Intelligent physiotherapy control system and method based on multi-scene multi-element cooperation

Abstract

The invention discloses an intelligent physiotherapy control system and method based on multi-scene multi-element cooperation, and relates to the technical field of physiotherapy, and the method comprises the following steps: carrying out the short-time Fourier transform of a drive waveform of a magnetic therapy module and an excitation waveform of a phototherapy module, extracting a dominant frequency component, a harmonic frequency band and an energy density parameter in each work period, and constructing a magnetic-optical dual-channel spectrum feature vector set; and based on the frequency spectrum feature vector set, calculating a frequency relative ratio and an energy superposition ratio between the magnetic therapy main frequency point and the phototherapy main frequency point and higher harmonics of the magnetic therapy main frequency point and the phototherapy main frequency point to obtain a frequency spectrum coupling degree index. Quantitative evaluation of the magnetic therapy and phototherapy risk intensity is realized by constructing the combined resonance superposition degree, the waveform time sequence is dynamically adjusted based on the index, and energy output peak shifting control is realized by delaying the rising edge and the amplitude limiting conduction time, so that the instantaneous superposition density is effectively reduced, and the physiotherapy safety and the system adaptive capacity are improved.

Description

Technical Field

[0001] The present invention relates to the field of physical therapy technology, and in particular to an intelligent physical therapy control system and method based on multi-scene and multi-element collaboration. Background Art

[0002] Intelligent therapy control based on multi-scenario, multi-element collaboration refers to an intelligent technology system that integrates multiple therapy elements (such as light therapy, magnetic therapy, negative oxygen ions, and far-infrared) and implements dynamic collaborative control for different usage scenarios (such as full-body therapy, foot care, and sleep relaxation). This control mechanism not only identifies the user's current usage status and scenario requirements, but also intelligently matches the output parameters of different elements according to the therapy goals. For example, it adjusts the wavelength of light therapy to adapt to muscle relaxation, adjusts the frequency of magnetic therapy to promote neural regulation, controls the concentration of negative oxygen ions to improve the respiratory environment, and regulates the intensity of far-infrared radiation to enhance the deep warming effect. By optimizing the linkage of various therapy elements in the time, space, and effect domains, a high degree of adaptation between treatment intensity, stimulation rhythm, and physiological rhythm is achieved, thereby improving the personalized effect, safety, and overall treatment efficiency of therapy.

[0003] The existing technology has the following deficiencies: In the existing physiotherapy system based on multi-element collaborative control, there is a lack of an effective resonant intervention mechanism between the magnetic therapy frequency output and the phototherapy wave pattern, which easily leads to unpredictable frequency coupling phenomena at specific tissue levels. When the two resonate and superimpose within the tissue, it may cause abnormal local energy density accumulation, resulting in deep muscle or nerve tissue continuing to absorb energy without obvious skin surface temperature rise, forming the so-called "deep hot spot area". Because such deep thermal effects are not sensitive to the user's subjective perception and are difficult to detect through traditional temperature control methods, they can easily cause damage to tissue protein structure, abnormal nerve conduction function, and even irreversible burns. They are typical hidden injury problems and seriously threaten the user's physiological safety during long-term physiotherapy.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent physiotherapy control system and method based on multi-scene and multi-element collaboration to solve the problems in the above-mentioned background technology.

[0006] In order to achieve the above objectives, the present invention provides the following technical solution: an intelligent physiotherapy control method based on multi-scenario and multi-element collaboration, comprising the following steps: Perform short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module, extract the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and construct a set of magnetic-optical dual-channel spectrum feature vectors; Based on the set of spectrum feature vectors, the relative frequency ratio and energy superposition ratio between the main frequency point of magnetic therapy and the main frequency point of phototherapy and their higher harmonics are calculated to obtain the spectrum coupling index, which is used to reflect the synergy of the frequency distribution structure of magnetic therapy and phototherapy waveforms; Within a unit time window, the effective action period of the magnetic therapy output and the light therapy output in the same area of ​​physical space is determined, the time overlap ratio and the energy cross-integral value of the action period are calculated, and the energy cross-integral value is normalized to a time domain coupling index; The spectral coupling degree and time domain coupling index are integrated to calculate the joint resonance superposition degree through a weighted mapping function. The joint resonance superposition degree is a continuous value between 0 and 1, which is used to evaluate the resonance superposition risk intensity between magnetic therapy and light therapy in real time. When the degree of joint resonance superposition exceeds the preset safety threshold, the control system applies delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform, delaying the rising edge of the excitation pulse within each waveform cycle and limiting its continuous conduction time to adjust the output peak power duration, thereby suppressing the risk of instantaneous energy superposition.

[0007] Preferably, the step of performing short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module to construct a set of spectrum feature vectors specifically includes: The original output waveforms of the magnetic therapy module and the light therapy module are sampled separately and short-term segmented using a preset time sliding window to obtain multiple local waveform segments for capturing the time-frequency characteristics of non-stationary signals; Perform short-time Fourier transform on each local waveform segment to extract the main frequency component, the second-order and higher harmonic frequency bands, and the energy density value corresponding to each frequency band to form a single-channel spectrum feature description vector; The spectral feature description vectors obtained from the magnetic therapy module and the phototherapy module are paired according to timestamp synchronization and merged into a set of magnetic-optical dual-channel spectral feature vectors for subsequent spectral coupling analysis and resonance risk assessment.

[0008] Preferably, the step of calculating the spectrum coupling index specifically includes: The main frequency component and the second to fifth order harmonic components in each working cycle are extracted from the magneto-optical dual-channel spectrum feature vector set, a main frequency-harmonic frequency list is constructed, and the energy density value corresponding to each frequency component is normalized; For each pair of magnetic therapy frequency components and light therapy frequency components, the relative frequency ratio is calculated and it is determined whether the relative frequency ratio falls within the preset resonance window interval. For frequency pairs that fall within the resonance window interval, the energy density superposition ratio is further calculated to evaluate the energy interaction intensity of the frequency pair within the tissue action area; Based on the relative frequency ratios and energy density superposition ratios of all main frequency and harmonic frequency pairs, a weighted combination function was used to calculate the spectrum coupling index, which was used to quantitatively reflect the coupling trend and synergistic risk level of the frequency distribution structure of magnetic therapy and phototherapy waveforms.

[0009] Preferably, the step of calculating the time domain coupling index specifically includes: Within a unit time window, the spatial overlapping area of ​​the magnetic therapy output and the light therapy output in the target tissue area is determined by using the spatial positioning parameters preset in the sensor array or the control module, and the actual action time period of the two in the spatial overlapping area is extracted; Based on the actual time period of action, the time-energy function curves of magnetic therapy and light therapy were constructed respectively. The energy output of the two in the overlapping time period was multiplied point by point to obtain the energy cross-integral value, which reflects the degree of energy superposition of the two forms of physical therapy acting simultaneously in time. The obtained energy cross-integral value is normalized with the total energy output value of magnetic therapy and phototherapy in the corresponding time window to form a standardized time domain coupling index, which is used to quantitatively evaluate the superposition synergy and instantaneous energy interaction intensity of the two physiotherapy signals on the time axis.

[0010] Preferably, the step of calculating the joint resonance superposition degree specifically includes: The spectral coupling index calculated by the spectral coupling analysis step and the time domain coupling index obtained by the time domain interaction analysis step are obtained respectively, and the spectral coupling index and the time domain coupling index are normalized respectively so that their numerical range is limited to between 0 and 1 to ensure that they are comparable and integrated within the same numerical scale; Based on the multi-factor weight model set by the system, adjustable weight factors are assigned to the spectral coupling index and the time domain coupling index respectively. The weight factors can be dynamically configured according to the usage scenario, tissue type or risk sensitivity strategy to adapt to the risk assessment needs under different physical treatment goals; A nonlinear mapping function was used to fuse the normalized spectral coupling index and the time domain coupling index to construct a joint resonance superposition degree. The joint resonance superposition degree was a continuous value between 0 and 1, which was used to quantitatively reflect the risk of synergistic resonance caused by the simultaneous superposition of magnetic therapy and light therapy in the frequency and time domains, and served as the basis for judging the triggering of the subsequent dynamic control mechanism.

[0011] Preferably, when the combined resonance superposition degree exceeds a preset safety threshold, a delayed duty cycle limiting control is applied to the magnetic therapy waveform or the light therapy waveform, specifically: First, dynamic delay control is applied to the pulse signal in each cycle of the current excitation waveform (magnetic therapy or light therapy). Assuming that the waveform period is T, the rising edge time of the original excitation pulse is , the required delay is calculated based on the difference between the joint resonance superposition degree and the preset safety threshold, and the rising edge time point after the delay is calculated based on the delay. The calculation expression is: ,in: is the delay modulation coefficient, which is used to control the sensitivity of the delay amplitude. ; The joint resonance superposition degree is calculated in real time, indicating the current magneto-optical resonance risk level; is the preset safety threshold, indicating the maximum allowable resonance risk value; is the delay time, which controls the starting offset of the excitation signal; is the rising edge time point after delay.

[0012] Preferably, after adjusting the start time of the excitation signal, the continuous conduction time within a single cycle is continued to be limited to avoid excessive accumulation of peak power that may still occur after the delay. The limiting processing formula is as follows: ,in: is the on-time after limiting (effective pulse width); The maximum on-time allowed in the current cycle; is the limiting response factor, which is used to adjust the intensity of output energy reduction. ; Fractional terms It indicates the excess ratio of resonance risk, ensuring that as the risk value increases, the on-time shrinks nonlinearly.

[0013] An intelligent physiotherapy control system based on multi-scenario and multi-element collaboration, including a spectrum feature extraction module, a spectrum coupling analysis module, a time domain coupling analysis module, a risk assessment and fusion module, and a dynamic intervention control module; The spectrum feature extraction module performs short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module, extracts the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and constructs a set of magnetic-optical dual-channel spectrum feature vectors; The spectrum coupling analysis module calculates the relative frequency ratio and energy superposition ratio between the main frequency point of magnetic therapy and the main frequency point of light therapy and their higher harmonics based on the spectrum feature vector set to obtain the spectrum coupling index; The time-domain coupling analysis module determines the effective action time period of the magnetic therapy output and the light therapy output in the same area of ​​physical space, calculates the time overlap ratio and energy cross-integral value of the action time period, and normalizes the energy cross-integral value into the time-domain coupling index; The risk assessment and fusion module integrates the spectrum coupling degree and time domain coupling indicators, calculates the joint resonance superposition degree through a weighted mapping function, and evaluates the resonance superposition risk intensity between magnetic therapy and light therapy in real time; The dynamic intervention control module applies delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform when the combined resonance superposition degree exceeds the preset safety threshold, delaying the rising edge of the excitation pulse within each waveform cycle, limiting its continuous conduction time, and adjusting the output peak power duration.

[0014] In the above technical solution, the technical effects and advantages provided by the present invention are: This invention extracts the spectral structure and spatial action timing characteristics of magnetic therapy and phototherapy waveforms in real time, constructs a unified joint resonance superposition degree, and quantitatively describes the risk intensity of the two therapeutic signals during the synergistic interaction. Based on this, it dynamically drives a refined waveform control strategy. In particular, by delaying the rising edge of the excitation pulse and limiting the on-time, the multimodal energy output is staggered in the time domain, significantly reducing the energy superposition density per unit time, avoiding excessive energy concentration within the tissue, and ensuring physiological safety and intervention reliability during long-term physical therapy. This provides an efficient, safe, and adaptive collaborative control solution for multi-element intelligent physical therapy equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction to the drawings required for use in the embodiments will be given below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0016] Figure 1 This is a method flow chart of an intelligent physiotherapy control method based on multi-scene and multi-element collaboration of the present invention.

[0017] Figure 2 This is a module schematic diagram of an intelligent physiotherapy control system based on multi-scene and multi-element collaboration of the present invention. DETAILED DESCRIPTION

[0018] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art.

[0019] The present invention provides Figure 1 The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration shown includes the following steps: Perform short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module, extract the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and construct a set of magnetic-optical dual-channel spectrum feature vectors; The steps of performing short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module to construct a set of spectrum feature vectors specifically include: The original output waveforms of the magnetic therapy module and the phototherapy module are sampled separately and short-time segmented using a preset time sliding window to obtain multiple local waveform segments for capturing the time-frequency characteristics of non-stationary signals. A short-time Fourier transform is performed on each local waveform segment to extract the main frequency component, second-order and higher harmonic frequency bands, and the energy density values ​​corresponding to each frequency band to form a single-channel spectrum feature description vector. The spectrum feature description vectors obtained from the magnetic therapy module and the phototherapy module are paired according to timestamp synchronization and merged into a set of magnetic-optical dual-channel spectrum feature vectors for subsequent spectrum coupling analysis and resonance risk assessment.

[0020] This step aims to provide a highly accurate, structured mathematical description of the frequency behavior characteristics of two different physical interventions: magnetic therapy and phototherapy, thereby providing data support for subsequent spectrum coupling analysis and resonance risk assessment. During physical therapy, magnetic therapy and phototherapy typically act on human tissue in the form of periodic or quasi-periodic signals. However, their output waveforms often exhibit instability, multiple harmonic components, and uneven energy density. Without precise decomposition and extraction, it is difficult to determine whether their combined effect in the frequency domain constitutes a potential physical interference.

[0021] By performing short-time Fourier transforms (STFTs) on the magnetic therapy drive waveform and the light therapy excitation waveform, their dominant frequency components, harmonic distribution, and energy density changes can be captured simultaneously in both time and frequency dimensions. This method is particularly suitable for processing non-steady-state signals under dynamic control modes. This method not only identifies whether there is a frequency proximity, overlap, or resonant relationship between the two therapy signals, but also further evaluates the impact of local frequency bands at the tissue level by extracting energy density parameters.

[0022] Ultimately, the extracted results are structured into a set of magnetic-optical dual-channel spectral feature vectors, enabling standardized representation and comparison of the frequency-domain behavior of the two therapeutic modalities. This provides a solid data foundation for constructing spectral coupling models and joint resonance superposition. This process is the core prerequisite for risk identification and energy coordination within the entire intelligent therapy control system, providing critical signal analysis and decision-making support.

[0023] Based on the set of spectrum feature vectors, the relative frequency ratio and energy superposition ratio between the main frequency point of magnetic therapy and the main frequency point of phototherapy and their higher harmonics are calculated to obtain the spectrum coupling index, which is used to reflect the synergy of the frequency distribution structure of magnetic therapy and phototherapy waveforms; The steps for calculating the spectrum coupling index include: The main frequency component and the second to fifth order higher harmonic components in each working cycle are extracted from the set of magnetic-optical dual-channel spectrum feature vectors respectively, and a main frequency-harmonic frequency list is constructed, and the energy density value corresponding to each frequency component is normalized; for each pair of magnetic therapy frequency component and phototherapy frequency component, the relative frequency ratio is calculated, and it is determined whether the relative frequency ratio falls within the preset resonance window interval. For the frequency pairs falling within the resonance window interval, the energy density superposition ratio is further calculated to evaluate the energy interaction intensity of the frequency pair in the tissue action area; based on the relative frequency ratio and energy density superposition ratio of all main frequency and harmonic frequency pairs, a weighted combination function is used to calculate the spectrum coupling index, which is used to quantitatively reflect the coupling trend and synergistic risk level of magnetic therapy and phototherapy waveforms in the frequency distribution structure.

[0024] For each pair of magnetic therapy and phototherapy frequency components, the relative frequency ratio is calculated, mainly by dividing the phototherapy frequency component by the magnetic therapy frequency component to obtain the relative ratio value between the two, such as 1:1, 2:1, 3:2, etc.; then the ratio is matched with the preset resonance window interval, which is usually set to a set of typical resonance ratio intervals with high coupling potential (such as 1:1±δ, 2:1±δ, 3:2±δ, δ is the allowable error).

[0025] This step can be achieved by calculating a frequency ratio list and adding a threshold judgment function. The judgment result can be represented by a Boolean matrix or a weight value list. Its specific function is to identify whether there is a possibility of physical resonance between magnetic therapy and light therapy under a specific frequency combination. This is because specific integer multiples or near-integer multiples of frequency combinations often induce standing wave effects or local energy coupling in biological tissues, thus constituting a resonance risk point. By determining whether it falls within the resonance window range, coupling screening at the frequency level can be achieved, providing an accurate basis for subsequent risk quantification and control decisions.

[0026] By analyzing the structural relationship between the main frequencies and higher harmonics of magnetic therapy and phototherapy in the frequency domain, a quantifiable spectral synergy index was established to identify and evaluate the frequency coupling or resonance that may occur during their interaction. Magnetic therapy and phototherapy each possess distinct physical wave characteristics. While their main frequencies and harmonics can be independently controlled in time, if there is an approximate integer multiple or linear correlation in the frequency domain, frequency matching can easily occur within the tissue, triggering a local energy superposition effect. This coupling can lead to the risk of latent heat accumulation, particularly in areas with low thermal perception, such as deep muscles and nerves. Therefore, using a set of spectral feature vectors, each frequency component is first extracted, and the relative frequency ratio between magnetic therapy and phototherapy is calculated. This can be used to identify whether the treatment is within a preset resonance window. Furthermore, the actual energy coupling strength under this frequency relationship is quantified by the superposition ratio of energy densities, thereby comprehensively evaluating the degree of spectral coupling between the two. The final spectrum coupling index is not only structurally sensitive, but also truly reflects the energy interaction trend in the frequency domain. It is the key reference data used by the entire system for risk identification, intelligent regulation, and triggering of linkage protection mechanisms, and helps to improve the personalized accuracy and physiological safety of the physiotherapy system.

[0027] Within a unit time window, the effective action period of the magnetic therapy output and the light therapy output in the same area of ​​physical space is determined, the time overlap ratio and the energy cross-integral value of the action period are calculated, and the energy cross-integral value is normalized to a time domain coupling index; The steps for calculating the time domain coupling index include: Within a unit time window, the spatial overlapping area of ​​the magnetic therapy output and the phototherapy output in the target tissue area is determined through the spatial positioning parameters preset in the sensor array or the control module, and the actual action time period of the two in the spatial overlapping area is extracted; based on the extracted actual action time period, the time energy function curves of the magnetic therapy and the phototherapy are constructed respectively, and the energy output of the two in the overlapping time period is multiplied point by point to obtain the energy cross-integral value to reflect the degree of energy superposition of the two forms of physical therapy acting simultaneously in time; the obtained energy cross-integral value is normalized with the total energy output value of the magnetic therapy and the phototherapy in the corresponding time window to form a standardized time domain coupling index, which is used to quantitatively evaluate the superposition synergy and instantaneous energy interaction intensity of the two physical therapy signals on the time axis.

[0028] The purpose of this step is to quantify the actual degree of superposition of magnetic therapy output and phototherapy output in the time and space dimensions, providing a key basis for identifying potential instantaneous energy concentration risks. In multimodal physiotherapy systems, although magnetic therapy and phototherapy can independently control their output timing, in actual applications they often need to act on the same tissue area simultaneously or alternately to achieve a comprehensive treatment effect. However, when there is a high degree of temporal overlap between the two in the same area and the output intensity is high, it is very likely that instantaneous energy accumulation will form in a short period of time, inducing abnormal tissue reactions or accumulation of thermal effects, especially in deep tissues that the user is not aware of, which may form a "hidden overload."

[0029] Through this step, the spatial co-action area of ​​magnetic therapy and light therapy within the unit time window is first identified to ensure that only the overlapping parts are analyzed. Subsequently, by calculating the time overlap ratio in this area, the continuous proportion of the two forms of physical therapy acting together in the same time period can be evaluated. Furthermore, the energy cross-integral calculation is introduced, which not only considers the overlapping time, but also integrates the energy output intensity of the two physical therapy signals, and obtains the energy overlap through function multiplication and accumulation. Finally, the integral value is standardized to obtain the time domain coupling index, which can intuitively reflect the superposition intensity of the combined magnetic and light effects on the time axis.

[0030] In summary, this step is the core mechanism of the intelligent control system to determine whether there is "instantaneous concentration of energy peaks", which is of key significance for preventing safety hazards caused by the incoordination of multi-source physical therapy signals. It provides accurate time-domain risk parameter support for the construction of the joint resonance superposition degree and the triggering of the dynamic limiting control strategy.

[0031] The spectral coupling degree and time domain coupling index are integrated to calculate the joint resonance superposition degree through a weighted mapping function. The joint resonance superposition degree is a continuous value between 0 and 1, which is used to evaluate the resonance superposition risk intensity between magnetic therapy and light therapy in real time. The steps of calculating the joint resonance superposition degree specifically include: The spectral coupling index calculated by the spectral coupling analysis step and the time domain coupling index obtained by the time domain interaction analysis step are obtained respectively, and the spectral coupling index and the time domain coupling index are normalized respectively so that their numerical range is limited to between 0 and 1 to ensure that the two are comparable and integrated within the same numerical scale; according to the multi-factor weight model set by the system, adjustable weight factors are assigned to the spectral coupling index and the time domain coupling index respectively. The weight factors can be dynamically configured according to the usage scenario, tissue type or risk sensitivity strategy to adapt to the risk assessment requirements under different physical therapy goals; a nonlinear mapping function is used to fuse the normalized spectral coupling index and the time domain coupling index to construct a joint resonance superposition degree. The joint resonance superposition degree is a continuous value between 0 and 1, which is used to quantitatively reflect the degree of synergistic resonance risk caused by the simultaneous superposition of magnetic therapy and light therapy in the frequency domain and time domain, and serves as the judgment basis for triggering the subsequent dynamic control mechanism.

[0032] By integrating the synergistic information of physical therapy in the frequency domain and the time domain, a unified and quantifiable risk assessment indicator - the joint resonance superposition degree - is constructed to monitor in real time whether there is a risk of synergistic resonance between magnetic therapy and phototherapy, and to provide a reliable trigger basis for the subsequent dynamic power control strategy. In a multimodal physical therapy system, magnetic therapy and phototherapy each have independent frequency characteristics and energy output characteristics, which may show different degrees of coupling effects in different time periods, different parts or different courses of treatment. If the two show a strong superposition trend in both frequency distribution and time effect, synergistic resonance may be triggered, resulting in instantaneous high energy density accumulation in local tissues, and then forming safety hazards such as "deep hot spots".

[0033] To avoid misjudgment caused by considering only one dimension (such as frequency matching or time overlap), this step comprehensively introduces the two parameters of spectral coupling and time domain coupling obtained from the above calculations, and constructs a multi-factor synergistic index through weighted mapping. First, the two indicators are normalized separately to unify their numerical scales to ensure the scientific nature and stability of the subsequent fusion calculation. Then, based on the system preset or scenario-adaptive risk assessment strategy, different weights are assigned to the spectral coupling and time domain coupling indicators. For example, in high-frequency intervention scenarios, the proportion of spectral coupling can be appropriately increased, while in long-term continuous treatment, the consideration of the impact of time domain overlap is enhanced.

[0034] This fusion process typically uses a weighted combination of nonlinear mapping functions (such as exponential decay, hyperbolic, or logistic regression functions) to form a continuous joint resonance superposition degree between 0 and 1. The closer this joint resonance superposition degree is to 1, the stronger the synergistic superposition trend between the magnetic and optical interventions, and the higher the potential risk of resonance induction. Conversely, a joint resonance superposition degree close to 0 indicates that the current treatment parameters are relatively safe, and there is almost no risk of resonance coupling between magnetic therapy and light therapy in the current state.

[0035] By constructing this joint resonance superposition degree, not only can real-time quantitative assessment of collaborative resonance risk be achieved, but it can also be seamlessly integrated with the control module to drive the system to implement dynamic intervention measures such as duty cycle control, delayed triggering, or power limiting. This is a key technical link in ensuring a balance between user physiological safety and controllable physical therapy effects. Therefore, this step plays a core role in the entire intelligent physical therapy control system, bridging risk perception, decision-making, and control response.

[0036] When the degree of joint resonance superposition exceeds a preset safety threshold, the control system applies delayed duty cycle limiting control to the magnetic therapy waveform or light therapy waveform, delaying the rising edge of the excitation pulse within each waveform cycle and limiting its continuous conduction time to adjust the output peak power duration, thereby suppressing the risk of instantaneous energy superposition; When the combined resonance superposition degree exceeds the preset safety threshold, a delayed duty cycle limiting control is applied to the magnetic therapy waveform or the light therapy waveform, specifically: First, dynamic delay control is applied to the pulse signal in each cycle of the current excitation waveform (magnetic therapy or light therapy). Assuming that the waveform period is T, the rising edge time of the original excitation pulse is , the required delay is calculated based on the difference between the joint resonance superposition degree and the preset safety threshold, and the rising edge time point after the delay is calculated based on the delay. The calculation expression is: ,in: is the delay modulation coefficient, which is used to control the sensitivity of the delay amplitude. ; The joint resonance superposition degree is calculated in real time, indicating the current magneto-optical resonance risk level; is the preset safety threshold, indicating the maximum allowable resonance risk value; is the delay time, which controls the starting offset of the excitation signal; is the rising edge time point after delay; The purpose of this step is to actively break the synchronization relationship of the two physical intervention signals on the time axis by delaying the rising edge of the magnetic therapy or light therapy excitation waveform, especially to avoid the peak energy output of the two signals acting on the same regional tissue at the same time. When magnetic therapy and light therapy have potential resonance trends in frequency structure, their waveforms often exhibit a certain periodic coincidence trend. If the triggering is completely synchronized on the time axis, it may cause the local tissue to suffer from double high-intensity energy injection in a very short time, thereby inducing a sharp rise in instantaneous energy density and forming a "deep hot spot area". Since such energy superposition is usually not immediately reflected in the skin surface temperature rise, it is not easy for users to subjectively perceive or for traditional thermal control systems to discover in time, and it has obvious hidden harm characteristics.

[0037] By introducing the dynamic calculation of the delay time based on the difference between the joint resonance superposition degree and the safety threshold, this mechanism can flexibly delay the starting point of the rising edge of the excitation pulse according to the system's perception of real-time risk intensity, and realize adaptive decoupling of the magnetic-light coupling relationship in different treatment periods. The amplitude of the delay is a continuous adjustable quantity controlled by the risk overrun degree and the system sensitivity factor, which can finely adjust the time distribution form of energy input without breaking the treatment rhythm and overall frequency strategy, thereby maximizing the probability of interference between the two physical therapy signals in the time domain. This step is not only a passive protection strategy, but also a "feedforward" safety coordination mechanism with high engineering practicability and dynamic response value, and is one of the core control links for building a trusted intelligent physical therapy system.

[0038] After adjusting the starting time of the excitation signal, the duration of the single cycle is continued to be limited to avoid the peak power overaccumulation that may still occur after the delay. The limiting formula is as follows: wherein: is the on-time after limiting (effective pulse width); is the maximum on-time allowed in the current cycle; is the limiting response factor, used to adjust the intensity of energy reduction, ; the fractional term represents the overrun proportion of the resonance risk, ensuring that as the risk value rises, the on-time shrinks in a nonlinear manner; According to the current synergistic effect strength of magnetic therapy and phototherapy reflected by the joint resonance superposition degree, the conduction time window of the excitation signal is adaptively adjusted, especially the energy output segment within each waveform cycle is actively compressed and controlled. By compressing the output window, that is, shortening the continuous conduction time of the waveform, the peak energy released per unit time can be effectively reduced, thereby controlling the energy injection rate and achieving the purpose of reducing the tissue energy accumulation rate. This is particularly critical in multimodal physical therapy systems, because once the magnetic therapy and phototherapy signals are coupled in the time and frequency dimensions, their simultaneously superimposed output waveforms will form instantaneous high-density energy hotspots in certain deep tissue areas. These hotspots are often difficult to be detected by conventional temperature control systems because they are not accompanied by significant surface temperature rise.

[0039] Furthermore, the dynamic limit on the on-time is not a rigid setting. Instead, it combines the excess ratio between the combined resonance superposition degree and a preset safety threshold, using a nonlinear compression model to control the maximum effective pulse width, thus making the system more risk-adaptable and responsive. Under high-risk conditions, the output window is significantly compressed to quickly suppress possible instantaneous energy concentrations; while under lower-risk conditions, a relatively wide output time period is retained to ensure normal therapeutic efficacy. This continuously adjustable control strategy not only ensures precise regulation of tissue energy load but also avoids the weakening of therapeutic effects caused by one-size-fits-all control. It is the key control logic for achieving a "safety and effectiveness balance" in intelligent physical therapy systems. Furthermore, this mechanism offers the advantages of strong real-time performance, high programmability, and moderate hardware resource requirements, making it suitable for rapid integration into embedded microcontroller systems and possessing high engineering value and practicality.

[0040] The core purpose of this step is to establish a dynamic, responsive energy intervention control mechanism to mitigate the physiological risks associated with the potential for instantaneous energy superposition between magnetic and light therapy in both frequency and time dimensions, particularly the imperceptible "hidden heat accumulation" in deep tissue. In multimodal therapy systems, although magnetic and light therapy are two independent physical stimulation methods, they are often integrated into the same treatment device in practice, acting on the same body region. However, due to the potential for structural coupling in their control mechanisms or signal generation methods, synchronous excitation at the same or similar frequencies can easily occur on the time axis. If this synchronization is not restricted, pulses of the two waveforms can overlap within the same time window, leading to excessively high peak power output per unit time. This can particularly induce "deep hotspots," where energy density accumulates abnormally in deep muscle or neural tissue. Because these effects are not necessarily accompanied by a surface temperature rise, they are difficult for users to perceive through their skin. Furthermore, traditional temperature control mechanisms, which are mostly based on surface detection, are inherently hidden and unpredictable.

[0041] Through this step, when the system detects that the joint resonance superposition degree (used to evaluate the degree of risk of the synergistic resonance of magnetic therapy and light therapy) exceeds the preset safety threshold, two core intervention measures are immediately taken on the output waveform: delay of the rising edge and limitation of the conduction time. The former reduces the superposition probability of magnetic therapy and light therapy in the time dimension by dynamically calculating the delay time and shifting the starting time of the excitation pulse backward, avoiding the synchronous impact of energy; the latter further limits and compresses the pulse duration within a waveform period, effectively reducing the total energy injection amount in the overlapping area even if the two excitation signals still partially overlap. The two control strategies work together to break the formation conditions of synchronous resonance and suppress the possible energy concentration peak, thereby realizing fine and real-time control of safety risks on the basis of ensuring efficacy.

[0042] In addition, the control mechanism is realized based on the difference between the joint resonance superposition degree and the safety threshold, has self-adaptability and continuous adjustment capability, and can dynamically adjust the delay amount and the conduction time compression ratio according to the actual risk degree, which is not the traditional fixed threshold power limiting strategy. It has high intelligence and fast response speed, is suitable for integrated control of embedded systems or medical special chip platforms, has strong engineering feasibility and clinical application value in multi-scene intelligent physiotherapy systems, and is a key component module for realizing the "safety-efficacy balance" control strategy.

[0043] Through the above-mentioned intelligent physiotherapy control method based on multi-scene multi-element cooperation, the potential resonance superposition risk of magnetic therapy and light therapy in the frequency domain and the time domain is comprehensively perceived and dynamically intervened, effectively solving the problem of "deep hot spot area" hidden thermal injury caused by the lack of resonance control mechanism in the prior art. The scheme not only can extract and analyze the frequency spectrum structure and spatial action timing of the two physiotherapy waveforms in real time, but also can construct a unified joint resonance superposition degree to quantitatively represent the cooperation risk intensity, thereby triggering a fine waveform regulation mechanism. Especially by delaying the rising edge of the excitation pulse and limiting the conduction time, the energy is distributed in time staggered, the instantaneous superposition power per unit time is significantly reduced, and the energy accumulation trend in the deep tissue is effectively suppressed, thereby ensuring the physiological safety in the long-term physiotherapy process. Therefore, the method has good safety, self-adaptability and engineering realizability, and provides an intelligent, efficient and expandable energy coordination control technology path for multi-modal physiotherapy equipment.

[0044] The present application provides an intelligent physiotherapy control system based on multi-scene multi-element cooperation as shown in Figure 2 The present application provides an intelligent physiotherapy control system based on multi-scene multi-element cooperation as shown in The spectrum feature extraction module performs short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module, extracts the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and constructs a set of magnetic-optical dual-channel spectrum feature vectors; The spectrum coupling analysis module calculates the relative frequency ratio and energy superposition ratio between the main frequency point of magnetic therapy and the main frequency point of light therapy and their higher harmonics based on the spectrum feature vector set to obtain the spectrum coupling index; The time-domain coupling analysis module determines the effective action time period of the magnetic therapy output and the light therapy output in the same area of ​​physical space, calculates the time overlap ratio and energy cross-integral value of the action time period, and normalizes the energy cross-integral value into the time-domain coupling index; The risk assessment and fusion module integrates the spectrum coupling degree and time domain coupling indicators, calculates the joint resonance superposition degree through a weighted mapping function, and evaluates the resonance superposition risk intensity between magnetic therapy and light therapy in real time; The dynamic intervention control module applies delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform when the combined resonance superposition degree exceeds the preset safety threshold, delaying the rising edge of the excitation pulse within each waveform cycle, limiting its continuous conduction time, and adjusting the output peak power duration.

[0045] An embodiment of the present invention provides an intelligent physiotherapy control method based on multi-scene and multi-element collaboration, which is realized by the above-mentioned intelligent physiotherapy control system based on multi-scene and multi-element collaboration. The specific method and process of an intelligent physiotherapy control system based on multi-scene and multi-element collaboration are detailed in the embodiment of the above-mentioned intelligent physiotherapy control method based on multi-scene and multi-element collaboration, and will not be repeated here.

[0046] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0047] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

[0048] The above are only specific embodiments of the present application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. An intelligent physiotherapy control method based on multi-scenario and multi-element collaboration, characterized in that: The following steps are involved: Perform short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module, extract the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and construct a set of magnetic-optical dual-channel spectrum feature vectors; Based on the spectrum feature vector set, the relative frequency ratio and energy superposition ratio between the main frequency point of magnetic therapy and the main frequency point of light therapy and their higher harmonics are calculated to obtain the spectrum coupling index; Determine the effective action time period of magnetic therapy output and light therapy output in the same area of ​​physical space, calculate the time overlap ratio and energy cross-integral value of the action time period, and standardize the energy cross-integral value into a time domain coupling index; By integrating the spectral coupling degree and the time domain coupling index, the joint resonance superposition degree is calculated through a weighted mapping function, and the resonance superposition risk intensity between magnetic therapy and light therapy is evaluated in real time. When the degree of combined resonance superposition exceeds the preset safety threshold, a delayed duty cycle limiting control is applied to the magnetic therapy waveform or the phototherapy waveform, delaying the rising edge of the excitation pulse within each waveform cycle, limiting its continuous conduction time, and adjusting the output peak power duration.

2. The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to claim 1 is characterized in that: The steps of performing short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module to construct a set of spectrum feature vectors specifically include: The original output waveforms of the magnetic therapy module and the light therapy module are sampled respectively, and short-term segmented processing is performed using a preset time sliding window to obtain multiple local waveform segments; Perform short-time Fourier transform on each local waveform segment to extract the main frequency component, the second-order and higher harmonic frequency bands, and the energy density value corresponding to each frequency band to form a single-channel spectrum feature description vector; The spectrum feature description vectors obtained by the magnetic therapy module and the light therapy module are paired according to the timestamp synchronization method and merged into a magnetic-optical dual-channel spectrum feature vector set.

3. The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to claim 1 is characterized in that: The steps for calculating the spectrum coupling index include: The main frequency component and the second to fifth order harmonic components in each working cycle are extracted from the magneto-optical dual-channel spectrum feature vector set, a main frequency-harmonic frequency list is constructed, and the energy density value corresponding to each frequency component is normalized; For each pair of magnetic therapy frequency components and light therapy frequency components, the relative frequency ratio is calculated, and it is determined whether the relative frequency ratio falls within the preset resonance window interval. For the frequency pairs that fall within the resonance window interval, the energy density superposition ratio is calculated; The spectrum coupling index is calculated using a weighted combination function based on the relative frequency ratios and energy density superposition ratios of all main frequency and harmonic frequency pairs.

4. The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to claim 1 is characterized in that: The steps for calculating the time domain coupling index include: Within a unit time window, the spatial overlapping area of ​​the magnetic therapy output and the light therapy output in the target tissue area is determined by using the spatial positioning parameters preset in the sensor array or the control module, and the actual action time period of the two in the spatial overlapping area is extracted; Based on the actual action time period extracted, the time-energy function curves of magnetic therapy and light therapy were constructed respectively, and the energy output of the two in the overlapping time period was calculated point by point to obtain the energy cross-integral value; The obtained energy cross-integral value is normalized with the total energy output value of magnetic therapy and phototherapy in the corresponding time window to form a standardized time domain coupling index.

5. The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to claim 1 is characterized in that: The steps of calculating the joint resonance superposition degree specifically include: Respectively obtaining the spectrum coupling index calculated by the spectrum coupling analysis step and the time domain coupling index obtained by the time domain interaction analysis step, and normalizing the spectrum coupling index and the time domain coupling index respectively so that their numerical ranges are limited to between 0 and 1; According to the set multi-factor weight model, adjustable weight factors are assigned to the spectrum coupling index and the time domain coupling index respectively; A nonlinear mapping function was used to fuse the normalized spectral coupling index and the time domain coupling index to construct the joint resonance superposition degree. The joint resonance superposition degree was a continuous value between 0 and 1, which was used to quantitatively reflect the risk of synergistic resonance caused by the simultaneous superposition of magnetic therapy and light therapy in the frequency domain and time domain.

6. The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to claim 1 is characterized in that: When the combined resonance superposition degree exceeds the preset safety threshold, a delayed duty cycle limiting control is applied to the magnetic therapy waveform or the light therapy waveform, specifically: Apply dynamic delay control to the pulse signal in each cycle of the current excitation waveform. Assuming that the waveform period is T and the rising edge time of the original excitation pulse is , the required delay is calculated based on the difference between the joint resonance superposition degree and the preset safety threshold, and the rising edge time point after the delay is calculated based on the delay. The calculation expression is: ,in: is the delay modulation coefficient, which is used to control the sensitivity of the delay amplitude. ; The joint resonance superposition degree is calculated in real time, indicating the current magneto-optical resonance risk level; is the preset safety threshold, indicating the maximum allowable resonance risk value; is the delay time, which controls the starting offset of the excitation signal; is the rising edge time point after delay.

7. The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to claim 6 is characterized in that: After adjusting the start time of the excitation signal, continue to limit the continuous conduction time within a single cycle. The limiting processing formula is as follows: ,in: is the on-time after limiting; The maximum on-time allowed in the current cycle; is the limiting response factor, which is used to adjust the intensity of output energy reduction. ; Fractional terms It indicates the excess ratio of resonance risk, ensuring that as the risk value increases, the on-time shrinks nonlinearly.

8. An intelligent physiotherapy control system based on multi-scenario and multi-element collaboration, used to implement the intelligent physiotherapy control method based on multi-scenario and multi-element collaboration as described in any one of claims 1 to 7, characterized in that: It includes spectrum feature extraction module, spectrum coupling analysis module, time domain coupling analysis module, risk assessment and fusion module and dynamic intervention control module; The spectrum feature extraction module performs short-time Fourier transform on the driving waveform of the magnetic therapy module and the excitation waveform of the light therapy module, extracts the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and constructs a set of magnetic-optical dual-channel spectrum feature vectors; The spectrum coupling analysis module calculates the relative frequency ratio and energy superposition ratio between the main frequency point of magnetic therapy and the main frequency point of light therapy and their higher harmonics based on the spectrum feature vector set to obtain the spectrum coupling index; The time-domain coupling analysis module determines the effective action time period of the magnetic therapy output and the light therapy output in the same area of ​​physical space, calculates the time overlap ratio and energy cross-integral value of the action time period, and normalizes the energy cross-integral value into the time-domain coupling index; The risk assessment and fusion module integrates the spectrum coupling degree and time domain coupling indicators, calculates the joint resonance superposition degree through a weighted mapping function, and evaluates the resonance superposition risk intensity between magnetic therapy and light therapy in real time; The dynamic intervention control module applies delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform when the combined resonance superposition degree exceeds the preset safety threshold, delaying the rising edge of the excitation pulse within each waveform cycle, limiting its continuous conduction time, and adjusting the output peak power duration.

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