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

Abstract

This invention discloses an intelligent physiotherapy control system and method based on multi-scenario, multi-element collaboration, relating to the field of physiotherapy technology. The method includes the following steps: performing short-time Fourier transforms on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module respectively, extracting the dominant frequency component, harmonic frequency band, and energy density parameters within each working cycle, and constructing a set of magnetic-optical dual-channel spectral feature vectors; based on the spectral feature vector set, calculating the relative frequency ratio and energy superposition ratio between the dominant frequency point of magnetotherapy and the dominant frequency point of phototherapy and their higher harmonics, obtaining a spectral coupling degree index. This invention achieves quantitative assessment of the risk intensity of magnetotherapy and phototherapy by constructing a joint resonance superposition degree, and dynamically adjusts the waveform timing based on this index. By delaying the rising edge and limiting the conduction time, it achieves peak-shifting control of energy output, effectively reducing instantaneous superposition density and improving physiotherapy safety and system adaptability.

Description

Technical Field

[0001] This invention relates to the field of physiotherapy technology, specifically to an intelligent physiotherapy control system and method based on multi-scenario and multi-element collaboration. Background Technology

[0002] Intelligent physiotherapy control based on multi-scenario and multi-element synergy refers to an intelligent technology system that integrates multiple physiotherapy elements (such as phototherapy, magnetotherapy, negative oxygen ions, and far-infrared radiation) and implements dynamic and coordinated control for different usage scenarios (such as full-body physiotherapy, foot care, and sleep relaxation). This control mechanism can not only identify the user's current usage status and scenario requirements, but also intelligently match the output parameters of different elements according to the physiotherapy goals. For example, it can adjust the phototherapy wavelength to suit muscle relaxation, regulate the magnetotherapy frequency to promote nerve regulation, control the concentration of negative oxygen ions to improve the respiratory environment, and regulate the intensity of far-infrared radiation to enhance the deep warming effect. Through the coordinated optimization of various physiotherapy elements in the time domain, spatial domain, and effect domain, 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 physiotherapy.

[0003] The existing technology has the following shortcomings:

[0004] In existing physiotherapy systems based on multi-element synergistic control, there is a lack of effective resonance intervention mechanisms between the magnetic therapy frequency output and the phototherapy wave pattern, which can easily lead to unpredictable frequency coupling phenomena at specific tissue levels. When the two resonate and superimpose within the tissue, it may cause abnormal accumulation of local energy density, resulting in deep muscle or nerve tissue continuously absorbing energy without a significant increase in skin surface temperature, forming so-called "deep hotspot areas." Because such deep thermal effects are not sensitive to the user's subjective perception and are difficult to detect using traditional temperature control methods, they can easily cause damage to tissue protein structure, abnormal nerve conduction function, or even irreversible burns. This is a typical case of hidden harm, seriously threatening the user's physiological safety during long-term physiotherapy.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent physiotherapy control system and method based on multi-scenario and multi-element collaboration to solve the problems in the background art.

[0007] 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:

[0008] Short-time Fourier transforms are performed on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module respectively to extract the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and to construct a set of magneto-optical dual-channel spectral feature vectors.

[0009] Based on the set of spectral feature vectors, the relative frequency ratio and energy superposition ratio between the main frequency point of magnetotherapy and the main frequency point of phototherapy and their higher harmonics are calculated to obtain the spectral coupling index, which is used to reflect the synergy of the waveforms of magnetotherapy and phototherapy in the frequency distribution structure.

[0010] Within a unit time window, determine the effective period of action of magnetic therapy output and phototherapy output in the same area of ​​physical space, calculate the time overlap ratio and energy cross integral value of the period of action, and standardize the energy cross integral value into a time-domain coupling index.

[0011] The spectral coupling degree and temporal coupling index are integrated, and the joint resonance superposition degree is calculated through a weighted mapping function. The joint resonance superposition degree is a continuous value between 0 and 1, which is used to assess the intensity of resonance superposition risk between magnetotherapy and phototherapy in real time.

[0012] When the superposition of joint resonances exceeds the preset safety threshold, the control system applies a time-delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform. In each waveform cycle, the rising edge of the excitation pulse is delayed and its continuous conduction time is limited to adjust the duration of the output peak power, thereby suppressing the risk of instantaneous energy superposition.

[0013] Preferably, the step of performing short-time Fourier transforms on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module to construct a set of spectral feature vectors specifically includes:

[0014] The original output waveforms of the magnetotherapy module and the phototherapy module are sampled separately and processed into short-time segments using a preset time sliding window to obtain multiple local waveform segments, which are used to capture the time-frequency characteristics of non-stationary signals.

[0015] For each local waveform segment, a short-time Fourier transform is performed to extract the main frequency component, the second-order and above harmonic frequency bands, and the energy density value corresponding to each frequency band, forming a single-channel spectral feature description vector.

[0016] The spectral feature description vectors obtained from the magnetotherapy module and the phototherapy module are paired according to the timestamp synchronization method and merged into a set of magneto-optical dual-channel spectral feature vectors for subsequent spectral coupling analysis and resonance risk assessment.

[0017] Preferably, the steps for calculating the spectral coupling index specifically include:

[0018] The dominant frequency component and the second to fifth order higher harmonic components in each working cycle are extracted from the magnetic-optic dual-channel spectral feature vector set, respectively, to construct the dominant frequency-harmonic frequency list, and the energy density value corresponding to each frequency component is normalized.

[0019] For each pair of magnetic therapy frequency components and phototherapy frequency components, calculate their relative frequency ratio and determine whether the relative frequency ratio falls within a preset resonance window range. For frequency pairs that fall within the resonance window range, further calculate their energy density superposition ratio to evaluate the energy interaction intensity of the frequency pair within the tissue action area.

[0020] Based on the relative frequency ratios and energy density superposition ratios of all major and harmonic frequency pairs, a weighted combination function is used to calculate the spectral coupling index. The spectral coupling index is used to quantitatively reflect the coupling trend and synergistic risk level of the magnetotherapy and phototherapy waveforms in the frequency distribution structure.

[0021] Preferably, the steps for calculating the time-domain coupling index specifically include:

[0022] Within a unit time window, the spatial overlap area of ​​the magnetic therapy output and phototherapy output in the target tissue area is determined by the preset spatial positioning parameters in the sensor array or control module, and the actual time period of their effects within the spatial overlap area is extracted.

[0023] Based on the extracted actual time period, time-energy function curves for magnetotherapy and phototherapy are constructed respectively. The energy output of the two in the overlapping time period is calculated point by point to obtain the energy cross integral value, which reflects the degree of energy superposition of the two physiotherapy forms acting simultaneously in time.

[0024] The obtained energy cross-integral value and the total energy output value of magnetotherapy and phototherapy within the corresponding time window are normalized to form a standardized time-domain coupling index, which is used to quantitatively evaluate the superposition synergy of the two physiotherapy signals on the time axis and the intensity of instantaneous energy interaction.

[0025] Preferably, the steps for calculating the joint resonance superposition degree specifically include:

[0026] The spectral coupling degree index calculated by the spectral coupling analysis step and the temporal coupling index obtained by the temporal interaction analysis step are obtained respectively. The spectral coupling degree index and the temporal coupling index are normalized respectively to limit their numerical range to between 0 and 1, so as to ensure that the two are comparable and compatible within the same numerical scale.

[0027] Based on the multi-factor weighting model set by the system, adjustable weighting factors are assigned to the spectral coupling index and the temporal coupling index respectively. The weighting factors can be dynamically configured according to the usage scenario, organization type or risk sensitivity strategy to adapt to the risk assessment needs under different physiotherapy goals.

[0028] A nonlinear mapping function is used to fuse the normalized spectral coupling index and the temporal 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 magnetotherapy and phototherapy in the frequency domain and time domain, and serves as the basis for judging the triggering of subsequent dynamic control mechanisms.

[0029] Preferably, when the superposition degree of joint resonance exceeds a preset safety threshold, a time-delayed duty cycle limiting control is applied to the magnetotherapy waveform or phototherapy waveform, specifically as follows:

[0030] First, dynamic delay control is applied to the pulse signal within each cycle of the current excitation waveform (magnetotherapy or phototherapy). Assuming the waveform period is T, and the rising edge time of the original excitation pulse is... The required delay is calculated based on the excess amplitude between the joint resonance superposition degree and the preset safety threshold, and the rise time after the delay is calculated based on the delay amount. The calculation expression is as follows: ,in: These are the delay modulation coefficients, used to control the sensitivity to the delay amplitude. ; The joint resonance superposition degree, calculated in real time, represents the current level of magneto-optical resonance risk. The preset safety threshold represents the maximum permissible resonance risk value; The delay duration controls the initial offset of the excitation signal; This refers to the delayed rising edge time.

[0031] Preferably, after adjusting the start time of the excitation signal, the continuous conduction time within a single cycle is further limited to avoid excessive accumulation of peak power that may still occur after the delay. The limiting formula is as follows: ,in: The conduction time (effective pulse width) after amplitude limiting; This represents the maximum allowable on-time during the current cycle. This is a limiting response factor used to regulate the degree of output energy reduction. fractional terms The over-limit weight of the resonance risk is used to ensure that the conduction time shows a non-linear shrinkage trend as the risk value increases.

[0032] An intelligent physiotherapy control system based on multi-scenario and multi-element collaboration includes 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.

[0033] The spectrum feature extraction module performs short-time Fourier transform on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module respectively, extracts the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and constructs a set of magneto-optical dual-channel spectrum feature vectors.

[0034] The spectrum coupling analysis module, based on the set of spectrum feature vectors, calculates the relative frequency ratio and energy superposition ratio between the main frequency point of magnetotherapy and the main frequency point of phototherapy and their higher harmonics, and obtains the spectrum coupling index.

[0035] The temporal coupling analysis module determines the effective time period of magnetic therapy output and phototherapy output in the same area of ​​physical space, calculates the time overlap ratio and energy cross integral value of the time period, and standardizes the energy cross integral value into a temporal coupling index.

[0036] The risk assessment and fusion module integrates spectral coupling degree and temporal coupling index, calculates joint resonance superposition degree through a weighted mapping function, and assesses the risk intensity of resonance superposition between magnetotherapy and phototherapy in real time.

[0037] The dynamic intervention control module applies a delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform when the superposition degree of joint resonance exceeds the preset safety threshold. It delays the rising edge of the excitation pulse in each waveform cycle and limits its continuous conduction time, thereby adjusting the duration of the output peak power.

[0038] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0039] This invention extracts the spectral structure and spatial timing characteristics of magnetotherapy and phototherapy waveforms in real time, constructs a unified joint resonance superposition degree, quantifies the risk intensity of the two therapeutic signals during their synergistic effect, and dynamically drives a refined waveform control strategy based on this. In particular, by delaying the rising edge of the excitation pulse and limiting the conduction time, the multimodal energy output achieves a staggered distribution in the time domain, significantly reducing the energy superposition density per unit time, avoiding excessive energy concentration within tissues, and ensuring physiological safety and intervention reliability during long-term therapy. This provides an efficient, safe, and adaptive synergistic control solution for multi-element intelligent physiotherapy devices. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0041] Figure 1 This is a flowchart of an intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to the present invention.

[0042] Figure 2 This is a schematic diagram of a module of an intelligent physiotherapy control system based on multi-scenario and multi-element collaboration according to the present invention. Detailed Implementation

[0043] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0044] This invention provides, for example Figure 1 The intelligent physiotherapy control method shown includes the following steps:

[0045] Short-time Fourier transforms are performed on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module respectively to extract the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and to construct a set of magneto-optical dual-channel spectral feature vectors.

[0046] The steps of performing short-time Fourier transforms on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module to construct a set of spectral feature vectors specifically include:

[0047] The original output waveforms of the magnetotherapy module and the phototherapy module are sampled separately and processed into short-time segments using a preset time sliding window to obtain multiple local waveform segments, which are used to capture 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 above harmonic frequency bands, and the corresponding energy density values ​​of each frequency band, forming a single-channel spectral feature description vector. The spectral feature description vectors obtained by the magnetotherapy module and the phototherapy module are paired according to the timestamp synchronization method and merged into a magneto-optical dual-channel spectral feature vector set for subsequent spectral coupling analysis and resonance risk assessment.

[0048] The purpose of this step is to provide a high-precision, structured mathematical description of the frequency behavior characteristics between magnetotherapy and phototherapy, two different physical intervention methods, thereby providing data support for subsequent spectral coupling analysis and resonance risk assessment. Magnetotherapy and phototherapy typically act on human tissues in the form of periodic or quasi-periodic signals during physical therapy. 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 the superposition effect of the two in the frequency domain will constitute potential physical interference.

[0049] By performing short-time Fourier transforms (STFTs) on the magnetotherapy-driven waveform and the phototherapy-excited waveform, the dominant frequency component, harmonic distribution, and energy density changes can be captured simultaneously in both time and frequency dimensions. This method is particularly suitable for processing unsteady signals under dynamic control modes. It can not only identify whether there is frequency proximity, overlap, or resonance between two therapeutic signals, but also further evaluate the intensity of local frequency bands' influence at the tissue level by extracting energy density parameters.

[0050] The extracted results are ultimately structured into a set of magnetic-optical dual-channel spectral feature vectors, enabling standardized expression and comparison of the frequency domain behavior of the two physiotherapy methods. This provides a solid data foundation for constructing a spectral coupling degree model and joint resonance superposition degree. This process is a core prerequisite for the risk identification and energy synergistic regulation mechanism in the entire intelligent physiotherapy control system, possessing crucial signal analysis and decision support value.

[0051] Based on the set of spectral feature vectors, the relative frequency ratio and energy superposition ratio between the main frequency point of magnetotherapy and the main frequency point of phototherapy and their higher harmonics are calculated to obtain the spectral coupling index, which is used to reflect the synergy of the waveforms of magnetotherapy and phototherapy in the frequency distribution structure.

[0052] The specific steps for calculating the spectral coupling index include:

[0053] The dominant frequency component and second- to fifth-order harmonic components within each working cycle are extracted from the magnetic-optical dual-channel spectral feature vector set to construct a dominant-harmonic frequency list. The energy density values ​​corresponding to each frequency component are normalized. For each pair of magnetic therapy frequency components and phototherapy frequency components, their relative frequency ratio is calculated, and it is determined whether the relative frequency ratio falls within a preset resonance window. For frequency pairs that fall within the resonance window, their energy density superposition ratio is further calculated to assess 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 dominant and harmonic frequency pairs, a weighted combination function is used to calculate the spectral coupling index. The spectral coupling index is used to quantitatively reflect the coupling trend and synergistic risk level of the magnetic therapy and phototherapy waveforms in the frequency distribution structure.

[0054] For each pair of magnetotherapy and phototherapy frequency components, their relative frequency ratio is calculated. This is mainly done by dividing the phototherapy frequency component by the magnetotherapy frequency component to obtain the relative ratio between the two, such as 1:1, 2:1, 3:2, etc. Then, this ratio is matched with a preset resonance window range. This window is usually set as a set of typical resonance ratio ranges with high coupling potential (such as 1:1±δ, 2:1±δ, 3:2±δ, where δ is the allowable error).

[0055] 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 list of weight values. Its specific function is to identify the possibility of physical resonance between magnetotherapy and phototherapy at specific frequency combinations. Because specific integer or near-integer multiples of frequencies often induce standing wave effects or local energy coupling within biological tissues, thus constituting resonance risk points. By determining whether the frequency falls within the resonance window range, frequency-level coupling screening can be achieved, providing a precise basis for subsequent risk quantification and control decisions.

[0056] By analyzing the structural relationship between the dominant frequencies and higher harmonics of magnetotherapy and phototherapy in the frequency domain, a quantifiable spectral synergy index is established to identify and assess potential frequency coupling or resonance phenomena during their interaction. Magnetotherapy and phototherapy each possess different physical wave characteristics. While their dominant frequencies and harmonics can be independently controlled in terms of timing, the presence of approximately integer multiples or linear correlations in the frequency domain can easily lead to frequency matching within tissues, resulting in local energy superposition effects. This coupling can potentially cause latent heat accumulation, especially in low-thermal-sensing areas such as deep muscles and nerves. Therefore, using a set of spectral feature vectors, we first extract each frequency component and calculate the relative frequency ratio between magnetotherapy and phototherapy to identify whether they are within a preset resonance window. Furthermore, by using the superposition ratio of energy densities, we quantify the actual energy coupling strength under this frequency relationship, thereby comprehensively assessing the degree of spectral coupling between the two. The resulting spectral coupling index not only possesses structural sensitivity but also accurately reflects the energy interaction trend within the frequency domain. It serves as crucial reference data for the entire system in risk identification, intelligent control, and triggering of linkage protection mechanisms, thereby enhancing the personalized precision and physiological safety of the physiotherapy system.

[0057] Within a unit time window, determine the effective period of action of magnetic therapy output and phototherapy output in the same area of ​​physical space, calculate the time overlap ratio and energy cross integral value of the period of action, and standardize the energy cross integral value into a time-domain coupling index.

[0058] The specific steps for calculating the time-domain coupling index include:

[0059] Within a unit time window, the spatial overlap area of ​​the magnetic therapy output and phototherapy output in the target tissue area is determined by the preset spatial positioning parameters in the sensor array or control module, and the actual time period of their effects within this spatial overlap area is extracted. Based on the extracted actual time period, time-energy function curves of magnetic therapy and phototherapy are constructed respectively. The energy output of the two in the overlap time period is multiplied point by point to obtain the energy cross-integral value, which reflects the degree of energy superposition of the two physiotherapy forms acting simultaneously in time. The obtained energy cross-integral value and the total energy output value of magnetic therapy and phototherapy in the corresponding time window are normalized 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.

[0060] This step quantifies the actual superposition of magnetotherapy and phototherapy outputs in both temporal and spatial dimensions, providing crucial evidence for identifying potential risks of instantaneous energy concentration. In multimodal therapy systems, while the output timing of magnetotherapy and phototherapy can be independently controlled, in practice they often need to act simultaneously or alternately on the same tissue area to achieve a comprehensive therapeutic 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 highly likely that instantaneous energy accumulation will occur in a short period, inducing abnormal tissue reactions or thermal effect accumulation, especially in deep tissues where the user is unaware of the effects, potentially leading to "hidden overload."

[0061] This step first identifies the spatially overlapping regions of magnetotherapy and phototherapy within a unit time window, ensuring that only the overlapping portions are analyzed. Then, by calculating the temporal overlap ratio within this region, the duration of the combined effect of the two therapeutic methods within the same time period can be assessed. Furthermore, energy cross-integration calculations are introduced, considering not only the overlap time but also the energy output intensity of the two therapeutic signals, obtaining the energy overlap degree through function multiplication. Finally, the integral value is standardized to obtain a temporal coupling index, which directly reflects the superposition intensity of the combined magneto-optical effect along the time axis.

[0062] In summary, this step is the core mechanism for the intelligent control system to determine whether there is a "momentary concentration of energy peaks". It is of great significance to prevent safety hazards caused by the incoordination of multi-source physiotherapy signals and provides accurate time-domain risk parameters to support the construction of joint resonance superposition degree and the triggering of dynamic amplitude limiting control strategy.

[0063] The spectral coupling degree and temporal coupling index are integrated, and the joint resonance superposition degree is calculated through a weighted mapping function. The joint resonance superposition degree is a continuous value between 0 and 1, which is used to assess the intensity of resonance superposition risk between magnetotherapy and phototherapy in real time.

[0064] The specific steps for calculating the superposition degree of joint resonances include:

[0065] The spectral coupling degree index calculated by the spectral coupling analysis step and the temporal coupling index obtained by the temporal interaction analysis step are obtained separately. Both the spectral coupling degree index and the temporal coupling index are normalized to limit their numerical range to between 0 and 1, ensuring comparability and fusion within the same numerical scale. Based on the system's multi-factor weighting model, adjustable weight factors are assigned to the spectral coupling degree index and the temporal coupling index respectively. These weight factors can be dynamically configured according to the usage scenario, organization type, or risk sensitivity strategy to adapt to the risk assessment needs under different therapeutic goals. A nonlinear mapping function is used to fuse the normalized spectral coupling degree index and the temporal coupling index to construct a joint resonance superposition degree. The joint resonance superposition degree is a continuous value between 0 and 1, used to quantitatively reflect the degree of synergistic resonance risk generated by the simultaneous superposition of magnetotherapy and phototherapy in the frequency and time domains, and serves as the basis for determining the triggering of subsequent dynamic control mechanisms.

[0066] By fusing synergistic information from both the frequency and time domains, a unified and quantifiable risk assessment index—the joint resonance superposition degree—is constructed. This index is used to monitor in real time whether there is a risk of synergistic resonance between magnetotherapy and phototherapy, and to provide a reliable triggering basis for subsequent dynamic power control strategies. In multimodal physiotherapy systems, magnetotherapy and phototherapy each have independent frequency characteristics and energy output features, and may exhibit varying degrees of coupling effects at different times, locations, or treatment courses. If there is a strong superposition trend in both frequency distribution and temporal effects, synergistic resonance may occur, leading to a transient high energy density accumulation in local tissues, and potentially creating safety hazards such as "deep hotspot areas."

[0067] To avoid misjudgments caused by considering only one dimension (such as frequency matching or time overlap), this step comprehensively introduces the two parameters calculated above: spectral coupling degree and temporal coupling index. A multi-factor synergistic index is constructed through a weighted mapping method. First, both indices are normalized to unify their numerical scale, ensuring the scientific validity and stability of subsequent fusion calculations. Next, based on the system's preset or scenario-adaptive risk assessment strategy, different weights are assigned to the spectral coupling degree and temporal coupling index. For example, the weight of spectral coupling degree can be appropriately increased in high-frequency intervention scenarios, while the consideration of temporal overlap effects is strengthened in long-term continuous treatment.

[0068] This fusion process typically employs a weighted combination of nonlinear mapping functions (such as exponentially decaying functions, hyperbolic functions, or logistic regression functions) to form a joint resonance superposition degree with a continuous value range between 0 and 1. The closer the value of this joint resonance superposition degree is to 1, the stronger the synergistic superposition trend between magnetic and phototherapy, and the higher the potential risk of triggering resonance. 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 resonant coupling between magnetic therapy and phototherapy in the current state.

[0069] By constructing this joint resonance superposition degree, not only can real-time quantitative assessment of the risk of synergistic resonance be achieved, but seamless integration with the control module can also be realized. This enables the system to implement dynamic intervention measures such as duty cycle regulation, delay triggering, or power limiting, which is a key technical link in ensuring the balance between user physiological safety and the controllability of physiotherapy effects. Therefore, this step plays a core role in bridging risk perception, decision-making, and control response in the entire intelligent physiotherapy control system.

[0070] When the superposition of joint resonances exceeds the preset safety threshold, the control system applies a time-delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform. In each waveform cycle, the rising edge of the excitation pulse is delayed and its continuous conduction time is limited to adjust the duration of the output peak power, thereby suppressing the risk of instantaneous energy superposition.

[0071] When the superposition degree of joint resonance exceeds a preset safety threshold, a time-delayed duty cycle limiting control is applied to the magnetic therapy waveform or phototherapy waveform, specifically as follows:

[0072] First, dynamic delay control is applied to the pulse signal within each cycle of the current excitation waveform (magnetotherapy or phototherapy). Assuming the waveform period is T, and the rising edge time of the original excitation pulse is... The required delay is calculated based on the excess amplitude between the joint resonance superposition degree and the preset safety threshold, and the rise time after the delay is calculated based on the delay amount. The calculation expression is as follows: ,in: These are the delay modulation coefficients, used to control the sensitivity to the delay amplitude. ; The joint resonance superposition degree, calculated in real time, represents the current level of magneto-optical resonance risk. The preset safety threshold represents the maximum permissible resonance risk value; The delay duration controls the initial offset of the excitation signal; This refers to the delayed rising edge time point;

[0073] This step aims to proactively disrupt the synchronization of the two physical intervention signals on the time axis by delaying the rising edge of the magnetic or phototherapy excitation waveform, especially preventing their energy output peaks from acting on the same tissue area at the same moment. When magnetic therapy and phototherapy have a potential resonance tendency in their frequency structure, their waveforms often exhibit a certain periodic overlap trend. If this is superimposed with complete synchronization on the time axis, it may cause local tissue to suffer a double high-intensity energy injection in a very short time, thereby inducing a sharp increase in instantaneous energy density and forming a "deep hot spot area." Since this type of energy superposition usually does not immediately manifest as a temperature rise in the skin surface, it is not easily perceived by the user or detected in time by traditional thermal control systems, exhibiting obvious characteristics of hidden damage.

[0074] By dynamically calculating the delay time using the difference between the combined resonance superposition degree and the safety threshold, this mechanism can flexibly postpone the starting point of the excitation pulse's rising edge based on the system's perception of real-time risk intensity, achieving adaptive decoupling of the magneto-optical coupling relationship within different treatment cycles. The delay amplitude is a continuously adjustable quantity, controlled by the degree of risk exceeding limits and the system sensitivity factor. It can finely adjust the temporal distribution of energy input without disrupting the treatment rhythm and overall frequency strategy, thereby minimizing the probability of interference between the two physiotherapy signals in the time domain. This step is not only a passive protection strategy but also a "feedforward" safety coordination mechanism with extremely high engineering practicality and dynamic response value, making it one of the core control links in constructing a reliable intelligent physiotherapy system.

[0075] After adjusting the start time of the excitation signal, the continuous conduction time within a single cycle is further limited to avoid excessive accumulation of peak power that may still occur after the delay. The limiting formula is as follows: ,in: The conduction time (effective pulse width) after amplitude limiting; This represents the maximum allowable on-time during the current cycle. This is a limiting response factor used to regulate the degree of output energy reduction. fractional terms The over-limit weighting of the resonance risk ensures that the conduction time exhibits a non-linear shrinkage trend as the risk value increases;

[0076] Based on the intensity of the synergistic effect of magnetotherapy and phototherapy reflected by the current degree of joint resonance superposition, 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 this output window, i.e., 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 goal of reducing the rate of tissue energy accumulation. This is particularly crucial in multimodal physiotherapy systems because once the magnetotherapy 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 regions. These hotspots, because they are not accompanied by significant surface temperature rise, are often difficult to detect by conventional temperature control systems.

[0077] Furthermore, this dynamic limitation on conduction time is not rigidly set, but rather combines the over-limit ratio between the combined resonance superposition degree and the preset safety threshold, using a nonlinear compression model to control the maximum effective pulse width, thereby giving the system stronger risk adaptability and response elasticity. In high-risk states, the output window will be significantly compressed to quickly suppress possible instantaneous energy concentration; while in low-risk states, a relatively wide output time period is retained to avoid affecting normal therapeutic efficacy. This continuously adjustable control strategy not only ensures precise regulation of tissue energy load but also avoids the weakening of therapeutic effect caused by one-size-fits-all control, making it a key control logic for achieving a "safety and effectiveness balance" in intelligent physiotherapy systems. Simultaneously, this mechanism possesses advantages such as strong real-time performance, high programmability, and moderate requirements for device hardware resources, making it suitable for rapid integration into embedded microcontroller systems and possessing high engineering implementation value and practicality.

[0078] The core function of this step is to establish a dynamic, responsive energy intervention control mechanism to suppress the physiological risks arising from the potential instantaneous energy superposition of magnetotherapy and phototherapy in terms of frequency and time, particularly the problem of "hidden heat accumulation" that is difficult to perceive in deep tissues. In multimodal physiotherapy systems, although magnetotherapy and phototherapy are two independent physical stimulation methods, they are often integrated into the same treatment device and applied to the same body area in practical applications. Due to the possibility of structural coupling in their regulation mechanisms or signal generation methods, they can easily form synchronous excitations of the same or similar frequencies on the time axis. If such synchronization is not restricted, it may lead to the superposition of pulses of the two waveforms within the same time window, resulting in excessively high peak power output per unit time, especially inducing the phenomenon of "deep hotspots" where energy density abnormally accumulates in deep muscle or nerve tissue. Since these effects are not necessarily accompanied by a rise in surface temperature, users find it difficult to perceive the abnormality through the skin. Furthermore, traditional temperature control mechanisms are mostly based on surface detection, thus exhibiting significant concealment and unpredictability.

[0079] Through this step, when the system detects that the combined resonance superposition degree (used to assess the risk level of synergistic resonance between magnetotherapy and phototherapy) exceeds a preset safety threshold, it immediately takes two core intervention measures on the output waveform: delaying the rise edge and limiting the conduction time. The former, by dynamically calculating the delay time, shifts the start time of the excitation pulse backward, reducing the probability of superposition of magnetotherapy and phototherapy in the time dimension and avoiding energy synchronization impact; the latter further limits and compresses the pulse duration within a waveform cycle, effectively reducing the total energy injection in the overlapping area even if the two excitation signals still have partial time overlap. The two control strategies work together to both break the formation conditions of synchronous resonance and suppress possible concentrated energy peaks, thereby achieving refined and real-time control of safety risks while ensuring therapeutic efficacy.

[0080] Furthermore, this control mechanism is based on the quantitative calculation of the difference between the joint resonance superposition degree and the safety threshold, possessing adaptive and continuous adjustment capabilities. It can dynamically adjust the delay and conduction time compression ratio according to the actual risk level, unlike the traditional fixed threshold power limiting strategy. It boasts a high degree of intelligence and fast response speed, making it suitable for integrated control in embedded systems or medical-specific chip platforms. It demonstrates strong engineering feasibility and clinical application value in multi-scenario intelligent physiotherapy systems, and is a key component in achieving a "safety-efficiency dual balance" control strategy.

[0081] The aforementioned intelligent physiotherapy control method based on multi-scenario and multi-element collaboration achieves comprehensive perception and dynamic intervention of the potential resonance superposition risk of magnetotherapy and phototherapy in the frequency and time domains, effectively solving the problem of hidden thermal damage in "deep hot spots" caused by the lack of resonance control mechanisms in existing technologies. This scheme can not only extract and analyze the spectral structure and spatial action timing of the two physiotherapy waveforms in real time, but also construct a unified joint resonance superposition degree, quantify the intensity of collaborative risk, and thus trigger a refined waveform modulation mechanism. In particular, by delaying the rising edge of the excitation pulse and limiting the conduction time, the energy is distributed in a staggered temporal pattern, significantly reducing the instantaneous superposition power per unit time, effectively suppressing the energy accumulation trend in deep tissues, and ensuring physiological safety during long-term physiotherapy. Therefore, this method has good safety, adaptability, and engineering feasibility, providing an intelligent, efficient, and scalable energy coordination control technology path for multimodal physiotherapy devices.

[0082] This invention provides, for example Figure 2 The intelligent physiotherapy control system shown includes 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.

[0083] The spectrum feature extraction module performs short-time Fourier transform on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module respectively, extracts the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and constructs a set of magneto-optical dual-channel spectrum feature vectors.

[0084] The spectrum coupling analysis module, based on the set of spectrum feature vectors, calculates the relative frequency ratio and energy superposition ratio between the main frequency point of magnetotherapy and the main frequency point of phototherapy and their higher harmonics, and obtains the spectrum coupling index.

[0085] The temporal coupling analysis module determines the effective time period of magnetic therapy output and phototherapy output in the same area of ​​physical space, calculates the time overlap ratio and energy cross integral value of the time period, and standardizes the energy cross integral value into a temporal coupling index.

[0086] The risk assessment and fusion module integrates spectral coupling degree and temporal coupling index, calculates joint resonance superposition degree through a weighted mapping function, and assesses the risk intensity of resonance superposition between magnetotherapy and phototherapy in real time.

[0087] The dynamic intervention control module applies a delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform when the superposition degree of joint resonance exceeds the preset safety threshold. It delays the rising edge of the excitation pulse in each waveform cycle and limits its continuous conduction time, thereby adjusting the duration of the output peak power.

[0088] The present invention provides an intelligent physiotherapy control method based on multi-scenario and multi-element collaboration, which is implemented through the above-mentioned intelligent physiotherapy control system based on multi-scenario and multi-element collaboration. For details of the specific method and process of the intelligent physiotherapy control system based on multi-scenario and multi-element collaboration, please refer to the above-mentioned embodiment of the intelligent physiotherapy control method based on multi-scenario and multi-element collaboration, which will not be repeated here.

[0089] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0090] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0091] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An intelligent physiotherapy control method based on multi-scene multi-element cooperation, characterized in that, Includes the following steps: Short-time Fourier transforms are performed on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module respectively to extract the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and to construct a set of magneto-optical dual-channel spectral feature vectors. Based on the set of spectral feature vectors, the relative frequency ratio and energy superposition ratio between the main frequency point of magnetotherapy and the main frequency point of phototherapy and their higher harmonics are calculated to obtain the spectral coupling index. Determine the effective time period of magnetic therapy output and phototherapy output in the same area of ​​physical space, calculate the time overlap ratio and energy cross integral value of the time period, and standardize the energy cross integral value into a time-domain coupling index. By integrating spectral coupling degree and temporal coupling index, the joint resonance superposition degree is calculated through a weighted mapping function to assess the intensity of resonance superposition risk between magnetotherapy and phototherapy in real time. When the superposition of joint resonances exceeds the preset safety threshold, a time-delayed duty cycle limiting control is applied to the magnetic therapy waveform or phototherapy waveform. The rising edge of the excitation pulse is delayed in each waveform cycle, and its continuous conduction time is limited to adjust the duration of the output peak power. The specific steps for calculating the superposition degree of joint resonances include: The spectral coupling degree index calculated by the spectral coupling analysis step and the temporal coupling index obtained by the temporal interaction analysis step are obtained respectively. The spectral coupling degree index and the temporal coupling index are normalized respectively to limit their numerical range to between 0 and 1. Based on the established multi-factor weighting model, adjustable weighting factors are assigned to the spectral coupling index and the temporal coupling index respectively; A nonlinear mapping function is used to fuse the normalized spectral coupling index and the temporal 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 magnetotherapy and phototherapy in the frequency domain and time domain.

2. The intelligent physiotherapy control method based on multi-scene multi-element cooperation according to claim 1, characterized in that, The steps of performing short-time Fourier transforms on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module to construct a set of spectral feature vectors specifically include: The original output waveforms of the magnetotherapy module and the phototherapy module are sampled separately and processed into short-time segments using a preset time sliding window to obtain multiple local waveform segments. For each local waveform segment, a short-time Fourier transform is performed to extract the main frequency component, the second-order and above harmonic frequency bands, and the energy density value corresponding to each frequency band, forming a single-channel spectral feature description vector. The spectral feature description vectors obtained by the magnetotherapy module and the phototherapy module are paired according to the timestamp synchronization method and merged into a set of magneto-optical dual-channel spectral feature vectors. 3.The intelligent physiotherapy control method based on multi-scene multi-element cooperation according to claim 1, characterized in that, The specific steps for calculating the spectral coupling index include: The dominant frequency component and the second to fifth order higher harmonic components in each working cycle are extracted from the magnetic-optic dual-channel spectral feature vector set, respectively, to construct the dominant frequency-harmonic frequency list, and the energy density value corresponding to each frequency component is normalized. For each pair of magnetic therapy frequency components and phototherapy frequency components, calculate their relative frequency ratio and determine whether the relative frequency ratio falls within the preset resonance window range. For frequency pairs that fall within the resonance window range, calculate their energy density superposition ratio. The spectral coupling index is calculated using a weighted combination function based on the relative frequency ratios and energy density superposition ratios of all major and harmonic frequency pairs.

4. The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to claim 1, characterized in that, The specific steps for calculating the time-domain coupling index include: Within a unit time window, the spatial overlap area of ​​the magnetic therapy output and phototherapy output in the target tissue area is determined by the preset spatial positioning parameters in the sensor array or control module, and the actual time period of their effects within the spatial overlap area is extracted. Based on the extracted actual time period of action, time-energy function curves for magnetotherapy and phototherapy are constructed respectively. The energy output of the two in the overlapping time period is calculated by multiplying them point by point to obtain the energy cross integral value. The obtained energy cross-integral value and the total energy output value of magnetotherapy and phototherapy within the corresponding time window are normalized 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, characterized in that, When the superposition degree of joint resonance exceeds a preset safety threshold, a time-delayed duty cycle limiting control is applied to the magnetic therapy waveform or phototherapy waveform, specifically as follows: Dynamic delay control is applied to the pulse signal within each cycle of the current excitation waveform. Assuming the waveform period is T and the rising edge time of the original excitation pulse is... The required delay is calculated based on the excess amplitude between the joint resonance superposition degree and the preset safety threshold, and the rise time after the delay is calculated based on the delay amount. The calculation expression is as follows: ,in: These are the delay modulation coefficients, used to control the sensitivity to the delay amplitude. ; The joint resonance superposition degree, calculated in real time, represents the current level of magneto-optical resonance risk. The preset safety threshold represents the maximum permissible resonance risk value; The delay duration controls the initial offset of the excitation signal; This refers to the delayed rising edge time.

6. The intelligent physiotherapy control method based on multi-scenario and multi-element collaboration according to claim 5, characterized in that, After adjusting the start time of the excitation signal, the duration of conduction within a single cycle is further limited. The limiting formula is as follows: ,in: The conduction time after amplitude limiting; This represents the maximum allowable on-time during the current cycle. This is a limiting response factor used to regulate the degree of output energy reduction. fractional terms The over-limit weight of the resonance risk is used to ensure that the conduction time shows a non-linear shrinkage trend as the risk value increases.

7. A smart physiotherapy control system based on multi-scene and multi-element collaboration, used to implement the smart physiotherapy control method based on multi-scene and multi-element collaboration as described in any one of claims 1-6, characterized in that, It includes 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 and control module; The spectrum feature extraction module performs short-time Fourier transform on the driving waveform of the magnetotherapy module and the excitation waveform of the phototherapy module respectively, extracts the main frequency component, harmonic frequency band and energy density parameters in each working cycle, and constructs a set of magneto-optical dual-channel spectrum feature vectors. The spectrum coupling analysis module, based on the set of spectrum feature vectors, calculates the relative frequency ratio and energy superposition ratio between the main frequency point of magnetotherapy and the main frequency point of phototherapy and their higher harmonics, and obtains the spectrum coupling index. The temporal coupling analysis module determines the effective time period of magnetic therapy output and phototherapy output in the same area of ​​physical space, calculates the time overlap ratio and energy cross integral value of the time period, and standardizes the energy cross integral value into a temporal coupling index. The risk assessment and fusion module integrates spectral coupling degree and temporal coupling index, calculates joint resonance superposition degree through a weighted mapping function, and assesses the risk intensity of resonance superposition between magnetotherapy and phototherapy in real time. The dynamic intervention control module applies a delayed duty cycle limiting control to the magnetic therapy waveform or phototherapy waveform when the superposition degree of joint resonance exceeds the preset safety threshold. It delays the rising edge of the excitation pulse in each waveform cycle and limits its continuous conduction time, thereby adjusting the duration of the output peak power.

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