Control method and system based on ultrashort wave therapeutic apparatus

Abstract

The invention relates to the technical field of rehabilitation instruments, in particular to a control method and system based on an ultra-short wave therapeutic instrument. The method comprises the following steps: acquiring illness state information and human body composition data of a user; the illness state information comprises a treatment part, and the human body composition data comprises a body fat rate, a water content and a muscle content; inputting the human body composition data and the illness state information into a trained treatment parameter recommendation model to obtain treatment parameters of the user; the treatment parameters comprise output power and treatment time, and the treatment parameter recommendation model is a machine learning model; and outputting the treatment parameters, so that the ultrashort wave therapeutic apparatus emits ultrashort waves corresponding to the treatment parameters. According to the method, the treatment parameters are automatically generated according to the actual situation of the user, and the treatment effect of the user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of rehabilitation equipment, and more specifically, to a control method and system based on an ultrashort wave therapeutic apparatus. Background Art

[0002] Ultrashort wave therapy device is a commonly used physical therapy equipment. It emits high-frequency electromagnetic waves through electrode plates, which penetrate clothing, human skin and subcutaneous tissue, and act directly on the affected area, warming the body internally and producing necessary chemical reactions. It can accelerate blood circulation, melt rheumatism or sediment, promote anti-inflammation and reduce swelling. It is suitable for various acute and malignant inflammations such as wound healing and wound infection.

[0003] Ultrashort wave therapy devices usually generate ultrashort wave currents with a wavelength of 1 to 10m and a frequency of 30 to 300MHz. When using an ultrashort wave therapy device for treatment, medical staff or rehabilitation therapists generally manually set the power and working time of the ultrashort wave treatment output based on experience, and then the patient receives treatment based on this power and time. However, since the treatment parameters are set based on experience, it is easy for improper treatment parameters to cause burns, fatigue, etc. in the patient, thereby affecting the treatment effect. In addition, when setting the treatment parameters, the human body's absorption of ultrashort waves is not taken into account, resulting in a portion of the ultrashort wave being consumed when it reaches the treatment site, making the treatment effect not as good as expected.

[0004] Therefore, how to make the ultrashort wave therapy device output corresponding parameters according to the actual situation and needs of the user is a technical problem that needs to be solved urgently. Summary of the Invention

[0005] In order to solve the technical problem that the parameters of the ultrashort wave therapeutic apparatus are set based on experience, resulting in poor therapeutic effect, the present invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides a control method based on an ultrashort wave therapeutic apparatus, the method comprising: obtaining a user's medical condition information and body composition data; the medical condition information comprises the treatment site, cause of the disease and duration of illness, and the body composition data comprises body fat percentage, water content and muscle content; inputting the body composition data and the medical condition information into a trained treatment parameter recommendation model to obtain the user's treatment parameters; the treatment parameters comprise output power and treatment time, and the treatment parameter recommendation model is a machine learning model; outputting the treatment parameters so that the ultrashort wave therapeutic apparatus emits ultrashort waves corresponding to the treatment parameters.

[0007] Furthermore, the method for obtaining the treatment parameter recommendation model includes: obtaining human body composition data, disease condition information and corresponding treatment parameters; preprocessing the human body composition data, the disease condition information and the treatment parameters; inputting the preprocessed data into a preset random forest model for training to obtain the treatment parameter recommendation model.

[0008] Furthermore, before obtaining the treatment parameter recommendation model, the method further includes: using a random forest model whose comprehensive root mean square error is less than a preset threshold as the treatment parameter recommendation model, and the calculation expression of the comprehensive root mean square error is:

[0009] MSE=w1MSE w +w2MSE t ;

[0010] Where, MSE is the comprehensive root mean square error, w1 is the weight of the output power, w2 is the weight of the treatment time, w1 is greater than w2, MSE w is the root mean square error of the output power, MSE t is the root mean square error of the treatment moment.

[0011] Furthermore, during the treatment process, it also includes: collecting the temperature of the treatment site and the heart rate of the user; determining the heart rate abnormality, the heart rate abnormality indicating the possibility that the output power setting corresponding to the user exceeds the safety range, wherein the heart rate abnormality is positively correlated with the heart rate difference between the user's current moment and the treatment moment before the current moment, and is positively correlated with the heart rate difference between the user and the corresponding first case; in response to the heart rate abnormality exceeding a preset abnormal threshold, reducing the output power or shortening the treatment time; in response to the temperature exceeding a preset temperature threshold, turning off the ultrashort wave therapy device.

[0012] Furthermore, the calculation expression of the heart rate abnormality is:

[0013]

[0014] Where z i represents the abnormality of the user's heart rate at the i-th moment, k i represents the heart rate change rate of the user at the i-th moment, μ1 represents the average heart rate change rate at other moments except the i-th moment, σ1 represents the variance of the heart rate change rate at other moments except the i-th moment; μ jrepresents the average value of the heart rate change rate of the user in the j-th time period, μ2 represents the average value of the heart rate change rate of the first case corresponding to the user under the same output power, σ2 represents the variance of the heart rate change rate of the first case corresponding to the user under the same output power; norm() is a normalization function used to normalize the heart rate abnormality to the range of 0 to 1.

[0015] Furthermore, the method for obtaining the user and the corresponding first case includes: using Euclidean distance to search for the first case most similar to the user in a preset case library based on the user's medical condition information and treatment parameters; the first case represents a case that uses the same output power as the user and the output power is within a safe range.

[0016] Furthermore, collecting the temperature of the treatment site and the heart rate of the user includes: collecting the temperature through a temperature sensor, and collecting the heart rate through a heart rate sensor.

[0017] Furthermore, outputting the treatment parameters so that the ultrashort wave therapeutic device emits ultrashort waves corresponding to the treatment parameters includes: taking the treatment parameters as original treatment parameters, and generating first treatment parameters and second treatment parameters based on the original treatment parameters; wherein the parameters in the first treatment parameters are all smaller than the parameters in the original treatment parameters, and the parameters in the second treatment parameters are all larger than the parameters in the original treatment parameters; displaying the original treatment parameters, the first treatment parameters, the second treatment parameters and corresponding prompt information; and in response to receiving the treatment parameters selected by the user or medical staff, controlling the ultrashort wave therapeutic device to output the corresponding ultrashort waves.

[0018] Furthermore, the method further includes: generating a treatment report in response to the end of treatment, wherein the treatment report includes treatment parameters, a heart rate change curve, and a temperature change curve.

[0019] In a second aspect, the present invention provides a control system based on an ultrashort wave therapeutic apparatus, comprising a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a control method based on an ultrashort wave therapeutic apparatus according to the first aspect is implemented.

[0020] The beneficial effects of the present invention are that the method of the present invention can automatically generate treatment parameters for the ultrashort wave therapy device based on the user's actual situation, avoiding the need to set treatment parameters based on experience, thereby improving treatment effectiveness and reducing operational errors. Furthermore, by taking into account the fact that ultrashort waves are subject to a certain degree of attenuation in the human body, the present invention compensates for the treatment parameters by inputting human body composition data into a machine learning model, thereby improving the accuracy and reliability of determining treatment parameters. Furthermore, by adjusting the output power or treatment time according to the abnormality of the user's heart rate data and the temperature of the treatment area during treatment, harm to the user caused by excessively high power settings is avoided, thereby improving the user's safety during treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a flow chart schematically illustrating a control method based on an ultrashort wave therapeutic apparatus according to an embodiment of the present invention;

[0022] Figure 2 is a schematic diagram schematically showing an ultrashort wave therapeutic apparatus according to an embodiment of the present invention;

[0023] Figure 3 FIG. 1 is a block diagram schematically showing a structure of a control system based on an ultrashort wave therapeutic apparatus according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the scope of protection of the present invention.

[0025] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0026] Figure 1 FIG. 4 is a flow chart schematically illustrating a control method based on an ultrashort wave therapeutic apparatus according to an embodiment of the present invention.

[0027] In a first aspect, the present invention provides a control method based on an ultrashort wave therapeutic apparatus, such as Figure 1 As shown, the control method of the present invention includes:

[0028] S1. Obtain the user's medical condition information and body composition data.

[0029] Specifically, medical information includes: treatment area, duration of illness, cause, age, gender, etc., which is entered into the system by the user or medical staff. Body composition data includes body fat percentage, muscle mass, and water content, and can be measured using a body composition analyzer.

[0030] S2. Input the human body composition data and the disease condition information into a trained treatment parameter recommendation model to obtain the treatment parameters of the user.

[0031] In one embodiment, treatment parameters include treatment time and output power. It is understood that the greater the output power of the ultrashort wave therapy device, the greater the treatment energy intensity and treatment depth, and the wider the treatment range. Therefore, different patients will require different output powers. Excessive output power may cause burns, tissue damage, and other conditions, worsening the patient's condition and thus affecting the progress of treatment. Therefore, it is necessary to appropriately set the treatment time and output power.

[0032] In this embodiment, the treatment parameter recommendation model is based on a random forest model. Specifically, body composition data, condition information, and corresponding implemented treatment parameters are collected from medical device records and the hospital's electronic medical record system. The collected data is preprocessed, including data cleaning, data labeling, and feature extraction. The preprocessed data is then fed into a preset random forest model for training. The model's performance is evaluated using the root mean square error (RMSE). The random forest model with a RMSE less than a preset value is selected as the final treatment parameter recommendation model.

[0033] In one embodiment, the calculation expression of the comprehensive root mean square error is:

[0034] MSE=w1MSE w +w2MSE t ;

[0035] Where, MSE is the comprehensive root mean square error, w1 is the weight of the output power, w2 is the weight of the treatment time, w1 is greater than w2, MSE w is the root mean square error of the output power, MSE t is the root mean square error of the treatment time.

[0036] By assigning a higher weight to output power, the model can focus on improving the accuracy of output power prediction, ensuring that the treatment site can accurately obtain the required energy, and avoiding tissue burns caused by excessive power, thereby improving treatment efficacy and safety.

[0037] It is understandable that because ultrashort waves are absorbed by the human body, they experience a certain degree of attenuation before reaching the treatment site. Therefore, the power set based on experience fails to take into account the varying attenuation of ultrashort waves by different users due to varying body composition, resulting in situations where the treatment effect does not meet expectations. Therefore, by considering the attenuation of ultrashort waves by human body composition, a machine learning model is trained to output different treatment parameters based on different body composition and disease information, ensuring that the ultrashort waves that reach the treatment site achieve the desired therapeutic effect, thereby improving the user's treatment outcome.

[0038] S3. Output the treatment parameters so that the ultrashort wave therapeutic apparatus emits ultrashort waves corresponding to the treatment parameters.

[0039] In one embodiment, the treatment parameters output by the treatment parameter recommendation model can be directly sent to the ultrashort wave therapy device, so that the ultrashort wave therapy device emits ultrashort waves corresponding to the treatment parameters. In another embodiment, the first treatment parameters and the second treatment parameters can also be generated based on the original treatment parameters (i.e., the treatment parameters output by the treatment parameter recommendation model) to meet the needs of different users. In this case, the parameters in the first treatment parameters are all smaller than the parameters in the original treatment parameters, and the parameters in the second treatment parameters are all larger than the parameters in the original treatment parameters.

[0040] It is understandable that, compared to the original treatment parameters, the first treatment parameters actually reduce the treatment intensity. Specifically, the output power of the first treatment parameters may be 0.9 times the output power in the original treatment parameters, and the treatment time may also be 0.9 times the treatment time in the original treatment parameters.

[0041] Compared with the original treatment parameters, the second treatment parameters actually increase the treatment intensity. Specifically, the output power of the second treatment parameters can be 1.1 times the output power of the original treatment parameters, and the treatment time can also be 1.1 times the treatment time of the original treatment parameters.

[0042] Furthermore, the original treatment parameters, the first treatment parameters, the second treatment parameters and the corresponding prompt information are displayed on the system; specifically, the prompt information of the original treatment parameters may be "this treatment parameter is a standard treatment plan", the prompt information of the first treatment parameters may be "this treatment parameter is a conservative treatment plan", and the prompt information of the second treatment parameters may be "this treatment parameter is an enhanced plan".

[0043] After receiving the treatment parameters selected by the user or medical staff, the parameters are transmitted to the ultrashort wave therapy device, causing it to emit the designated ultrashort waves. By generating the first and second treatment parameters based on the original treatment parameters, the treatment needs of different users can be met. For example, a first-time user can select the first treatment parameter, thereby increasing treatment flexibility. Furthermore, by displaying the specific parameter values, medical staff can confirm their decision.

[0044] In one embodiment, during the treatment process, the method of the present invention further comprises: collecting the temperature of the treatment site and the heart rate of the user. Specifically, the temperature of the treatment site during the treatment process can be collected by a temperature sensor, and the heart rate of the user during the treatment process can be collected by a heart rate sensor.

[0045] The user's heart rate and temperature are monitored in real time. If they exceed corresponding thresholds, the output power or treatment time is adjusted. Specifically, during the treatment process, it is determined whether the temperature of the treatment area exceeds a preset temperature threshold. If so, the ultrashort wave therapy device is turned off. In one embodiment, the temperature threshold can be set to 42° or other values, which can be selected by those skilled in the art based on actual needs. By monitoring the temperature of the user's treatment area in real time, local burns caused by excessive power settings can be avoided, thereby improving the safety of the user's treatment.

[0046] At the same time, the user's heart rate abnormality is determined based on the user's heart rate, and a determination is made as to whether the user's heart rate abnormality exceeds a preset abnormality threshold. If so, the output power is reduced or the treatment time is shortened. The heart rate abnormality indicates the possibility that the output power setting is too high. The heart rate abnormality is positively correlated with the difference in heart rate between the user's current moment and a historical moment, as well as the difference in heart rate between the user and the corresponding first case. The historical moments referred to are the moments from the start of treatment to the current moment.

[0047] Specifically, the Euclidean distance can be used to search for the first case that is most similar to the user in the preset case library based on the user's medical condition information and treatment parameters. Specifically, in the case library, all cases with the same output power and treatment site as the user, and the set power is within a reasonable range (that is, it will not cause burns to the user, etc., and the output power is used to successfully complete the complete treatment), are determined, and then the Euclidean distance is used to search for the case that is most similar to the user among these cases, so as to obtain the first case corresponding to the user. In one embodiment, the importance of each feature can be determined based on the treatment parameter model, and then a corresponding weight is assigned to each feature in the medical condition information, and the first case closest to the user is found based on the parameter and the corresponding weight, thereby avoiding the interference of secondary features on the matching, thereby improving the reliability of determining the first case.

[0048] In one embodiment, the calculation expression of the heart rate abnormality is:

[0049]

[0050] Where z i represents the abnormality of the user's heart rate at the i-th moment, k i represents the heart rate change rate of the user at the i-th moment, μ1 represents the average heart rate change rate at other moments except the i-th moment, σ1 represents the variance of the heart rate change rate at other moments except the i-th moment; μ j represents the average value of the heart rate variability of the user in the j-th time period (one minute is regarded as a time period), μ2 represents the average value of the heart rate variability of the first case corresponding to the user under the same output power, σ2 represents the variance of the heart rate variability of the first case corresponding to the user under the same output power; norm() is a normalization function used to normalize the degree of heart rate abnormality to the range of 0 to 1.

[0051] When determining the user's own heart rate difference, by not considering the current mean and variance, it is possible to avoid the problem that the current heart rate change is large, which increases the mean and variance and thus fails to discover this abnormal situation.

[0052] Because heart rate changes significantly when power is set too high, monitoring power can verify whether the model's output power is reasonable, preventing harm to the user and ensuring safe treatment. Furthermore, by combining the user's own heart rate differences with the heart rate differences between the user and the first patient (the greater the heart rate difference, the less likely the user's output power is too high), the reliability of determining whether power is set too high can be improved, avoiding misjudgments.

[0053] In one embodiment, the abnormal threshold is set to 0.6. When the threshold is exceeded, the output power or treatment time of the user can be reduced to a certain extent, for example, the output power is controlled at 90% of the original output power.

[0054] In another embodiment, the heart rate data of cases with excessively high power settings can also be included in the determination of the heart rate abnormality to improve the reliability of the determination of the heart rate abnormality. The heart rate abnormality is positively correlated with the heart rate difference between the user's current moment and the historical moment, positively correlated with the heart rate difference between the user and the corresponding first case, and negatively correlated with the heart rate difference between the user and the second case. Specifically, the calculation expression for the heart rate abnormality is:

[0055]

[0056] Where z irepresents the abnormality of the user's heart rate at the i-th moment, k i represents the heart rate change rate of the user at the i-th moment, μ1 represents the average heart rate change rate at other moments except the i-th moment, σ1 represents the variance of the heart rate change rate at other moments except the i-th moment; μ j represents the average value of the heart rate variability of the user in the j-th time period, μ2 represents the average value of the heart rate variability of the first patient corresponding to the user under the same output power, σ2 represents the variance of the heart rate variability of the first patient corresponding to the user under the same output power; μ3 represents the average value of the heart rate variability of the second patient corresponding to the user under the setting of abnormal output power, σ3 represents the variance of the heart rate variability of the second patient corresponding to the user under the setting of abnormal output power.

[0057] When determining the second case, it is similar to determining the first case. The difference is that the second case is to first find out the cases with the same treatment part but the power setting exceeds the reasonable range (that is, during treatment, the treatment is interrupted due to the power setting being too high, or the power setting being too high results in poor treatment effect), and then find the case closest to the user among these cases as the second case.

[0058] By comprehensively considering the heart rate differences between the user at different times, the heart rate differences between the user and the first case, and the heart rate differences between the user and the second case, the reliability of determining the heart rate abnormality can be further improved, thereby avoiding misjudgment.

[0059] After the treatment is completed, a treatment report is generated based on the user's treatment data. The content of the treatment report includes treatment parameters, heart rate change curve, temperature change curve, etc.

[0060] Figure 3 FIG2 is a block diagram schematically showing a structure of a control system based on an ultrashort wave therapeutic apparatus according to this embodiment.

[0061] In a second aspect, the present invention also provides a control system based on an ultrashort wave therapeutic apparatus. Figure 3 As shown, the control system of the present invention includes a processor and a memory, wherein the memory stores computer program instructions. When the computer program instructions are executed by the processor, a control method based on an ultrashort wave therapeutic apparatus according to the first aspect of the present invention is implemented.

[0062] The control system also includes other components well known to those skilled in the art, such as a communication interface. The configuration and functions of these components are known in the art and will not be described in detail here.

[0063] In the present invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, the computer-readable storage medium can be any suitable magnetic storage medium or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc., or any other medium that can be used to store the required information and can be accessed by an application, module, or both. Any such computer storage medium can be part of a device or accessible or connectable to a device. Any application or module described in the present invention can be implemented using computer-readable / executable instructions that can be stored or otherwise retained by such a computer-readable medium.

[0064] While several embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Numerous modifications, variations, and alternatives will occur to those skilled in the art without departing from the concept and spirit of the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein may be employed in practicing the present invention.

Claims

1. A control method based on an ultrashort wave therapeutic apparatus, characterized in that: include: Obtaining the user's medical condition information and body composition data; the medical condition information includes treatment site, cause of disease, and duration of illness; the body composition data includes body fat percentage, water content, and muscle content; Inputting the human body composition data and the condition information into a trained treatment parameter recommendation model to obtain the user's treatment parameters; the treatment parameters include output power and treatment time, and the treatment parameter recommendation model is a machine learning model; The treatment parameters are output so that the ultrashort wave therapeutic apparatus emits ultrashort waves corresponding to the treatment parameters.

2. The control method based on the ultrashort wave therapeutic apparatus according to claim 1, characterized in that: The method for obtaining the treatment parameter recommendation model includes: Obtain body composition data, disease condition information and corresponding treatment parameters; Preprocessing the body composition data, the condition information, and the treatment parameters; The preprocessed data is input into a preset random forest model for training to obtain the treatment parameter recommendation model.

3. The control method based on the ultrashort wave therapeutic apparatus according to claim 2, characterized in that: Before obtaining the treatment parameter recommendation model, the method further includes: using a random forest model whose comprehensive root mean square error is less than a preset threshold as the treatment parameter recommendation model, and the calculation expression of the comprehensive root mean square error is: MSE=w1MSE w +w2MSE t ; Where, MSE is the comprehensive root mean square error, w1 is the weight of the output power, w2 is the weight of the treatment time, w1 is greater than w2, MSE w is the root mean square error of the output power, MSE t is the root mean square error of the treatment moment.

4. The control method based on the ultrashort wave therapeutic apparatus according to claim 1, characterized in that: The treatment process also includes: collecting the temperature of the treatment site and the heart rate of the user; determining a heart rate abnormality, the heart rate abnormality indicating a likelihood that the output power setting corresponding to the user exceeds a safe range, wherein the heart rate abnormality is positively correlated with a heart rate difference between the user at a current moment and a treatment moment before the current moment, and a heart rate difference between the user and a corresponding first case; In response to the abnormality of the heart rate exceeding a preset abnormal threshold, reducing the output power or shortening the treatment time; In response to the temperature exceeding a preset temperature threshold, the ultrashort wave therapy device is turned off.

5. The control method based on the ultrashort wave therapeutic apparatus according to claim 4, characterized in that: The calculation expression of the heart rate abnormality is: Where z i represents the abnormality of the user's heart rate at the i-th moment, k i represents the heart rate change rate of the user at the i-th moment, μ1 represents the average heart rate change rate at other moments except the i-th moment, σ1 represents the variance of the heart rate change rate at other moments except the i-th moment; μ j represents the average value of the heart rate change rate of the user in the j-th time period, μ2 represents the average value of the heart rate change rate of the first case corresponding to the user under the same output power, σ2 represents the variance of the heart rate change rate of the first case corresponding to the user under the same output power; norm() is a normalization function used to normalize the heart rate abnormality to the range of 0 to 1.

6. The control method based on the ultrashort wave therapeutic apparatus according to claim 5, characterized in that: The method for obtaining the user and the corresponding first case includes: using Euclidean distance to search for the first case most similar to the user in a preset case library based on the user's medical condition information and treatment parameters; the first case represents a case that uses the same output power as the user and the output power is within a safe range.

7. The control method based on the ultrashort wave therapeutic apparatus according to claim 5, characterized in that: Collecting the temperature of the treatment site and the heart rate of the user includes: collecting the temperature through a temperature sensor and collecting the heart rate through a heart rate sensor.

8. The control method based on the ultrashort wave therapeutic apparatus according to claim 1, characterized in that: Outputting the treatment parameters so that the ultrashort wave therapeutic apparatus emits ultrashort waves corresponding to the treatment parameters includes: Taking the treatment parameters as original treatment parameters, and generating first treatment parameters and second treatment parameters based on the original treatment parameters; wherein parameters in the first treatment parameters are all smaller than parameters in the original treatment parameters, and parameters in the second treatment parameters are all larger than parameters in the original treatment parameters; Displaying the original treatment parameter, the first treatment parameter, the second treatment parameter and corresponding prompt information; In response to receiving the treatment parameters selected by the user or medical staff, the ultrashort wave therapeutic device is controlled to output the corresponding ultrashort wave.

9. The control method based on the ultrashort wave therapeutic apparatus according to claim 1, characterized in that: In response to the end of the treatment, a treatment report is generated, which includes treatment parameters, heart rate change curve, and temperature change curve.

10. A control system based on an ultrashort wave therapeutic apparatus, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a control method based on an ultrashort wave therapeutic apparatus according to any one of claims 1 to 9 is implemented.

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