association strength constitution - deep association and depth-inflammation association Determine the ratio of high and low frequency energy High-frequency power and treatment duration ,in, in, The optimal solution representing the ratio of high to low frequency energy; Indicates the constitution type index; Indicates an index of inflammation severity levels; This represents the ideal treatment outcome score under the "Constitution U + Inflammation A" combination; Indicates the strength of the synergistic effect of constitution-depth-inflammation; for all lesion depths Connecting physical constitution with depth , depth power Treatment duration Deep-inflammation association Multiply and then sum; Represents the regularization coefficient; in, The optimal solution representing high-frequency power; Represents the regularization coefficient; Indicates the ratio of high to low frequency energy; in, The optimal solution representing the treatment duration; Represents the regularization coefficient; Indicates the strength of the intermediate association between depth and inflammation; The tolerance feedback module performs impedance monitoring, temperature control, and distance protection in real time, and records and stores abnormal condition data. The efficacy assessment module acquires blood flow distribution maps and infrared thermograms, calculates the blood flow improvement rate and the inflammation area reduction rate, and judges the treatment effect. The preprocessing module is used by the body constitution analysis module to preprocess the bioelectrical impedance data, hand thermal image data, humidity data, grip strength data, heart rate and pulse data and fingertip microcirculation data collected by the handheld portable terminal before inputting them into the meridian admittance model and determining the body constitution type. The preprocessing module includes: The alignment unit is used to treat the bioelectrical impedance data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data as multi-dimensional data to be processed, and to align the multi-dimensional data to be processed based on the time series. The feature extraction unit is used to input the aligned multi-dimensional data to be processed into a pre-trained feature extraction model to extract features and obtain the feature data corresponding to the multi-dimensional data to be processed. Anomaly detection unit, used for: Take any one dimension of the multi-dimensional data to be processed as the first dimension. Calculate the correlation index between the first-dimensional data and the data in other dimensions of the multi-dimensional data to be processed, except for the first-dimensional data, to obtain several correlation indices; The summation of several correlation indices is used as the first-dimensional correlation evaluation index. By traversing all dimensions of the multi-dimensional data to be processed, several relevance evaluation indices are obtained. The evaluation weight of each dimension is determined based on several relevance evaluation indices; Calculate the difference between the data in the same dimension corresponding to two adjacent time series points to obtain the data difference for each dimension; Multiply the data difference corresponding to each dimension by the evaluation weight of each dimension to obtain several products; use the sum of several products as the difference index of the data corresponding to two adjacent time series points; iterate through all time series points to obtain several difference indices. Calculate the local fluctuation value of each difference index within its neighborhood; The local fluctuation value is compared with the preset local fluctuation threshold, and the data corresponding to the time series point when the local fluctuation value is greater than or equal to the preset local fluctuation threshold is regarded as abnormal data. Iterate through the data corresponding to all time series points to obtain several abnormal data points; The data cleaning unit is used for: Obtain preset data cleaning rules; Based on the preset data cleaning rules, the several abnormal data are cleaned to obtain preprocessed bioelectrical impedance data, humidity data, grip strength data, heart rate and pulse data, and fingertip microcirculation data.

2. The dual-frequency single-guide head output superconducting therapy system according to claim 1, characterized in that, The specific working method of the body composition analysis module is as follows: The patient holds the handheld portable terminal with both hands to undergo testing; Electrode points were used to measure the patient's bioelectrical impedance data in the 5Hz-100kHz frequency band, and the resistance and capacitance values ​​were extracted. Infrared cameras acquire thermal images of the hand and detect abnormal areas with temperature differences greater than 2°C; The humidity sensor uses capacitive detection to detect sweat secretion on the palm, with an accuracy of ±3%RH. The grip strength sensor has a range of 0-100kg and an accuracy of ±0.5kg to obtain the strength of the hand grip. The heart rate and pulse monitor has a sampling frequency of 1 kHz and a pressure resolution of 0.1 kPa, and detects the patient's heart rate and pulse frequency and intensity. The Doppler probe has a wavelength of 785nm and a sampling rate of 50Hz to monitor the microcirculation of blood in the patient's fingertips. The central processing unit inputs different types of test data into the meridian conduction model to determine the patient's constitution type and generate an electronic report that includes constitution classification and the body's energy balance status.

3. The dual-frequency single-guide head output superconducting therapy system according to claim 1, characterized in that, The specific working method of the lesion scanning module is as follows: The composite probe moves longitudinally along the patient's spine to scan, while the dual-frequency electromagnetic transceiver simultaneously transmits a 13.56MHz low-frequency wave and a 40.68MHz high-frequency wave. A dual-frequency electromagnetic transceiver compares the reflected signal with the standard electrical characteristic values ​​of healthy tissue to determine whether inflammation is present. Construct a three-dimensional model of the lesion area with a lesion volume accuracy of ±2mm³.

4. The dual-frequency single-guide head output superconducting therapy system according to claim 1, characterized in that, The specific working method of the strategy generation module is as follows: The proportion and waveform type of high and low frequency energy are allocated according to the patient's specific physical condition. The energy intensity of the high-frequency wave is set according to the detected lesion depth; The total treatment duration is adjusted according to the severity of the inflammation; The intelligent learning chip optimizes the parameter combination in real time, and the treatment parameters are wirelessly transmitted to the composite guide for execution.

5. The dual-frequency single-guide head output superconducting therapy system according to claim 1, characterized in that, The tolerance feedback module further includes: Impedance monitoring unit, configured to acquire impedance values ​​of the treatment area every 200ms; The temperature control unit is configured to continuously monitor skin temperature using a temperature sensor. If the temperature rises too quickly, it will activate the semiconductor cooling chip in the composite head to cool the skin locally. The distance protection unit is configured to continuously detect the distance between the probe and the skin surface. If the distance is too close, an alarm will be triggered and energy output will be stopped.

6. The dual-frequency single-guide head output superconducting therapy system according to claim 1, characterized in that, The specific working method of the efficacy assessment module is as follows: The laser imaging lens scans the skin area, capturing 25 blood flow distribution images per second. The mean blood flow velocity in the area was remeasured during the treatment, and the immediate improvement rate of blood flow velocity was calculated. The reduction rate of inflammation area was calculated using infrared thermography after treatment. Weights were assigned to the immediate improvement rate of blood flow velocity and the reduction rate of inflammation area. A Comprehensive Efficacy Index (TEI) is generated, and the effectiveness of treatment is determined based on the TEI value.

7. A dual-frequency single-guide head output superconducting therapy system according to claim 2, characterized in that, The rules for determining the body type are as follows: If the conductivity deviation is greater than 15% and the humidity data is greater than 65%RH, it is marked as phlegm-dampness constitution; if the area of ​​palm temperature below 32℃ accounts for more than 40%, it is marked as yang deficiency constitution; if the grip strength data is less than 30kg, the heart rate variability is less than 40ms and the pulse wave attenuation slope is greater than 15% / s, it is marked as qi deficiency constitution; if the microcirculation blood flow velocity at the fingertips is less than 0.5mm / s, it is marked as blood stasis constitution; if the palm skin capacitance value is greater than 120pF, it is marked as yin deficiency constitution.

8. The dual-frequency single-guide head output superconducting therapy system according to claim 4, characterized in that, The specific allocation of high and low frequency energy ratios and waveform types based on the patient's specific physical condition is as follows: For phlegm-dampness constitution, high-frequency energy accounts for 65%-70%, the waveform mode is continuous wave, and the temperature control threshold is ≤39℃; for yang deficiency constitution, high-frequency energy accounts for 78%-85%, the waveform mode is square wave, and the temperature control threshold is ≤41℃; for qi deficiency constitution, high-frequency energy accounts for 50%-55%, the waveform mode is sine wave, and the temperature control threshold is ≤38℃; for blood stasis constitution, high-frequency energy accounts for 75%-80%, the waveform mode is pulse wave, and the temperature control threshold is ≤40℃; for yin deficiency constitution, high-frequency energy accounts for 45%-50%, the waveform mode is intermittent wave, and the temperature control threshold is ≤37℃.

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