A control method and system suitable for massage therapy instrument

Abstract

The present invention discloses a control method and system suitable for a massage therapy instrument, which relates to the technical field of physical therapy equipment, including: real-time collection of user's physical sign parameters, analysis of muscles, meridians and pain status, and generation of matching personalized treatment parameters; based on the personalized treatment parameters, dynamically adjusting the negative pressure adsorption force of the target area, and monitoring the adsorption status in real time; applying medium-frequency electric pulses to the target area on the basis of negative pressure adsorption, and dynamically adjusting the electric pulse parameters in combination with the adsorption status; based on feedback data of the target area after the medium-frequency electric pulse acts, controllable heat is transferred to deep tissues through a thermal energy device in the negative pressure adsorption area; after the controllable heat transfer is completed, high-frequency sound waves are released in the negative pressure adsorption area to perform micro-vibration of cell gaps; according to the feedback data, the present invention uses a thermal energy transfer mechanism to accurately act on deep tissues, improve blood flow and promote muscle relaxation.

Description

Technical Field

[0001] The present invention relates to the technical field of physical therapy equipment, and in particular to a control method and system suitable for a massage therapy device. Background Art

[0002] In recent years, with the increasing demand for intelligent and personalized treatment, massage therapy technology has gradually developed in a more precise and dynamic direction. Existing massage therapy equipment usually relies on fixed treatment modes or simple manual adjustments, which are difficult to customize and adjust in real time according to the user's specific physiological parameters. For example, traditional equipment often cannot provide sufficient flexibility and treatment depth for different users' muscle fatigue, blood flow conditions, meridian blockage and other problems. This leads to differences in treatment effects and inefficiency.

[0003] The shortcomings of existing technologies are mainly reflected in the inability to monitor in real time and automatically adjust treatment parameters according to the user's physiological feedback. For example, the negative pressure adsorption force and electric pulse frequency of traditional massage instruments are mostly preset values, which cannot be adjusted in time according to changes in electromyographic signals or blood flow status, resulting in difficulty in achieving the optimal treatment effect. In addition, existing treatment methods usually only focus on a single function, such as negative pressure adsorption or medium-frequency electric pulses, and lack the coordination of multiple treatment methods. Therefore, how to integrate multiple physical treatment methods and adjust various parameters in real time according to user feedback is a core problem that current technology urgently needs to solve. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a control method suitable for a massage therapy device to solve the problem that existing massage therapy equipment cannot dynamically adjust treatment parameters according to the real-time physiological state of the user.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a control method for a massage therapy device, which comprises: collecting physical sign parameters of a user in real time, analyzing muscle, meridian and pain status, and generating matching personalized treatment parameters;

[0008] Based on personalized treatment parameters, the negative pressure adsorption force of the target area is dynamically adjusted, and the adsorption status is monitored in real time;

[0009] Apply medium-frequency electric pulses to the target area based on negative pressure adsorption, and dynamically adjust the electric pulse parameters according to the adsorption state;

[0010] Based on the feedback data of the target area after the medium-frequency electric pulse, the heat energy device in the negative pressure adsorption area transfers controllable heat to the deep tissue;

[0011] After the controllable heat transfer is completed, high-frequency sound waves are released in the negative pressure adsorption area to cause micro-vibration of the cell gaps.

[0012] As a preferred solution of the control method applicable to the massage therapy apparatus described in the present invention, the user's physical sign parameters include muscle state parameters, meridian state parameters, pain state parameters, skin state parameters and blood flow state parameters.

[0013] As a preferred solution of the control method for the massage therapy apparatus of the present invention, the specific steps of generating matching personalized treatment parameters are as follows:

[0014] Normalize and filter the collected vital sign parameters to extract the electromyographic signal and skin conductivity data of the target area;

[0015] Calculate muscle tension and fatigue levels based on electromyographic signals and divide tension and fatigue states within a region;

[0016] Based on the divided tension and fatigue states, combined with skin conductivity data, the sensitive areas of meridians are located and the degree of patency is analyzed;

[0017] The meridian blockage area is demarcated according to the degree of patency;

[0018] According to the calibrated meridian blockage area information, combined with the normalized and filtered blood flow state parameters, the regional blood supply and oxygen supply are analyzed, and the low perfusion area is marked;

[0019] The marked low perfusion areas are used to generate personalized treatment parameters for negative pressure adsorption force, electric pulse intensity value and frequency, thermal energy transfer intensity and sound wave frequency.

[0020] As a preferred solution of the control method for the massage therapy apparatus of the present invention, the negative pressure adsorption force of the target area is dynamically adjusted based on the personalized treatment parameters, and the adsorption state is monitored in real time. The specific steps are as follows:

[0021] Initially set the negative pressure regulating device of the massage therapy device through personalized treatment parameters;

[0022] Obtain the blood flow state gradient value of the target area through flexible sensors and muscle tension gradient ;

[0023] After the initial setting, the negative pressure regulating device is fitted to the target area, and the negative pressure adsorption force is adjusted based on the marked low perfusion area in real time. The expression is:

[0024] ;

[0025] in, Indicates time The negative pressure adsorption force, Indicates the initial negative pressure adsorption force, represents the blood flow gradient coefficient, Indicates the gradient value of blood flow state, represents the integral coefficient of muscle tension, Indicates the muscle tension gradient value in the target area. Indicates the initial muscle tension gradient value of the target area. represents the time element;

[0026] The blood flow gradient value and muscle tension gradient , fed back to the negative pressure adsorption force adjustment formula, and the negative pressure adsorption force is adjusted in real time;

[0027] If the blood flow increases, the negative pressure adsorption force will be gradually reduced to avoid over-adsorption;

[0028] If the muscle tension changes, the negative pressure adsorption force will be increased, thus enhancing the treatment effect;

[0029] Based on the initial EMG signal of the target area , calculation time The gradient value of the electromyographic signal at time

[0030] Combined with the initial electromyographic signal and the electromyographic signal gradient value, normalizing the electromyographic signal gradient value to obtain a real-time normalized electromyographic signal gradient value;

[0031] According to the electromyographic signals collected in the target area, the electric pulse intensity value and the electric pulse frequency value are adaptively controlled in real time. The expression is:

[0032] ;

[0033] ;

[0034] in, Indicates time The electric pulse intensity value at Indicates the initial electric pulse intensity value, Indicates time The real-time normalized EMG signal gradient value, represents the initial electromyographic signal, represents the electric field adjustment coefficient, represents the frequency fluctuation coefficient, Indicates time The electric pulse frequency value at represents the initial electrical pulse frequency, represents the frequency fluctuation factor, Indicates that over time Varying sine waves;

[0035] According to the real-time normalized electromyographic signal gradient value, the time The electric pulse intensity value at Expression to adjust the electric pulse intensity value;

[0036] Use over time Changing sine wave Adjust time The electrical pulse frequency value ;

[0037] The degree of muscle fatigue is assessed by monitoring the real-time normalized electromyographic signal gradient value of the target area. If the degree of muscle fatigue gradually decreases, the electric pulse intensity value is gradually reduced.

[0038] Real-time monitoring of temperature distribution in the target area through flexible sensors;

[0039] During the action of high-frequency sound waves at the sound wave frequency, the echo signal of the deep tissue is collected in real time by using the ultrasonic echo signal receiving device;

[0040] The sound wave frequency is adjusted in real time according to the changes in the echo signal intensity of the deep tissue.

[0041] As a preferred solution of the control method for the massage therapy apparatus of the present invention, wherein: applying medium frequency electric pulses to the target area on the basis of negative pressure adsorption, and dynamically adjusting the electric pulse parameters in combination with the adsorption state, the specific steps are as follows:

[0042] Under the action of negative pressure adsorption, the conductivity distribution data of the skin in the target area is collected through the flexible sensor;

[0043] Based on the conductivity distribution data, combined with the muscle state parameters and blood flow state parameters of the target area, the changes in tissue conductivity are dynamically evaluated and real-time conductivity distribution data is output;

[0044] According to the real-time conductivity distribution data, the electrode array number and arrangement parameters of the target area are selected, and the electrode group with output current and phase adjustment is formed into an electrode array;

[0045] Using the real-time conductivity distribution data after dynamic evaluation, the output current and phase relationship of the electrode array are dynamically adjusted to form a three-dimensional electric field focusing;

[0046] By integrating the dynamic feedback mechanism, the three-dimensional electric field focusing is adaptively adjusted according to the real-time conductivity of the target area, and the expression is:

[0047] ;

[0048] in, Indicates time The electric field strength at represents the initial electric field strength, Indicates time The conductivity gradient at represents the electric field phase that changes with time, μ represents the conductivity gradient adjustment coefficient, Represents the periodic changes of electromagnetic signals in the electric field;

[0049] The intensity and frequency of the medium-frequency electric pulses are adjusted by combining the real-time conductivity distribution data of the target area with the three-dimensional electric field feedback.

[0050] As a preferred solution of the control method for the massage therapy apparatus of the present invention, wherein: based on the feedback data of the target area after the medium frequency electric pulse is applied, the controllable heat is transferred to the deep tissue through the thermal energy device in the negative pressure adsorption area, and the specific steps are as follows:

[0051] Collecting feedback data during the operation of the adjusted intensity and frequency of the medium frequency electrical pulses;

[0052] The heat transfer value is calculated based on the feedback data and the muscle state parameters and blood flow state parameters of the target area;

[0053] According to the heat transfer value, the output power is adjusted by the thermal energy device in the negative pressure adsorption area;

[0054] Adopting the principle of heat conduction, heat energy is transferred from the skin surface to the deep tissue through the heat conduction panel;

[0055] At the same time, during the heat transfer process, the heat transfer coefficient is fine-tuned to control the speed of heat transfer, and the output power of the thermal energy device is automatically adjusted according to the temperature changes in the target area.

[0056] As a preferred solution of the control method for the massage therapy apparatus of the present invention, after the controllable heat transfer is completed, high-frequency sound waves are released in the negative pressure adsorption area to perform micro-vibration of the cell gaps, and the specific steps are as follows:

[0057] The temperature of the target area is monitored in real time through the temperature sensor. When the temperature of the deep tissue stabilizes within the preset treatment range, the high-frequency sound wave release is triggered.

[0058] The frequency of the high-frequency sound waves is initially set according to the tissue characteristics of the target area, and the monitoring signals are collected in real time through the micro-vibration sensor;

[0059] Matching the resonant frequency in the monitoring signal with the natural vibration frequency of the intercellular space to trigger the resonant state;

[0060] Collect response data of the resonance state of the target area through a micro-vibration sensor;

[0061] Analyze the changes in electromyographic signals, blood flow and muscle status in the target area, combine the response data of the micro-vibration sensor, and dynamically adjust the power and frequency of the sound waves.

[0062] In a second aspect, the present invention provides a control system suitable for a massage therapy apparatus, comprising: a physical sign acquisition module, a parameter generation module, an adjustment module, a heat energy transfer module and a high-frequency sound wave module;

[0063] The physical sign collection module is used to collect the user's physical sign parameters in real time, analyze the muscle, meridian and pain status, and generate matching personalized treatment parameters;

[0064] The parameter generation module is used to dynamically adjust the negative pressure adsorption force of the target area based on the personalized treatment parameters, and monitor the adsorption state in real time;

[0065] The regulating module is used to apply medium-frequency electric pulses to the target area on the basis of negative pressure adsorption, and dynamically adjust the electric pulse parameters in combination with the adsorption state;

[0066] The heat energy transfer module is used to transfer controllable heat to deep tissues through the heat energy device in the negative pressure adsorption area based on the feedback data of the target area after the medium frequency electric pulse is applied;

[0067] The high-frequency sound wave module is used to release high-frequency sound waves in the negative pressure adsorption area to perform micro-vibration of cell gaps after the controllable heat transfer is completed.

[0068] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the control method applicable to a massage therapy device as described in the first aspect of the present invention is implemented.

[0069] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the control method applicable to a massage therapy device as described in the first aspect of the present invention is implemented.

[0070] The beneficial effects of the present invention are as follows: the present invention generates personalized treatment plans and dynamically adjusts treatment parameters by collecting user vital sign parameters in real time; monitors indicators such as blood flow, muscle tension and skin conductivity, accurately identifies fatigue and blockage in the target area, and then adjusts the negative pressure adsorption force and the intensity and frequency of the medium-frequency electric pulses; based on feedback data, the heat energy transfer mechanism accurately acts on deep tissues, improves blood flow and promotes muscle relaxation; through high-frequency sound waves, micro-vibrations between cells in this process further promote tissue repair and microcirculation, significantly improving the user's comfort and treatment effect, and achieving more refined and personalized treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0072] Figure 1 This is a flow chart of the control method applicable to the massage therapy device in Example 1.

[0073] Figure 2 This is a module diagram of a control system suitable for a massage therapy device in Example 1. DETAILED DESCRIPTION

[0074] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0075] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0076] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0077] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, provides a control method suitable for a massage therapy instrument, comprising the following steps:

[0078] S1. Collect the user's physical parameters in real time, analyze the muscles, meridians and pain status, and generate matching personalized treatment parameters.

[0079] Furthermore, the user's physical sign parameters include muscle state parameters, meridian state parameters, pain state parameters, skin state parameters and blood flow state parameters;

[0080] Specifically, meridian status parameters are used to describe the patency and activity characteristics of human meridians, including the location of meridian sensitive areas, meridian patency (e.g., based on changes in skin conductivity), and the calibration of meridian blockage areas (e.g., the distribution and severity of blockage points);

[0081] Pain state parameters are used to quantify and locate the user's pain perception area and intensity, including the location of the pain area (determined by user feedback or nerve conduction signals), pain level (based on subjective ratings or changes in skin surface electrical activity signals), and dynamic changes in pain induction (such as a decrease in pain sensitivity during treatment).

[0082] Skin condition parameters are used to characterize the physiological and physical properties of the skin in the target area, including skin conductivity (used to reflect skin moisture content or meridian patency), skin temperature distribution (collected in combination with thermal sensors), and skin elasticity or thickness (detecting pressure distribution through flexible sensors).

[0083] Normalize and filter the collected vital sign parameters to extract the electromyographic signal and skin conductivity data of the target area;

[0084] Specifically, first, the physical sign parameters are normalized, and the minimum-maximum normalization method is used to map all parameters to range, thereby eliminating the impact of different vital sign parameters due to dimensional differences; then, filtering processing is performed. A bandpass filter (frequency range 20Hz to 500Hz) is used for the electromyographic signal to remove high-frequency noise and low-frequency interference, and a low-pass filter (cut-off frequency of 10Hz) is used for the skin conductivity data to smooth the signal and remove high-frequency interference, which is used to ensure that the vital sign parameter data has a unified scale and a high signal-to-noise ratio, which is convenient for subsequent analysis.

[0085] Calculate muscle tension and fatigue levels based on electromyographic signals and divide tension and fatigue states within a region;

[0086] Based on the divided tension and fatigue states, combined with skin conductivity data, the sensitive areas of meridians are located and the degree of patency is analyzed;

[0087] Specifically, by processing the collected electromyographic signals, first use a bandpass filter (frequency range 20Hz to 500Hz) to remove high-frequency noise and low-frequency interference to ensure the stability and accuracy of the signal; then, extract the key characteristic parameters of the signal, such as root mean square value (RMS), peak value, median frequency and spectral energy distribution, among which the RMS value is closely related to the contraction strength of the muscle. The larger the RMS value, the higher the muscle tension in the area, and then the area where the RMS is higher than the preset threshold is marked as the tense area; in the assessment of the degree of fatigue, use wavelet transform or fast Fourier transform (FFT) to analyze the spectral characteristics of the electromyographic signal and detect the changes in the electromyographic frequency. Usually, during continuous muscle activity, the median frequency (MF) will gradually shift to the low-frequency direction as fatigue accumulates, and the frequency The high-frequency components of the spectrum will gradually decay; on this basis, the rate of change of the median frequency and the decay rate of the high-frequency energy are calculated. If these change rates exceed the preset fatigue threshold (for example, the rate of decrease of the median frequency exceeds a certain threshold or the attenuation amplitude of the high-frequency energy is large), the area is marked as a fatigue area; in order to ensure the accuracy of the division, the characteristics of muscle tension and fatigue are dynamically smoothed in combination with the signal change trend within the time window to avoid misjudgment due to short-term fluctuations; finally, the signal characteristics of the target area are spatially clustered through a regional clustering algorithm (such as the K-means algorithm or the density clustering algorithm), and the target area is automatically divided into a high-tension area, a high-fatigue area and a normal area by using the joint characteristics of the RMS value and the frequency change, and further provide a decision-making basis for subsequent treatment based on the distribution map of tension and fatigue.

[0088] The meridian blockage area is demarcated according to the degree of patency;

[0089] According to the calibrated meridian blockage area information, combined with the normalized and filtered blood flow state parameters, the regional blood supply and oxygen supply are analyzed, and the low perfusion area is marked;

[0090] It should be noted that the marking of low perfusion areas is based on a comprehensive analysis of blood flow parameters and blood and oxygen supply conditions, and is judged using the following conditions:

[0091] First, laser Doppler imaging (LDI) is used to evaluate the blood flow distribution in the target area. If the blood perfusion value is detected to be lower than the preset threshold (for example, 50% of the average perfusion value), it is marked as a low perfusion area. Secondly, combined with pulse oximetry (SpO2), the blood oxygen saturation in the target area is analyzed. If the blood oxygen saturation is lower than the normal level (such as below 90%), its low perfusion nature is further confirmed. At the same time, the blood flow state parameters after normalization and filtering are used to dynamically analyze the changing trend of the blood perfusion level, and the regional blood supply stability is evaluated in combination with the rate of change within the time window. If the above indicators comprehensively determine that a certain area is insufficiently supplied with blood and has a low oxygen supply status, it will be marked as a low perfusion area. After marking, the information will be directly used to generate negative pressure adsorption force and other treatment parameters, and will serve as the basis for subsequent dynamic adjustment, thereby achieving precise treatment intervention.

[0092] Specifically, the laser Doppler imaging (LDI) technology is used to evaluate the blood flow distribution in the target area in combination with the blood flow status parameters after normalization and filtering, and the pulse oximetry (SpO2) technology is used to obtain blood oxygen saturation data. By cross-analyzing the blood perfusion level and oxygen supply status, the specific conditions of blood supply and oxygen supply in the area are determined.

[0093] The marked low perfusion areas are used to generate personalized treatment parameters for negative pressure adsorption force, electric pulse intensity value and frequency, thermal energy transfer intensity and sound wave frequency.

[0094] Specifically, first, based on the marked low perfusion area, the severity of the low perfusion area is determined in combination with blood flow, blood oxygen saturation and muscle status data;

[0095] Furthermore, for the negative pressure adsorption force, by calculating the area of ​​the low perfusion area and the degree of insufficient blood supply, the adsorption force is gradually adjusted (for example, the adsorption force is increased when the area is large, and the adsorption time is prolonged when the severity is high); for the electric pulse intensity value and frequency, according to muscle tension and fatigue level, adjustments are made according to the principle of reducing the intensity when the fatigue level is high, increasing the pulse interval, and increasing the intensity when the tension state is high; for the heat energy transfer intensity, combined with the skin conductivity data and meridian blockage, it is adjusted by transferring higher heat energy to areas with high blockage and lower heat energy to areas with low blockage; finally, for the sound wave frequency, according to the depth and area characteristics of the low perfusion area, the sound wave frequency is selected for precise adjustment: for deep areas, lower frequency sound waves are preferentially used to achieve better penetration effects; for superficial areas, higher frequency sound waves are used to concentrate on the surface tissues, thereby optimizing the treatment effect.

[0096] S2. Based on personalized treatment parameters, dynamically adjust the negative pressure adsorption force of the target area and monitor the adsorption status in real time.

[0097] Furthermore, the negative pressure regulating device of the massage therapy device is initially set through personalized treatment parameters;

[0098] It should be noted that the initial setting of the negative pressure regulating device of the massage therapy instrument through personalized treatment parameters refers to pre-setting the working parameters of the negative pressure regulating device according to the patient's specific physiological condition and treatment needs to ensure the accuracy and safety of the treatment.

[0099] Specifically, the negative pressure regulating device in the massage therapy device is one of its key components, which is mainly used to realize the dynamic negative pressure regulating function according to the personalized treatment parameters. The negative pressure regulating device is used in conjunction with other components of the therapy device (such as the vital sign parameter collection component and the parameter calculation component) to complete the initial setting of the device and adjust the negative pressure adsorption force in real time by collecting and analyzing the user's vital sign parameters. At the same time, the negative pressure regulating device can not only provide precise negative pressure adsorption, but also respond dynamically according to the feedback data of the target area to ensure the accuracy and safety of the treatment process.

[0100] Specifically, the set initial parameters are usually based on the initial biological signals of the target area collected in the early stage (such as blood flow status, electromyographic signals, skin conductivity, etc.), combined with the personalized treatment plan obtained through analysis; for example: the marking results of the low perfusion area can be used to adjust the initial negative pressure adsorption force, the muscle tension status can be used to set the electric pulse intensity value and frequency, and the skin temperature and deep tissue condition are used to set the heat energy transfer intensity and sound wave frequency; the purpose of the initial setting is to provide a basis for subsequent dynamic adjustment, while avoiding the adverse effects of excessive or weak negative pressure adjustment equipment parameters on the target area.

[0101] Obtain the blood flow state gradient value of the target area through flexible sensors and muscle tension gradient ;

[0102] It should be noted that the flexible sensor is closely attached to the skin of the target area to ensure that the sensor is in full contact with the skin surface so as to obtain high-quality biological signal data in real time; for the acquisition of the blood flow state gradient value, the laser Doppler imaging (LDI) module and blood oxygen sensor integrated in the flexible sensor start working, and the LDI module irradiates the skin surface of the target area with a laser beam, receives the scattered signal caused by the red blood cells moving under the skin, and uses the Doppler effect to calculate the blood flow velocity and the rate of change of blood flow at different times; by comparing the change rate at the spatial position of the target area, the blood flow change rate at different positions is determined, and the blood flow state gradient value of the area is further calculated. , which indicates the degree of change in blood flow velocity in space. To obtain the muscle tension gradient value, the electromyographic sensor (EMG sensor) in the flexible sensor collects the electromyographic signal of the target area, removes high-frequency noise and low-frequency interference through a bandpass filter (frequency range 20Hz to 500Hz), and obtains a pure electromyographic signal; then, extracts the characteristic parameters of the electromyographic signal (such as RMS value and frequency component), evaluates the change in muscle tension level through the change trend of the RMS value, and further calculates the tension distribution at different positions in the target area; compares this distribution with the tension distribution in the initial state, obtains the tension change at different times and positions, and generates the muscle tension gradient value of the target area. , which is the rate of change of muscle tension in spatial position. Finally, these gradient values ​​are fed back to the control system in real time through the data processing module, providing a basis for the dynamic adjustment of negative pressure adsorption force, parameter setting of electric pulses, and refined control of heat energy transfer and sound wave regulation.

[0103] After the initial setting, the negative pressure regulating device is fitted to the target area, and the negative pressure adsorption force is adjusted based on the marked low perfusion area in real time. The expression is:

[0104] ;

[0105] in, Indicates time The negative pressure adsorption force, Indicates the initial negative pressure adsorption force, represents the blood flow gradient coefficient, Indicates the gradient value of blood flow state, represents the integral coefficient of muscle tension, Indicates the muscle tension gradient value in the target area. Indicates the initial muscle tension gradient value of the target area. represents the time element;

[0106] Specifically, obtain the blood flow gradient coefficient The specific steps are as follows: Through the laser Doppler imaging function in the flexible sensor, a laser beam is emitted to the target area, and the scattered signal generated by the movement of subcutaneous red blood cells is received. The received signal is processed using the Doppler effect to extract the change information of blood flow velocity. To ensure the stability and reliability of the data, the collected signal is filtered to remove noise, and normalization is performed to unify the data scale to facilitate subsequent calculations. Then, the processed blood flow data is used to calculate the blood flow velocity gradient value in the target area by spatial differentiation. This step clarifies the spatial distribution characteristics of blood flow velocity by comparing the changes in blood flow velocity at different times and different positions, and forms a preliminary distribution map of blood flow gradient. Subsequently, the blood flow gradient distribution map is compared with the low perfusion area in the target area to further identify the blood flow gradient characteristics of the key area. On the basis of clarifying the blood flow gradient characteristics, a comprehensive analysis is performed in combination with other relevant data of the target area. For example, the tension changes of muscles are analyzed by electromyographic signals to confirm the characteristic areas related to blood flow gradients, and the correlation between blood flow and muscle tension is modeled. In this way, irrelevant or abnormal data points can be eliminated to ensure that the extracted blood flow gradient values ​​have high accuracy and relevance. Then, based on the optimized blood flow gradient information, data fitting methods such as multivariate regression analysis or fuzzy logic reasoning are used to calculate the blood flow gradient coefficient suitable for the specific state of the target area. .

[0107] It should be noted that the muscle tension integral coefficient It is a coefficient used to measure the degree of influence of changes in muscle tension in the target area on the control system. The coefficient itself is not obtained through direct measurement, but is a parameter pre-set according to the control requirements and the feedback characteristics of muscle tension changes. During the control process of the massage therapy instrument, the muscle tension data of the target area will be collected in real time through the flexible sensor, and compared with the initial tension state to calculate the gradient of muscle tension. . Muscle tension integral coefficient It is usually used in control formulas as a weight factor to participate in the dynamic adjustment of negative pressure adsorption force to ensure that when muscle tension changes greatly, the negative pressure adsorption force can be increased in time, thereby enhancing the treatment effect. In other words, the role of the muscle tension integral coefficient is similar to the gain coefficient of an amplifier, and its size will directly affect the adjustment amplitude of the negative pressure adsorption force by the change of muscle tension.

[0108] The dynamic adjustment method of adjusting the negative pressure adsorption force through real-time feedback is superior to the traditional fixed or manual adjustment method. It can dynamically optimize the adsorption force according to the blood flow state gradient and muscle tension gradient monitored in real time by the flexible sensor, ensuring that the treatment intensity is always in the optimal range; at the same time, it can accurately adapt to the patient's personalized needs, reduce the adsorption force when the blood flow increases to avoid tissue damage, and increase the adsorption force when the muscle tension increases to enhance the treatment effect, with higher real-time, safety and comfort.

[0109] The blood flow state gradient value and muscle tension gradient value of the target area are obtained through flexible sensors, and fed back into the negative pressure adsorption force adjustment formula to adjust the negative pressure adsorption force in real time to ensure dynamic optimization of blood supply and oxygen supply to tissues;

[0110] Among them, flexible sensors include flexible blood flow sensors, flexible muscle sensors and integrated sensor arrays, as follows: Flexible blood flow sensors: sensors used to detect blood flow, usually working in combination with photoelectric, ultrasonic or resistance principles; Flexible muscle sensors: sensors used to detect muscle tension or electromyographic signals, such as those based on conductive polymers or thin film sensors; Integrated sensor arrays: flexible arrays that can simultaneously detect multiple physiological parameters, such as patch sensors for health monitoring.

[0111] If blood flow increases , then gradually reduce the negative pressure adsorption force to avoid excessive adsorption;

[0112] It should be noted that a significant increase in blood flow means that the blood perfusion status of the target area is improved, so the negative pressure adsorption force is gradually reduced to avoid tissue damage or excessive adsorption.

[0113] If muscle tension changes increase Then the negative pressure adsorption capacity is improved and the treatment effect is enhanced;

[0114] It should be noted that when the degree of muscle fatigue decreases, appropriately reducing the electric pulse intensity can avoid over-stimulation and ensure the comfort and safety of treatment.

[0115] Based on the initial EMG signal of the target area , calculation time The gradient value of the electromyographic signal at time

[0116] Combined with the initial electromyographic signal and the electromyographic signal gradient value, normalizing the electromyographic signal gradient value to obtain a real-time normalized electromyographic signal gradient value;

[0117] According to the electromyographic signals collected in the target area, the electric pulse intensity value and the electric pulse frequency value are adaptively controlled in real time. The expression is:

[0118] ;

[0119] ;

[0120] in, Indicates time The electric pulse intensity value at Indicates the initial electric pulse intensity value, Indicates time The real-time normalized EMG signal gradient value, represents the initial electromyographic signal, represents the electric field adjustment coefficient, represents the frequency fluctuation coefficient, Indicates time The electric pulse frequency value at represents the initial electrical pulse frequency, represents the frequency fluctuation factor, Indicates that over time Varying sine waves;

[0121] It should be noted that by collecting the electromyographic signals of the target area in real time, a bandpass filter is used to remove high-frequency noise and low-frequency interference, and key characteristic parameters such as the root mean square value, frequency median and spectrum energy distribution of the signal are extracted. These parameters are used to calculate the electromyographic gradient value to reflect the dynamic change trend of the muscle state in the target area. Combined with the real-time collected skin conductivity data, a multidimensional data analysis method is used to comprehensively evaluate the changes in electrical activity and conductivity in the target area. The changes in skin conductivity reflect the dynamic state of ion concentration and hydration in the area. These characteristics directly affect the propagation path and action intensity of the electric field. Through the comprehensive analysis of the above data, a real-time electrical activity distribution map and a conductivity change trend map of the target area are generated. Subsequently, the electromyographic signal change rate in the electrical activity distribution map is used in combination with the conductivity change trend to calculate the sensitivity of the electric field to the target area through a nonlinear optimization algorithm. Specifically, by gradually adjusting the electric field parameters (such as electric pulse intensity and frequency), the response data to the changes in electromyographic gradient and conductivity are collected, and the mapping relationship between the electric field parameters and the response of the target area is established. Based on these data, the sensitivity index is solved by curve fitting or machine learning methods. To ensure the consistency and comparability of sensitivity indicators among different target areas, these indicators were normalized.

[0122] Among them, the electric field adjustment coefficient The value of should take into account the following requirements: the uniformity of the electric field distribution in the target area should be ensured, while avoiding tissue damage caused by local over-concentration; the size of the coefficient needs to be compatible with the amplitude of the change in conductivity of the target area. Usually, in experiments, the electric field adjustment coefficient is limited to 75%-90% of the highest sensitivity range based on the optimal response range of the target area. This range of values ​​can ensure the effective intensity of the electric field while avoiding excessive stimulation, thereby achieving high efficiency and safety of the electric field effect.

[0123] It should also be noted that obtaining the frequency fluctuation coefficient The specific steps are as follows: by collecting the EMG signals and neural activity data of the target area in real time, using a bandpass filter to remove high-frequency noise and low-frequency interference, extracting key characteristic parameters such as the frequency component and change rate of the EMG signals to accurately reflect the muscle activity state and neural excitation level of the target area. Based on the dynamic change trend of the frequency component, further analyze the response characteristics of the target area muscles to different stimulation frequencies, especially the dynamic characteristics of neuromuscular adaptability with frequency changes. Subsequently, by gradually adjusting the stimulation frequency, observe the effects of different frequencies on the fluctuation amplitude and stability of the frequency component of the EMG signal, and establish the association between the frequency fluctuation amplitude and the neural response of the target area. Combined with the analysis results, the neural response characteristics under different frequency fluctuation conditions are normalized, and the optimal fluctuation amplitude range is determined based on the response sensitivity of the target area.

[0124] Among them, in determining the frequency fluctuation coefficient When adjusting the range, it is necessary to ensure that the frequency fluctuation can effectively avoid neuromuscular adaptability, while ensuring that the stimulation intensity and frequency changes do not exceed the tolerance of the nerves and tissues in the target area. Usually, the setting of the fluctuation range is based on the muscle fatigue state and nerve activity stability in the target area. The fluctuation amplitude of the frequency change is recommended to be controlled between 5% and 15% of the original frequency to maintain the dynamic regulation effect and avoid overstimulation. Finally, the fluctuation range is matched with the electrical pulse parameters through the optimization algorithm, the adjustment amount required for the frequency fluctuation is dynamically calculated, and the frequency fluctuation coefficient is generated to ensure that the stimulation achieves the best balance between safety, stability and effect.

[0125] Furthermore, we can obtain the frequency fluctuation factor The specific steps are as follows: by collecting the electromyographic signals and neural activity data of the target area in real time, using a bandpass filter to remove noise and interference in the signal, extracting key parameters reflecting the neuromuscular state, including frequency components and dynamic change trends. Based on these data, analyze the response characteristics of the neuromuscular system to different stimulation frequencies, especially the changes in adaptability and stability, and determine the physical limits of the frequency fluctuation range in combination with biological characteristics. Subsequently, adjust the stimulation frequency experimentally, gradually observe its impact on the fluctuation amplitude and stability of the frequency components of the electromyographic signals, and extract the optimal frequency fluctuation range of the target area. Use normalization to map this range to the standardized parameter space, and combine the response sensitivity of the target area to the stimulation frequency, and use an optimization algorithm to calculate the frequency fluctuation factor suitable for the target tissue.

[0126] Among them, the frequency fluctuation factor The value of needs to ensure that neuromuscular adaptation is effectively avoided while maintaining the safety and stability of stimulation. It is usually set within a range that does not cause excessive tissue load while ensuring sufficient dynamic response, thereby achieving personalized and dynamically optimized frequency regulation.

[0127] According to the real-time normalized electromyographic signal gradient value, the time The electric pulse intensity value at Expression, adjust the electric pulse intensity value, and enhance neuromuscular stimulation in the target area;

[0128] Use over time Changing sine wave Adjust time The electrical pulse frequency value , avoiding neural adaptation through periodic fluctuations;

[0129] The degree of muscle fatigue is assessed by monitoring the real-time normalized electromyographic signal gradient value of the target area. If the degree of muscle fatigue is gradually reduced , then gradually reduce the electric pulse intensity to ensure the safety of treatment;

[0130] It should be noted that as muscle fatigue gradually decreases , which means that the muscles in the target area have gradually recovered their vitality, and the neuromuscular response threshold may increase. If the electrical pulse intensity is still maintained at a high level at this time, it may cause muscle overstimulation or discomfort, and even reduce the treatment effect. Therefore, by gradually reducing the electrical pulse intensity, it can better adapt to the muscle recovery state, avoid the risk of excessive stimulation, and ensure the comfort and safety of the treatment. This adjustment is based on the analysis of real-time fatigue gradient signals and is completed dynamically in combination with personalized treatment parameters to ensure that the treatment parameters are highly consistent with the user's current physiological state.

[0131] For example, in a physical therapy session, the initial muscle fatigue level is high, and the real-time normalized EMG signal gradient value The gradient value is 0.8 (assuming the range is 0 to 1), and the corresponding initial electric pulse intensity is 50mA. When the treatment reaches a certain stage, the real-time normalized myoelectric signal gradient value is monitored. Gradually decreases to 0.2, at which point the control system automatically reduces the electric pulse intensity to 30mA to reduce stimulation and protect the target tissue. If the fatigue gradient further decreases to close to 0 (such as below 0.05), the electric pulse intensity will be adjusted to a lower safety range (such as 20mA) to ensure adaptability and safety during treatment and avoid excessive intervention.

[0132] The temperature distribution of the target area is monitored in real time by flexible sensors to ensure the intensity of heat energy transfer is within range, and dynamically adjust the heat energy transfer intensity according to temperature changes;

[0133] The specific control logic is as follows: if the temperature gradient is too low, the intensity of heat energy transfer will be gradually increased to promote metabolism; if the temperature gradient is too high, the heat energy output will be automatically reduced to avoid tissue damage.

[0134] During the action of high-frequency sound waves at the sound wave frequency, the echo signal of the deep tissue is collected in real time by using the ultrasonic echo signal receiving device;

[0135] The sound wave frequency is adjusted in real time according to the change of echo signal intensity of deep tissue to optimize the sound wave penetration depth and echo signal quality to ensure that deep tissue is effectively stimulated;

[0136] Specifically, the ultrasonic sensor receives the ultrasonic signal reflected from the deep tissue, and the collected ultrasonic signal is subjected to frequency band filtering processing through a bandpass filter to remove possible environmental noise and background interference, thereby ensuring that the acquired signal has a high signal-to-noise ratio and clarity; the filtered ultrasonic signal is transmitted to the digital signal processing unit, which performs fast Fourier transform analysis on the signal to extract the amplitude, frequency offset and delay characteristics of the ultrasonic echo signal of the deep tissue, and the analysis result is used to calculate the echo signal strength of the deep tissue in real time, and the echo signal strength data is transmitted to the sound wave frequency adjustment unit through an interface, and the sound wave frequency adjustment unit adjusts the frequency and power of the sound wave according to the change in the echo signal strength, thereby ensuring that the sound wave output parameters are dynamically matched with the acoustic characteristics of the deep tissue, thereby optimizing the treatment effect on the deep tissue.

[0137] The specific control logic is as follows: if the echo signal is enhanced (deep tissue activity is increased), the sound wave frequency is gradually reduced; if the echo signal is weakened (deep tissue metabolism is slow), the sound wave frequency is appropriately increased.

[0138] S3. Apply medium-frequency electric pulses to the target area based on negative pressure adsorption, and dynamically adjust the electric pulse parameters according to the adsorption state.

[0139] Furthermore, under the action of negative pressure adsorption, the conductivity distribution data of the skin in the target area is collected through a flexible sensor;

[0140] Based on the conductivity distribution data, combined with the muscle state parameters and blood flow state parameters of the target area, the changes in tissue conductivity are dynamically evaluated and real-time conductivity distribution data is output;

[0141] It should be noted that in order to more accurately evaluate changes in tissue conductivity, it is necessary to combine muscle state parameters (such as electromyographic signals and muscle tension) with blood flow state parameters (such as blood flow, blood flow velocity, and blood flow changes) in the target area.

[0142] Specifically, muscle state parameters reflect the degree of muscle contraction and fatigue state by real-time monitoring of muscle electrical activity and tension changes; blood flow state parameters reveal the blood flow in the target area, especially the blood flow recovery under negative pressure adsorption. Changes in electromyographic signals, muscle tension, blood flow, blood flow velocity, and conductivity distribution data directly affect the conductivity of tissues, because muscle contraction or relaxation, and improved or reduced blood flow will lead to fluctuations in water content and ion concentration in tissues, thereby changing conductivity.

[0143] Preferably, by dynamically analyzing these data (i.e., conductivity distribution data, electromyographic signals, muscle tension, blood flow, and blood flow velocity data), the trend of tissue conductivity changes can be evaluated in real time, and the treatment strategy can be adjusted according to the degree of muscle tension and blood flow improvement. Real-time conductivity distribution data provides accurate feedback for subsequent electric field focusing and electric pulse adjustment, ensuring that the effects of electric fields and electric pulses can be accurately adjusted during treatment, thereby optimizing the treatment effect.

[0144] According to the real-time conductivity distribution data, the electrode array number and arrangement parameters of the target area are selected, and the electrode group with output current and phase adjustment is formed into an electrode array;

[0145] Specifically, a flexible sensor is used to collect real-time conductivity distribution data of the target area, extract conductivity gradient values ​​and coordinates of high conductivity areas, and calculate the electrode array number and spatial layout parameters that are suitable for the target area by performing cluster analysis on the distribution of high conductivity areas. Based on the calculation results, an electrode array that matches the characteristics of the target area is retrieved from a preset electrode array library, and adjacent electrode groups are selected to form an electrode group for output current and phase adjustment. The number and relative position relationship of the selected electrode group are dynamically updated in combination with changes in the conductivity gradient to generate an electrode array corresponding to the target area.

[0146] Using the real-time conductivity distribution data after dynamic evaluation, the output current and phase relationship of the electrode array are dynamically adjusted to form a three-dimensional electric field focus, ensuring that the electric field is concentrated in the area with significant conductivity changes;

[0147] By integrating the dynamic feedback mechanism, the three-dimensional electric field focusing is adaptively adjusted according to the real-time conductivity of the target area, and the expression is:

[0148] ;

[0149] in, Indicates time The electric field strength at represents the initial electric field strength, Indicates time The conductivity gradient at represents the electric field phase that changes with time, μ represents the conductivity gradient adjustment coefficient, Represents the periodic changes of electromagnetic signals in the electric field;

[0150] Specifically, the steps for obtaining the conductivity gradient adjustment coefficient are as follows: collect the conductivity distribution data of the target area in real time through the flexible sensor to obtain the initial gradient value of the conductivity changing with position; compare the initial gradient value with the reference conductivity distribution calibrated in the target area, and calculate the time The conductivity gradient On this basis, the real-time monitoring of muscle tension and blood flow state parameters, combined with the sensitive areas of conductivity change, and the multidimensional data fitting method were used to generate the conductivity gradient change weight factor. , which is used to describe the contribution of the conductivity change in the target area to the electric field distribution.

[0151] Furthermore, the conductivity gradient change weight factor The periodic changes of electromagnetic signals in the electric field Through nonlinear function The conductivity gradient adjustment coefficient μ is calculated by coupling through the dynamic feedback mechanism, and the expression is: ;

[0152] Preferably, by integrating a dynamic feedback mechanism and adjusting the focus of the three-dimensional electric field according to the real-time conductivity of the target area, the accuracy and effectiveness of the treatment can be significantly improved. Specifically, by real-time monitoring of the conductivity changes in the target area, the conductivity gradient can be dynamically calculated, and the electric field strength can be adaptively adjusted in combination with the periodic changes in the electric field phase, thereby optimizing the distribution of the electric field in deep tissues. This adaptive adjustment not only ensures that the electric field is focused precisely on the area that needs treatment, but also adjusts the treatment intensity according to the changes in the physiological feedback of the tissue, avoiding problems such as over-stimulation or insufficient treatment. Ultimately, the synchronous adjustment of the electric field and the medium-frequency electric pulses can effectively improve the treatment efficiency and achieve personalized and more precise treatment effects.

[0153] Combine the real-time conductivity distribution data of the target area with the three-dimensional electric field feedback to adjust the intensity and frequency of the medium-frequency electric pulses;

[0154] Specifically, the tissue status of the target area is accurately evaluated by using the real-time feedback of conductivity distribution data and three-dimensional electric field information. The conductivity distribution data reflects the electrical characteristics of the target area, while the three-dimensional electric field affects the focusing effect of the electric field through the adjustment of the electrode array. Based on the feedback of these two, the parameters of the medium-frequency electric pulse are adjusted in real time to ensure that the current and frequency act accurately on the key parts of the tissue.

[0155] Among them, the three-dimensional electric field information specifically includes the following contents: Electric field intensity distribution: describes the spatial distribution of the electric field in the target area, and calculates the electric field strength at different positions through the real-time collected conductivity data and the output characteristics of the electrode array; Electric field direction distribution: reflects the directionality of the electric field vector, which is used to determine the direction of the force of the electric field on the tissue, so as to achieve precise focusing and action; Electric field phase relationship: involves the current phase adjustment between the electrode arrays, which is used to control the periodic changes of the electric field and the spatial interference effect, so as to achieve precise action at different depths and regions; Conductivity gradient: based on the real-time conductivity distribution data, the gradient change of the electric field in the target area is calculated to optimize the effect of electric field focusing.

[0156] The method for obtaining three-dimensional electric field information is as follows: the conductivity information of the skin surface is collected through a flexible sensor, and the conductivity distribution is dynamically evaluated by combining the muscle tension and blood flow gradient parameters of the target area; a three-dimensional electric field is generated by adjusting the current intensity and phase relationship using a programmable electrode array; based on the changes in the electrical characteristics of the target area (such as conductivity and impedance), the configuration of the electrode array is dynamically updated using feedback data; real-time conductivity data, muscle tension and blood flow gradient data are input into a finite element analysis (FEA) model to generate three-dimensional electric field information through calculation.

[0157] Furthermore, according to the change in conductivity, the resistance and capacitance characteristics of the target area are dynamically calculated, and the intensity of the electric pulse is adjusted accordingly. For example, when the conductivity of the tissue increases, it means that the regional blood flow and hydration are good, and the electric pulse intensity value will be appropriately reduced to avoid overstimulation. Conversely, when the conductivity decreases, it may be due to poor blood flow or poor tissue hydration, so the electric pulse intensity value will be increased to enhance the treatment effect. At the same time, the frequency of the medium-frequency electric pulse is adjusted according to the tissue feedback in the target area. Usually, the frequency is adjusted to achieve tissue stimulation at different depths. Low frequency can more effectively stimulate shallow tissue, while high frequency can act more deeply on deep muscle tissue. Through these dynamic adjustments, precise treatment of the target area can be achieved, improving efficacy and reducing side effects.

[0158] Preferably, by combining tissue conductivity and electric field feedback, the adjustment of electric pulses no longer relies on a single parameter, but rather optimizes the treatment process through real-time interaction between electric field and conductivity. This approach enhances the precision and personalization of treatment.

[0159] S4. Based on the feedback data of the target area after the medium-frequency electric pulse is applied, the controllable heat is transferred to the deep tissue through the thermal energy device in the negative pressure adsorption area.

[0160] Furthermore, feedback data is collected during the operation of the intensity and frequency of the adjusted intermediate frequency electrical pulses;

[0161] The heat transfer is calculated based on the feedback data and the muscle state parameters and blood flow state parameters of the target area;

[0162] Specifically, biological signal monitoring technology and thermal conduction modeling methods are used; the electromyographic signal (EMG), blood flow signal (such as photoplethysmography (PPG)) and temperature signal of the target area are collected in real time through flexible sensors, and the raw data are denoised and normalized using signal processing algorithms (such as wavelet transform or filter); based on these data, combined with muscle fatigue models (such as changes in the median frequency of the electromyographic spectrum) and hemodynamic models (such as changes in blood flow rate and blood oxygen saturation), thermodynamic conduction equations (such as Fourier heat conduction equations) are used to calculate the heat transfer requirements of local tissues; through a feedback regulation mechanism, the output power of the thermal energy device is dynamically adjusted to ensure that the amount of heat transferred is consistent with the biological state of the target area (muscle fatigue, blood flow conditions), thereby achieving personalized deep heat therapy.

[0163] According to the heat transfer value, the output power is adjusted by the thermal energy device in the negative pressure adsorption area;

[0164] It should be noted that the thermal energy device uses adjustable power output to ensure precise heat control to avoid overheating or underheating.

[0165] Adopting the principle of heat conduction, heat energy is transferred from the skin surface to the deep tissue through the heat conduction panel;

[0166] At the same time, during the heat transfer process, the heat transfer rate is controlled by fine-tuning the heat transfer coefficient, and the output power of the thermal energy device is automatically adjusted according to the temperature change of the target area;

[0167] It should be noted that during the heat transfer process, the temperature change of the target area is monitored in real time by the temperature sensor, and the heat transfer coefficient of the heat conduction panel is dynamically fine-tuned according to the preset target temperature range and temperature change rate; in specific implementation, when the temperature of the target area rises too fast or exceeds the preset range, the output power of the thermal energy device is appropriately reduced or the heat transfer coefficient is reduced to slow down the heat transfer speed; when the temperature rises slowly or does not reach the target range, the output power of the thermal energy device is increased or the heat transfer coefficient is increased to accelerate the heat transfer; by adjusting the coordination of thermal energy output and heat transfer coefficient in real time, the stability and controllability of heat transfer are ensured, thereby achieving precise temperature control and effective treatment of deep tissues.

[0168] S5. After the controllable heat transfer is completed, high-frequency sound waves are released in the negative pressure adsorption area to cause micro-vibration of the cell gaps.

[0169] Furthermore, the temperature of the target area is monitored in real time through a temperature sensor, and when the temperature of the deep tissue stabilizes within the preset treatment range, the high-frequency sound wave release is triggered;

[0170] Among them, the preset treatment range refers to the pre-set deep tissue temperature range to achieve the best treatment effect and ensure safety. Specifically, when the temperature of the target area is stable within this range, it is considered that the ideal treatment conditions have been reached, thereby triggering the release of high-frequency sound waves; usually, this temperature range needs to be determined based on clinical research and biomedical principles to ensure that while promoting blood circulation, relieving muscle fatigue and improving tissue permeability, tissue overheating or damage is avoided; for example, the common treatment temperature range may be between 38°C and 45°C, but the specific range should be determined in combination with the functional design, treatment goals and user tolerance of the massage therapy device.

[0171] The frequency of the high-frequency sound waves is initially set according to the tissue characteristics of the target area, and the monitoring signals are collected in real time through the micro-vibration sensor;

[0172] Among them, the "tissue characteristics" of the target area specifically refer to: muscle state: including muscle tension, fatigue level, distribution of tense areas and relaxed areas; blood flow state: including blood flow, blood flow velocity and blood oxygen saturation; electromyographic signal: electrophysiological signal of muscle activity, used to evaluate muscle activity and fatigue status; tissue density: the density and distribution of different tissues (such as muscle, fat, connective tissue) in the target area.

[0173] It should be noted that the frequency of the initially set high-frequency sound waves is usually determined based on the tissue characteristics of the target area. Specifically, the sound wave absorption characteristics and resonance frequency range of the tissue are evaluated by analyzing the biometric data such as the electromyographic signal, blood flow status, muscle status and tissue density of the target area; based on the sound wave absorption characteristics and resonance frequency range, an initial frequency value that can effectively propagate in the target tissue and induce a micro-vibration effect is selected; this frequency value is usually determined with the support of experimental data and biomechanical models to ensure that its penetration depth and vibration intensity in the tissue achieve the best balance for the therapeutic effect; subsequently, during the operation of the negative pressure regulation device, the micro-vibration sensor will collect feedback signals in real time and dynamically adjust the frequency and amplitude of the high-frequency sound waves to adapt to changes in tissue characteristics.

[0174] Matching the resonant frequency in the monitoring signal with the natural vibration frequency of the intercellular space to trigger the resonant state;

[0175] It should be noted that the natural vibration frequency of the intercellular gap can be obtained through experimental measurement, tissue model calculation and feedback adjustment, as follows: Experimental measurement: using a highly sensitive micro-vibration sensor or sound wave echo test equipment to directly measure the resonance frequency of the tissue in its natural state; Tissue model calculation: based on the tissue characteristics of the target area (such as elastic modulus, density and damping coefficient, etc.), the natural vibration frequency is calculated through mathematical or biophysical models; Feedback adjustment: through the gradual adjustment of high-frequency sound waves, the response signal of the tissue is monitored in real time, and the frequency that triggers resonance is determined.

[0176] It should also be noted that "matching the resonance frequency in the monitoring signal with the natural vibration frequency of the intercellular space" means adjusting the parameters (frequency and intensity) of the high-frequency sound wave to be consistent with the natural vibration frequency of the target tissue through the vibration signal (including the input sound wave frequency and the frequency of the tissue response) collected in real time by the monitoring device, thereby triggering the resonance effect of the target tissue. This resonance effect can enhance the penetration and micro-vibration effect of the sound wave on the tissue and optimize the treatment effect.

[0177] Collect response data of the resonance state of the target area through a micro-vibration sensor;

[0178] Analyze the changes in electromyographic signals, blood flow and muscle status in the target area, and dynamically adjust the power and frequency of the sound waves based on the response data of the micro-vibration sensor;

[0179] Specifically, the sensor first collects the electromyographic signals, blood flow status and muscle changes of the target area in real time to analyze the tension, blood circulation and fatigue status of the target area. At the same time, the micro-vibration sensor monitors the micro-vibration effect of the intercellular space and evaluates the actual effect of the sound wave through feedback data. Based on these feedback data, combined with the muscle tension, blood flow and micro-vibration response of the target area, the power and frequency of the sound wave are dynamically adjusted.

[0180] Furthermore, when the target area has muscle tension or poor blood flow, the power and frequency of the sound waves will be appropriately increased to promote blood circulation, relieve muscle tension and enhance the micro-vibration effect between cells; when the muscles are relaxed and blood flow improves, the power and frequency of the sound waves will be appropriately reduced to avoid over-stimulation and ensure the comfort and effect of the treatment. This process is adjusted in real time to ensure that the treatment is always carried out in the best condition.

[0181] The present embodiment also provides a control system suitable for a massage therapy apparatus, comprising: a physical sign acquisition module, a parameter generation module, an adjustment module, a heat energy transfer module and a high-frequency sound wave module; the physical sign acquisition module is used to collect the user's physical sign parameters in real time, analyze the muscles, meridians and pain status, and generate matching personalized treatment parameters; the parameter generation module is used to dynamically adjust the negative pressure adsorption force of the target area based on the personalized treatment parameters, and monitor the adsorption status in real time; the adjustment module is used to apply medium-frequency electric pulses to the target area on the basis of negative pressure adsorption, and dynamically adjust the electric pulse parameters based on the adsorption status; the heat energy transfer module is used to transfer controllable heat to deep tissues through a thermal energy device in the negative pressure adsorption area based on feedback data of the target area after the medium-frequency electric pulse acts; the high-frequency sound wave module is used to release high-frequency sound waves in the negative pressure adsorption area to perform cell gap micro-vibration after the controllable heat transfer is completed.

[0182] This embodiment also provides a computer device, which is applicable to the control method of a massage therapy device, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the control method of a massage therapy device proposed in the above embodiment.

[0183] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0184] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the control method applicable to the massage therapy instrument as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0185] In summary, the present invention generates personalized treatment plans and dynamically adjusts treatment parameters by collecting user vital sign parameters in real time; monitors indicators such as blood flow, muscle tension and skin conductivity, accurately identifies fatigue and blockage in the target area, and then adjusts the negative pressure adsorption force and the intensity and frequency of the medium-frequency electric pulses; based on feedback data, the heat energy transfer mechanism accurately acts on deep tissues, improves blood flow and promotes muscle relaxation; through high-frequency sound waves, micro-vibrations between cells in this process further promote tissue repair and microcirculation, significantly improving the user's comfort and treatment effect, and achieving more refined and personalized treatment.

[0186] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A control method suitable for a massage therapy instrument, characterized in that: include: Collect the user's physical parameters in real time, analyze the muscle, meridian and pain status, and generate matching personalized treatment parameters; Based on personalized treatment parameters, the negative pressure adsorption force of the target area is dynamically adjusted, and the adsorption status is monitored in real time. The specific steps are as follows: the negative pressure adjustment device of the massage therapy instrument is initially set according to the personalized treatment parameters; Obtain the blood flow state gradient value of the target area through flexible sensors and muscle tension gradient ; After the initial setting, the negative pressure regulating device is fitted to the target area, and the negative pressure adsorption force is adjusted based on the marked low perfusion area in real time. The expression is: ； in, Indicates time The negative pressure adsorption force, Indicates the initial negative pressure adsorption force, represents the blood flow gradient coefficient, Indicates the gradient value of blood flow state, represents the integral coefficient of muscle tension, Indicates the muscle tension gradient value in the target area. Indicates the initial muscle tension gradient value of the target area. represents the time element; The blood flow state gradient value and muscle tension gradient , fed back to the negative pressure adsorption force adjustment formula, and the negative pressure adsorption force is adjusted in real time; If the blood flow increases, the negative pressure adsorption force will be gradually reduced to avoid over-adsorption; If the change in muscle tension increases, the negative pressure adsorption force will be increased to enhance the treatment effect; Based on the initial EMG signal of the target area , calculation time The gradient value of the electromyographic signal at time Combined with the initial electromyographic signal and the electromyographic signal gradient value, normalizing the electromyographic signal gradient value to obtain a real-time normalized electromyographic signal gradient value; According to the electromyographic signals collected in the target area, the electric pulse intensity value and the electric pulse frequency value are adaptively controlled in real time. The expression is: ； ； in, Indicates time The electric pulse intensity value at Indicates the initial electric pulse intensity value, Indicates time The real-time normalized EMG signal gradient value, represents the initial electromyographic signal, represents the electric field adjustment coefficient, represents the frequency fluctuation coefficient, Indicates time The electric pulse frequency value at represents the initial electrical pulse frequency, represents the frequency fluctuation factor, Indicates that over time Varying sine waves; According to the real-time normalized electromyographic signal gradient value, the time The electric pulse intensity value at Expression to adjust the electric pulse intensity value; Use over time Changing sine wave Adjust time The electrical pulse frequency value ; The degree of muscle fatigue is assessed by monitoring the gradient value of the electromyographic signal in the target area. If the degree of muscle fatigue gradually decreases, the intensity value of the electric pulse is gradually reduced. Real-time monitoring of temperature distribution in the target area through flexible sensors; During the action of high-frequency sound waves at the sound wave frequency, the echo signal of the deep tissue is collected in real time by using the ultrasonic echo signal receiving device; The sound wave frequency is adjusted in real time according to the changes in the echo signal intensity of the deep tissue; Apply medium-frequency electric pulses to the target area based on negative pressure adsorption, and dynamically adjust the electric pulse parameters according to the adsorption state; Based on the feedback data of the target area after the medium-frequency electric pulse, the heat energy device in the negative pressure adsorption area transfers controllable heat to the deep tissue; After the controllable heat transfer is completed, high-frequency sound waves are released in the negative pressure adsorption area to cause micro-vibration of the cell gaps.

2. The control method for a massage therapy device as claimed in claim 1, characterized in that: The user's physical sign parameters include muscle state parameters, meridian state parameters, pain state parameters, skin state parameters and blood flow state parameters.

3. The control method for a massage therapy device as claimed in claim 2, characterized in that: The specific steps of generating matching personalized treatment parameters are as follows: Normalize and filter the collected vital sign parameters to extract the electromyographic signal and skin conductivity data of the target area; Calculate muscle tension and fatigue levels based on electromyographic signals and divide tension and fatigue states within a region; Based on the divided tension and fatigue states, combined with skin conductivity data, the sensitive areas of meridians are located and the degree of patency is analyzed; The meridian blockage area is demarcated according to the degree of patency; According to the calibrated meridian blockage area information, combined with the normalized and filtered blood flow state parameters, the regional blood supply and oxygen supply are analyzed, and the low perfusion area is marked; The marked low perfusion areas are used to generate personalized treatment parameters for negative pressure adsorption force, electric pulse intensity value and frequency, thermal energy transfer intensity and sound wave frequency.

4. The control method for a massage therapy apparatus as claimed in claim 3, characterized in that: The steps of applying medium frequency electric pulses to the target area based on negative pressure adsorption and dynamically adjusting the electric pulse parameters in combination with the adsorption state are as follows: Under the action of negative pressure adsorption, the conductivity distribution data of the skin in the target area is collected through the flexible sensor; Based on the conductivity distribution data, combined with the muscle state parameters and blood flow state parameters of the target area, the changes in tissue conductivity are dynamically evaluated and real-time conductivity distribution data is output; According to the real-time conductivity distribution data, the electrode array number and arrangement parameters of the target area are selected, and the electrode group with output current and phase adjustment is formed into an electrode array; Using the real-time conductivity distribution data after dynamic evaluation, the output current and phase relationship of the electrode array are dynamically adjusted to form a three-dimensional electric field focusing; By integrating the dynamic feedback mechanism, the three-dimensional electric field focusing is adaptively adjusted according to the real-time conductivity of the target area, and the expression is: ； in, Indicates time The electric field strength at represents the initial electric field strength, Indicates time The conductivity gradient at represents the time-varying electric field phase, represents the conductivity gradient adjustment coefficient, Represents the periodic changes of electromagnetic signals in the electric field; The intensity and frequency of the medium-frequency electric pulses are adjusted by combining the real-time conductivity distribution data of the target area with the three-dimensional electric field feedback.

5. The control method for a massage therapy apparatus as claimed in claim 4, characterized in that: Based on the feedback data of the target area after the medium frequency electric pulse is applied, the controllable heat is transferred to the deep tissue through the thermal energy device in the negative pressure adsorption area. The specific steps are as follows: Collecting feedback data during the operation of the adjusted intensity and frequency of the medium frequency electrical pulses; The heat transfer value is calculated based on the feedback data and the muscle state parameters and blood flow state parameters of the target area; According to the heat transfer value, the output power is adjusted by the thermal energy device in the negative pressure adsorption area; Adopting the principle of heat conduction, heat energy is transferred from the skin surface to the deep tissue through the heat conduction panel; At the same time, during the heat transfer process, the heat transfer coefficient is fine-tuned to control the speed of heat transfer, and the output power of the thermal energy device is automatically adjusted according to the temperature changes in the target area.

6. The control method for a massage therapy apparatus as claimed in claim 5, characterized in that: After the controllable heat transfer is completed, high-frequency sound waves are released in the negative pressure adsorption area to perform micro-vibration of the cell gaps. The specific steps are as follows: The temperature of the target area is monitored in real time through the temperature sensor. When the temperature of the deep tissue stabilizes within the preset treatment range, the high-frequency sound wave release is triggered. The frequency of the high-frequency sound waves is initially set according to the tissue characteristics of the target area, and the monitoring signals are collected in real time through the micro-vibration sensor; Matching the resonant frequency in the monitoring signal with the natural vibration frequency of the intercellular space to trigger the resonant state; Collect response data of the resonance state of the target area through a micro-vibration sensor; Analyze the changes in electromyographic signals, blood flow and muscle status in the target area, combine the response data of the micro-vibration sensor, and dynamically adjust the power and frequency of the sound waves.

7. A control system for a massage therapy device, based on the control method for a massage therapy device according to any one of claims 1 to 6, characterized in that: include: Vital sign collection module, parameter generation module, adjustment module, heat energy transfer module and high-frequency sound wave module; The physical sign collection module is used to collect the user's physical sign parameters in real time, analyze the muscle, meridian and pain status, and generate matching personalized treatment parameters; The parameter generation module is used to dynamically adjust the negative pressure adsorption force of the target area based on the personalized treatment parameters, and monitor the adsorption state in real time; The regulating module is used to apply medium-frequency electric pulses to the target area on the basis of negative pressure adsorption, and dynamically adjust the electric pulse parameters in combination with the adsorption state; The heat energy transfer module is used to transfer controllable heat to deep tissues through the heat energy device in the negative pressure adsorption area based on the feedback data of the target area after the medium frequency electric pulse is applied; The high-frequency sound wave module is used to release high-frequency sound waves in the negative pressure adsorption area to perform micro-vibration of cell gaps after the controllable heat transfer is completed.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the control method applicable to the massage therapy instrument as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the control method applicable to a massage therapy device as described in any one of claims 1 to 6 are implemented.

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