Millimeter wave therapeutic instrument remote communication method and system

Abstract

The application relates to the technical field of telemedicine communication, and discloses a millimeter wave therapeutic instrument remote communication method and system. The method comprises the following steps: a secure communication channel based on equipment characteristics is established for a millimeter wave therapeutic instrument and a doctor terminal through a double verification method; treatment data of the millimeter wave therapeutic instrument are collected and segmented and marked; a copy is established for each data segment in an initial stage, and the copy generation frequency and the sending time interval are dynamically adjusted; the doctor terminal records the two-way transmission duration, predicts the future transmission duration based on historical data, and adjusts the treatment parameters in advance. Through the dynamic copy mechanism, the predictive parameter adjustment and the abnormal response strategy, the reliability, the real-time performance and the safety of the millimeter wave therapeutic instrument remote communication are significantly improved.

Description

Technical Field

[0001] This application relates to the field of telemedicine communication technology, and in particular to a telemedicine communication method and system for a millimeter-wave therapy device. Background Technology

[0002] With the development of telemedicine technology, medical devices such as millimeter-wave therapy instruments are increasingly supporting remote monitoring and parameter adjustment functions. In existing technologies, remote communication often employs retransmission mechanisms or forward error correction techniques to address issues such as network instability, packet loss, or latency. However, retransmission mechanisms significantly increase communication latency in environments with high packet loss rates, affecting treatment response speed; forward error correction techniques have limited error correction capabilities and are ill-suited to handle sudden anomalies in complex network environments. Furthermore, existing systems lack the ability to predict and adaptively adjust communication states, making it impossible to pre-adjust device parameters to avoid potential risks.

[0003] A similar prior art patent application, CN104135488A, discloses a data transmission system, method, and application for a telemedicine system. The system includes a network, a computer system, a remote central management controller, a monitor, and a camera. The patient connects the monitor's signal output to the computer's signal input at home. Using an improved UDP packet protocol, control commands are transmitted via a service center web server, enabling remote online video consultations between doctors and patients. Without extending consultation time, the patient connects the monitor to the computer at home, transmitting physiological data collected by the monitor using the improved UDP protocol.

[0004] However, this application uses traditional retransmission mechanisms to deal with network instability, packet loss, or delays when transmission errors occur, without considering that retransmission mechanisms can significantly increase communication latency and affect treatment response speed in environments with high packet loss rates.

[0005] Therefore, the present invention provides a remote communication method and system for a millimeter wave therapy device. Summary of the Invention

[0006] This application provides a remote communication method and system for millimeter wave therapy devices, which improves the reliability, real-time performance and security of remote communication for millimeter wave therapy devices.

[0007] In a first aspect, this application provides a remote communication method for a millimeter-wave therapy device, the method comprising:

[0008] A secure communication channel based on dynamic tokens and device characteristics is established for millimeter-wave therapy devices and doctor terminals through a dual authentication method.

[0009] The treatment data of the millimeter wave therapy device is collected, and multiple different treatment data segments are obtained based on the treatment data. The treatment data includes treatment parameters, device status and patient physiological feedback data. A unique data tag is configured for each treatment data segment.

[0010] In the first phase, a corresponding copy data segment is created for each data segment with data tags. The original treatment data segment and the copy data segment are sent to the doctor's terminal through a secure communication channel according to a pre-set initial time interval. During the data segment sending process, the frequency of creating the copy data segment is dynamically modified, and the time interval is also dynamically updated.

[0011] The doctor's terminal receives treatment data, records the bidirectional transmission duration of the data segment, and predicts the future bidirectional transmission duration based on multiple bidirectional transmission durations in the past time period. Based on the predicted value, the doctor adjusts the usage parameters of the millimeter wave therapy device in advance.

[0012] In conjunction with the first aspect, in the first implementation of the first aspect of this application, dynamically modifying the frequency of establishing replica data segments during the transmission of data segments includes:

[0013] A preset sliding window length is used to continuously calculate the packet loss rate within the sliding window length. When the packet loss rate is less than a first threshold, the creation of replica data segments is stopped, and only the original data segments are sent. When the packet loss rate is greater than or equal to the first threshold but less than a second threshold, for every first number of data segments generated, one data segment is randomly selected to create a corresponding replica data segment. When the packet loss rate is greater than or equal to the second threshold, for every second number of data segments generated, one data segment is randomly selected to create a corresponding replica data segment. The second number is less than the first number.

[0014] In conjunction with the first aspect, in the second implementation of the first aspect of this application, the dynamic update time interval includes:

[0015] The data packet loss rate within the most recent first time period is obtained, and the continuous average number of packet losses within the first time period is calculated. The first time period is divided by the total number of transmitted data segments within the first time period to obtain the average packet loss duration. The average packet loss duration is multiplied by the average number of packet losses to obtain the estimated total packet loss duration. The total packet loss duration is added to the preset second time period to obtain the updated time interval. Subsequently, when sending the original data segment with the replica data segment, the corresponding replica data segment is sent after the updated time interval has elapsed after sending the original data segment.

[0016] In conjunction with the first aspect, in the third implementation of the first aspect of this application, predicting the predicted value of the future bidirectional transmission duration based on multiple bidirectional transmission durations over past time periods includes:

[0017] The process involves obtaining the bidirectional transmission duration of several recently transmitted treatment data segments, exponentially smoothing the bidirectional transmission duration to obtain the average bidirectional duration, calculating the duration difference between two adjacent average bidirectional durations, inputting multiple duration differences into a multi-level filtering model for smoothing, obtaining the first-level output and the final-level output, determining an adaptive threshold based on the first-level output, comparing the final-level output with the adaptive threshold to determine the current network state, calculating the first and second predicted values, evaluating network stability based on historical network state data, and selecting different methods based on network stability to determine the predicted values ​​of future bidirectional transmission durations.

[0018] In conjunction with the first aspect, in the fourth implementation of the first aspect of this application, the final stage output is compared with an adaptive threshold to determine the current network state, including:

[0019] If the final output is greater than the adaptive threshold, it is determined to be in a changing state; if the final output is less than or equal to the adaptive threshold, it is determined to be in a stable state.

[0020] If the state is changing, obtain several recently obtained duration differences. If the duration differences exceeding the first proportion are all greater than zero, it is determined that the state is in the duration increase state. If the duration differences exceeding the first proportion are all less than zero, it is determined that the state is in the duration decrease state.

[0021] In conjunction with the first aspect, in the fifth implementation of the first aspect of this application, network stability is evaluated based on historical network state data, including:

[0022] Set corresponding state values ​​for the duration increase state, duration decrease state, and stable state, and calculate the cumulative value of historical state values;

[0023] If the current time is in a state of increasing duration, the absolute value of the difference between the first predicted value and the latest average two-way duration is used as the reference value. If the current time is in a state of decreasing duration, the absolute value of the difference between the second predicted value and the latest average two-way duration is used as the reference value. If the current time is in a stable state, zero is used as the reference value.

[0024] Different weights are assigned to the cumulative value and the reference value, and the weighted sum of the cumulative value and the reference value is calculated. The weighted sum is used as the state judgment value. If the state judgment value is greater than the preset fluctuation threshold, the network is judged to be in an unstable state; otherwise, the network is judged to be in a stable state.

[0025] In conjunction with the first aspect, in the sixth implementation of the first aspect of this application, different methods are selected based on network stability to determine the predicted value of future bidirectional transmission duration, including:

[0026] When the network is in a stable state, if the current duration is increasing, the first predicted value is used as the final predicted value; if the current duration is decreasing, the second predicted value is used as the final predicted value; if the current state is stable, the weighted moving average of the most recent average two-way durations is calculated as the final predicted value; when the network is in an unstable state, the latest average two-way duration is used as the final predicted value.

[0027] In conjunction with the first aspect, in the seventh implementation of the first aspect of this application, the secure communication channel based on dynamic tokens and device characteristics includes:

[0028] The doctor's terminal generates a first dynamic token and receives a connection request initiated by the doctor's terminal. The connection request includes the doctor's identity information and the first dynamic token. The doctor requests the security authentication center to verify the validity of the doctor's identity information and the first dynamic token. After successful verification, a one-time session initiation command is generated and sent to the millimeter-wave therapy device. The millimeter-wave therapy device generates a second dynamic token and sends its own device identifier and the second dynamic token to the security authentication center. The security authentication center verifies the device identifier and the second dynamic token. After successful verification, the doctor's terminal and the millimeter-wave therapy device negotiate a temporary session key using a key exchange protocol based on elliptic curve cryptography. Subsequent communication data between the two is encrypted and decrypted based on the temporary session key.

[0029] In conjunction with the first aspect, the eighth implementation of the first aspect of this application, the secure communication channel based on dynamic tokens and device characteristics, further includes:

[0030] Obtain the pre-stored shared key, obtain the current timestamp, divide the timestamp by the preset time step to obtain the first result value, round down the first result value to obtain the first quantity, and generate the first dynamic token based on the shared key and the first quantity using the preset key generation algorithm.

[0031] Secondly, this application provides a remote communication system for a millimeter-wave therapy device, the system comprising:

[0032] The channel establishment module is used to establish a secure communication channel between the millimeter-wave therapy device and the doctor's terminal based on dynamic tokens and device characteristics through a dual authentication method.

[0033] The data acquisition module is used to collect treatment data from the millimeter wave therapy device. Based on the treatment data, multiple different treatment data segments are obtained. The treatment data includes treatment parameters, device status, and patient physiological feedback data. A unique data tag is configured for each treatment data segment.

[0034] The data communication module is used to establish a corresponding copy data segment for each data segment with data tags in the first time phase, and send the original treatment data segment and the copy data segment to the doctor terminal through a secure communication channel according to a preset initial time interval. During the data segment transmission process, the frequency of establishing the copy data segment is dynamically modified, and the time interval is also dynamically updated.

[0035] The parameter adjustment module is used by the doctor's terminal to receive treatment data, record the bidirectional transmission duration of the data segment, and predict the future bidirectional transmission duration based on multiple bidirectional transmission durations in the past time period. Based on the predicted value, the operating parameters of the millimeter wave therapy device are adjusted in advance.

[0036] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0037] The technical solution provided in this application significantly reduces the risk of data loss and the reliance on high-latency retransmission mechanisms by dynamically adjusting the replica generation frequency based on the real-time packet loss rate and sending replicas at the optimal time. This ensures both the reliability and real-time performance of data transmission. Through multi-level filtering, state judgment, and stability assessment models, future network transmission latency is accurately predicted, and the parameters of the treatment device are adjusted in advance based on the prediction results, shifting from passive response to proactive prevention and effectively avoiding the risk of treatment interruption or poor efficacy due to network fluctuations. A dual authentication mechanism based on dynamic tokens and device hardware characteristics, combined with high-strength elliptic curve cryptography for negotiating session keys, is employed to construct end-to-end security protection from identity authentication to data transmission, effectively preventing unauthorized access and data leakage, and ensuring the security and reliability of remote medical operations. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of an embodiment of the remote communication method for a millimeter-wave therapy device in this application.

[0040] Figure 2 This is a schematic diagram of one embodiment of the remote communication system for a millimeter-wave therapy device in this application. Detailed Implementation

[0041] This application provides a remote communication method and system for a millimeter-wave therapy device. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data used can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0042] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the remote communication method for millimeter-wave therapy devices in this application includes:

[0043] Step S1: Establish a secure communication channel between the millimeter-wave therapy device and the doctor's terminal based on dynamic tokens and device characteristics using a dual authentication method.

[0044] Specifically, to ensure the security of communication between the millimeter-wave therapy device and the doctor's terminal, a secure communication channel based on dynamic tokens and device characteristics is established through a dual authentication method. The dynamic token is a temporary password that is only valid for a predetermined period of time to improve security. Device characteristics refer to unique and difficult-to-copy physical identifiers embedded in the doctor's terminal and the millimeter-wave therapy device. By establishing a secure communication channel, the security of communication between the millimeter-wave therapy device and the doctor's terminal is ensured.

[0045] Step S2: Collect treatment data from the millimeter wave therapy device. The treatment data includes treatment parameters, device status, and patient physiological feedback data. Based on the treatment data, obtain multiple different treatment data segments and assign a unique data tag to each treatment data segment.

[0046] Specifically, when the millimeter-wave therapy device and the doctor's terminal communicate, the treatment data needs to be sent to the doctor's terminal in real time so that the doctor's terminal can adjust the usage parameters of the millimeter-wave therapy device in a timely manner based on the patient's physiological feedback data. In this case, it is necessary to ensure the reliability of the treatment data sent by the millimeter-wave therapy device. However, when packet loss occurs, the traditional method of sending data ensures reliability by retransmission, but this method will significantly increase the communication latency. Although traditional error correction methods, such as forward error correction, can reduce retransmission, their error correction capability is limited. Therefore, this application proposes a remote communication method for millimeter-wave therapy devices.

[0047] First, a data acquisition module is set up inside the millimeter wave therapy device to collect the treatment data of the millimeter wave therapy device in real time. The treatment data includes treatment parameters, device status and patient physiological feedback data. In order to transmit the treatment data more quickly in the future, the treatment data is divided into multiple different treatment data segments, and each treatment data segment is also configured with a unique data tag to mark the sequence of the treatment data segment.

[0048] Step S3: During the first time period, a corresponding copy data segment is established for each treatment data segment. The original treatment data segment and the copy data segment are encrypted and sent to the doctor's terminal sequentially according to the preset initial time interval. During the data segment sending process, the frequency of establishing the copy data segment is dynamically modified, and the time interval is also dynamically updated.

[0049] Specifically, to ensure that the doctor's terminal receives treatment data quickly and completely, a corresponding copy data segment is created for each data segment with a data tag during the first time phase. The first time phase refers to the period when the millimeter-wave therapy device and the doctor's terminal just begin communicating, specifically within the first 5 minutes after the millimeter-wave therapy device is activated. A corresponding copy data segment is created for each treatment data segment, and the data tag of the original data segment is completely copied during the creation of the copy data segment. Then, the original treatment data segment is sent to the doctor's terminal first. After sending the original treatment data segment, a pre-set initial time interval is followed by the sending of the corresponding copy data segment. Sending the copy data segment ensures that retransmission is not required if the original data segment is lost. The initial time interval can be the middle of historical time intervals. The frequency of creating replica data segments is set, but during the continuous transmission of treatment data segments, if the network conditions are good, such as when the packet loss rate approaches 0, it may not be necessary to create replica data segments. Therefore, the frequency of creating replica data segments is dynamically modified during the transmission of data segments to reduce the creation of redundant replica data segments. In addition, the corresponding time interval also needs to be updated according to different network conditions. The time interval cannot be set too small, otherwise the replica data segments may still be lost under the same sudden change, such as a sudden deterioration of the network. The time interval cannot be set too large either, as it may increase the transmission time of medical data segments, which may violate the timeliness of transmitting treatment data. Therefore, the time interval is also dynamically updated to ensure that replica data segments are transmitted based on the optimal time interval.

[0050] Step S4: The doctor's terminal receives treatment data and records the bidirectional transmission duration. Based on multiple bidirectional transmission durations in the past time period, it predicts the future bidirectional transmission duration and adjusts the usage parameters of the millimeter wave therapy device in advance based on the predicted value.

[0051] Specifically, the bidirectional transmission duration refers to the transmission time from the millimeter-wave therapy device to the doctor's terminal, and then from the doctor's terminal receiving the treatment data to sending confirmation or adjustment information back to the millimeter-wave therapy device. After receiving the treatment data segment, the doctor's terminal can determine in real time whether corresponding parameter adjustments are needed. However, due to the time delay between the generation and transmission of treatment data to the doctor's terminal, and the time delay in the doctor's terminal sending adjustment information to the millimeter-wave therapy device, this delay is the bidirectional transmission duration. If the doctor's terminal always makes corresponding adjustments only after receiving the treatment data, the millimeter-wave therapy device will continue to use the previous treatment parameters during this time delay, leading to adjustment delays. To ensure the safety and effectiveness of millimeter-wave therapy and enable the doctor's terminal to make timely and accurate adjustments to treatment parameters after receiving treatment data, thereby achieving accurate treatment results, the bidirectional transmission duration is also recorded, and the predicted value of the future bidirectional transmission duration is predicted based on multiple bidirectional transmission durations over past time periods. The usage parameters of the millimeter-wave therapy device are adjusted in advance based on the predicted value. It should be noted that the treatment data mentioned in this step refers to the data segment received by the doctor's terminal, including the treatment data segment and the copy data segment.

[0052] In one specific embodiment, the frequency of establishing replica data segments is dynamically modified during the transmission of data segments, specifically including the following steps:

[0053] A preset sliding window length is used to continuously calculate the packet loss rate within the sliding window length. When the packet loss rate is less than a first threshold, the creation of replica data segments is stopped, and only the original data segments are sent. When the packet loss rate is greater than or equal to the first threshold but less than the second threshold, for every first number of treatment data segments generated, one treatment data segment is selected to create a corresponding replica data segment. When the packet loss rate is greater than or equal to the second threshold, for every second number of treatment data segments generated, one treatment data segment is selected to create a corresponding replica data segment. The second number is less than the first number.

[0054] Specifically, to maximize communication efficiency while ensuring communication reliability, the creation of replica data segments is reasonably reduced based on network conditions. First, a sliding window length is preset, for example, to send 1000 medical data segments. Within the nearest sliding window length, the packet loss rate is calculated, for example, with a first threshold of 1%. If the packet loss rate is less than the first threshold, it indicates a very low packet loss rate. In this case, creating replica data segments is unnecessary and would increase communication load; therefore, the creation of replica data segments is stopped. For example, a second threshold is set to 5%. If the packet loss rate is greater than or equal to the first threshold but less than the second threshold, the packet loss rate increases slightly. In the case of sending 1000 medical data segments, there might be 50 data losses. Therefore, after generating a first number of data segments, from... A data segment is selected from the data segments to create a corresponding replica data segment. Based on historically lost data segments, the treatment data segment most likely to be lost in the 50th treatment data segment is selected, and a replica data segment is created for transmission. If the packet loss rate is greater than or equal to the second threshold, the packet loss rate increases again, and more than 50 losses may occur when sending 1000 medical data segments. Therefore, the frequency of creating replica treatment data segments is increased. For every two numbers of treatment data segments generated, one treatment data segment is selected to create a corresponding replica data segment, where the second number is less than the first number. This ensures that even if a treatment data segment is lost during transmission, the corresponding data can be obtained based on the corresponding replica data segment, reducing data retransmission and improving the reliability and efficiency of data transmission.

[0055] In one specific embodiment, dynamically updating the time interval specifically includes the following steps:

[0056] The data packet loss rate within the most recent first time period is obtained, and the continuous average number of packet losses within the first time period is calculated. The first time period is divided by the total number of transmitted data segments within the first time period to obtain the average packet loss duration. The average packet loss duration is multiplied by the average number of packet losses to obtain the estimated total packet loss duration. The total packet loss duration is added to the preset second time period to obtain the updated time interval.

[0057] Specifically, because the network environment is constantly changing, different network environments require different time intervals. To obtain the optimal time interval, ensure that the replica data segments provide the necessary supplementation, and guarantee that the doctor's terminal can obtain treatment data in a timely manner, we first obtain the packet loss rate of the most recent first time interval. For example, if 2000 data packets were sent in the last 2 seconds, we calculate the packet loss rate of those 2000 data packets. Then, we calculate the average number of consecutive packet losses within those 2 seconds. For instance, if 10 data losses occurred during the sending of 2000 data packets, with losses of 2, 5, 8, 3, 1, 9, 7, 5, 4, and 6 packets respectively, for a total loss of 50 data packets, the average number of consecutive packet losses would be 50 / 10 = 5. Therefore, the average number of packet losses is 5. Since it's 2 seconds, we divide 2 by the total number of transmissions, 2000, to get 0.001. 0.001 is the average packet loss duration, representing the average duration of each packet loss within 2 seconds. Then, we multiply the average packet loss duration by the average number of packet losses, 5, to get 0.005 as the estimated total packet loss duration. The calculated total packet loss duration is 5 milliseconds. To leave sufficient margin for the replica data segment and ensure that the replica data segment can truly jump to a better network state, we add a preset second duration, such as 1 millisecond, to the total packet loss duration to get the updated time interval. Subsequently, after sending the original data segment containing the replica data segment, we wait for the updated time interval before sending the corresponding replica data segment. Through the above method, the replica data segment can achieve the purpose of supplementing the lost original data segment as much as possible.

[0058] It should be noted that while this method can minimize the retransmission of lost data segments, it cannot completely eliminate retransmission. There may be cases where some data segments are lost but no replica data segments have been created, or cases where some data segments are lost and the created replica data segments are also lost. In these cases, it is still necessary to retransmit the lost original data segments.

[0059] In one specific embodiment, predicting the future bidirectional transmission duration based on multiple bidirectional transmission durations over past time periods includes the following steps:

[0060] The process involves obtaining the bidirectional transmission duration of several recently transmitted treatment data segments, exponentially smoothing the bidirectional transmission duration to obtain the average bidirectional duration, calculating the duration difference between two adjacent average bidirectional durations, inputting multiple duration differences into a multi-level filtering model for smoothing, obtaining the first-level output and the final-level output, determining an adaptive threshold based on the first-level output, comparing the final-level output with the adaptive threshold to determine the current network state, calculating the first and second predicted values, evaluating network stability based on historical network state data, and selecting different methods based on network stability to determine the predicted values ​​of future bidirectional transmission durations.

[0061] Specifically, a multi-stage filtering model refers to a multi-stage Kalman filter. Multiple duration differences are input into the multi-stage filtering model for smoothing. Through multi-stage processing, the trend of the duration differences is identified, determining whether it is continuously increasing, continuously decreasing, or trending towards stability. For example, six consecutive average bidirectional durations are 100ms, 105ms, 110ms, 108ms, 111ms, and 115ms, corresponding to duration differences of 5, 5, -2, 3, and 4. Different parameters are set for each stage of the multi-stage Kalman filter model, and the input of each stage is used as the output of the next stage. Inputting multiple duration differences into the multi-stage Kalman filter model yields the first-stage output. Assuming the first-stage output is 2.88, it reflects the trend estimate of the current network state, representing the short-term trend estimate of the duration differences, i.e., the direction of network latency change. An adaptive threshold is determined based on the first-stage output; for example, an allowable trend offset coefficient of 1.2 is set. Multiplying the first-stage output by the offset coefficient yields 3.46. The adaptive threshold is adjusted based on real-time filtering results to prevent the fixed threshold from failing during network fluctuations. The first-stage filtering has already reduced the impact of noise, allowing the adaptive threshold to reflect the true network change boundary. The final output is a high-precision state estimate obtained after multiple stages of filtering. It is a stable trend value that excludes the influence of short-term fluctuations and provides the final optimized state estimate for comparison with the adaptive threshold to determine the network state. Assuming the final output is 3.48, which is greater than the adaptive threshold of 3.46, if the final output is greater than the adaptive threshold, it indicates that the trend change has significantly deviated from the baseline level. Therefore, it is determined that the state is in a state of increasing or decreasing duration. Further, it can be determined whether it is in a state of increasing or decreasing duration based on the duration difference. If the final output is less than the adaptive threshold, it indicates that the trend change has not exceeded the baseline fluctuation range. Therefore, the current network state is a stable state. Note that the network state determined at this time is the network state at this specific moment.

[0062] In one specific embodiment, the final stage output is compared with an adaptive threshold to determine the current network state, which specifically includes the following steps:

[0063] If the final output is greater than the adaptive threshold, it is determined to be in a changing state; if the final output is less than or equal to the adaptive threshold, it is determined to be in a stable state.

[0064] If the state is changing, obtain several recently obtained duration differences. If the duration differences exceeding the first proportion are all greater than zero, it is determined that the state is in the duration increase state. If the duration differences exceeding the first proportion are all less than zero, it is determined that the state is in the duration decrease state.

[0065] Specifically, assuming the final output is 3.48, which is greater than the adaptive threshold of 3.46, if the final output is greater than the adaptive threshold, it indicates that the trend change has significantly deviated from the baseline level. Therefore, the network is judged to be in a state of increasing or decreasing duration. If most of the recent duration differences are greater than 0, it means that the average bidirectional duration is increasing, and the current network state is judged to be in a state of increasing duration. If the final output is greater than the adaptive threshold and most of the recent duration differences are less than 0, it means that the average bidirectional duration is decreasing, and the current network state is judged to be in a state of decreasing duration. If the final output is less than or equal to the adaptive threshold, it means that the trend change has not exceeded the baseline fluctuation range, and the current network state is a stable state.

[0066] In one specific embodiment, assessing network stability based on historical network state data includes the following steps:

[0067] Set corresponding state values ​​for the duration increase state, duration decrease state, and stable state, and calculate the cumulative value of historical state values;

[0068] If the current time is in a state of increasing duration, the absolute value of the difference between the first predicted value and the latest average two-way duration is used as the reference value. If the current time is in a state of decreasing duration, the absolute value of the difference between the second predicted value and the latest average two-way duration is used as the reference value. If the current time is in a stable state, zero is used as the reference value.

[0069] Different weights are assigned to the cumulative value and the reference value, and the weighted sum of the cumulative value and the reference value is calculated. The weighted sum is used as the state judgment value. If the state judgment value is greater than the preset fluctuation threshold, the network is judged to be in an unstable state; otherwise, the network is judged to be in a stable state.

[0070] Specifically, corresponding state values ​​are assigned to the duration increase state, duration decrease state, and stable state, and the cumulative value of historical state values ​​is calculated. For example, the state value for the duration increase state is set to 1, the state value for the duration decrease state is set to -1, and the state value for the stable state is set to 0. First, the cumulative value of the number of times the duration increase state or duration decrease state is counted. If the network is in a continuous duration increase state, more severe bidirectional transmission duration may occur in the future. Therefore, when the duration increase state occurs continuously, a first prediction value is obtained. The first prediction value is the deterioration prediction value, which represents the more severe bidirectional transmission duration that the network will experience in the future. The latest bidirectional transmission duration is obtained, and the difference between the deterioration prediction value and the latest bidirectional transmission duration is calculated. The absolute value of the value is used as a reference value. When the network is in a state of continuous increase in duration, the reference value represents the distance between the current bidirectional transmission duration and the predicted value of severe future deterioration. The larger the distance, the more likely the network will change in the future. At the same time, if the network state is also in a state of continuous increase in duration (with a large cumulative value of the number of times), it indicates that the network state will also change in the future. Different weights are set for the cumulative value of the number of times and the reference value, such as 0.3 and 0.7 respectively. The weighted sum of the cumulative value and the reference value is used as the state judgment value. The larger the state judgment value, the more unstable the network is. If the state judgment value is greater than the preset fluctuation threshold, the network is judged to be in an unstable state; otherwise, the network is judged to be in a stable state.

[0071] Similarly, if the network is in a state of continuous duration reduction, there is a possibility of even lower bidirectional transmission duration in the future. Therefore, when the duration reduction and increase states occur consecutively, a second predicted value is obtained. The second predicted value is the improved predicted value, which represents the lower bidirectional transmission duration that the network will experience in the future. The absolute value of the difference between the improved predicted value and the latest bidirectional transmission duration is also calculated and used as a reference value. This reference value represents the distance between the current bidirectional transmission duration and the lower improved predicted value in the future. The larger the distance, the more likely the network will continue to change in the future. At the same time, if the network state is in a state of continuous duration reduction, it also indicates that the network state will change in the future. Therefore, different weights are set for the cumulative value and the reference value, such as 0.3 and 0.7 respectively. The weighted sum of the cumulative value and the reference value is used as the state judgment value. The larger the state judgment value, the more unstable the network is. If the state judgment value is greater than the preset fluctuation threshold, the network is judged to be in an unstable state; otherwise, the network is judged to be in a stable state.

[0072] When the network is in a stable state, the reference value is set to zero in order to make the final calculated state judgment value small enough.

[0073] In one specific embodiment, different methods are selected based on network stability to determine the predicted value of future bidirectional transmission duration, specifically including the following steps:

[0074] When the network is in a stable state, if the current duration is increasing, the first predicted value is used as the final predicted value; if the current duration is decreasing, the second predicted value is used as the final predicted value; if the current state is stable, the weighted moving average of the most recent average two-way durations is calculated as the final predicted value; when the network is in an unstable state, the latest average two-way duration is used as the final predicted value.

[0075] Specifically, when the network is in a stable state, there are three scenarios: When the duration is increasing, since the network is stable, the increase in bidirectional transmission duration is roughly the same each time, indicating a potentially larger bidirectional transmission duration in the future. Therefore, the first predicted value is used as the final predicted value. The first predicted value is the deterioration predicted value, representing a more severe bidirectional transmission duration in the future. When the duration is decreasing, since the network is stable, the decrease in bidirectional transmission duration is roughly the same each time, indicating a potentially smaller bidirectional transmission duration in the future. Therefore, the second predicted value is used as the final predicted value. The second predicted value is the improvement predicted value, representing a lower bidirectional transmission duration in the future. If the current state is stable, it means the average bidirectional transmission duration does not show a significant trend. Therefore, several past average bidirectional transmission durations are assigned exponential decay weights and weighted summed to obtain the final predicted value. If the network is unstable, it means historical trends are unreliable. Therefore, the real-time average bidirectional transmission duration is directly used as the final predicted value to avoid prediction lag.

[0076] Further, the first predicted value is calculated, including:

[0077] Collect several average two-way durations from the past, calculate the corresponding mean and standard deviation, construct a normal probability distribution based on the mean and standard deviation, take the value of the first quantile in the normal probability distribution as the first predicted value, and take the value of the second quantile in the normal probability distribution as the second predicted value.

[0078] Specifically, several past average two-way durations are collected, and their corresponding mean and standard deviation are calculated. A normal probability distribution is constructed based on the mean and standard deviation. The value of the first quantile in the normal probability distribution is taken as the first predicted value. For example, the value of the 95th quantile is taken as the first predicted value. The 95th quantile means that 95% of the data is less than or equal to this value. If the mean of several past average two-way durations is 100ms and the standard deviation is 10ms, then the value corresponding to 95% is 100 + 1.645. 10 = 116.45ms, so 116.45 is the first predicted value. If the duration continues to increase, the 95th percentile is taken as the extreme predicted duration (the first predicted value) to reserve resources in advance. If the second quantile is the value corresponding to the 5th percentile, then the second predicted value is 100 - 1.645. 10 = 83.55. If the duration continues to decrease, the 5th percentile is taken as the lowest predicted duration (second predicted value) to achieve the goal of optimizing resource allocation.

[0079] In one specific embodiment, establishing a secure communication channel based on dynamic tokens and device characteristics includes the following steps:

[0080] The doctor's terminal generates a first dynamic token and receives a connection request initiated by the doctor's terminal. The connection request includes the doctor's identity information and the first dynamic token. The doctor requests the security authentication center to verify the validity of the doctor's identity information and the first dynamic token. After successful verification, a one-time session initiation command is generated and sent to the millimeter-wave therapy device. The millimeter-wave therapy device generates a second dynamic token and sends its own device identifier and the second dynamic token to the security authentication center. The security authentication center verifies the device identifier and the second dynamic token. After successful verification, the doctor's terminal and the millimeter-wave therapy device negotiate a temporary session key using a key exchange protocol based on elliptic curve cryptography. Subsequent communication data between the two is encrypted and decrypted based on the temporary session key.

[0081] Specifically, to establish a secure communication channel, the millimeter-wave therapy device first receives a connection request initiated by the doctor's terminal. The connection request includes the doctor's identification information, which refers to the unique identification information of the doctor operating the doctor's terminal. After receiving the connection request, the millimeter-wave therapy device verifies the validity of the doctor's identification information with the security authentication center. After successful verification, the security authentication center generates a one-time session initiation command and sends it to the millimeter-wave therapy device. After receiving the session initiation command, the millimeter-wave therapy device sends its own device identifier to the security authentication center, which verifies the device identifier. After successful verification, a secure communication channel is established between the doctor's terminal and the millimeter-wave therapy device.

[0082] The security authentication center obtains a pre-stored shared key bound to the doctor's identity information. Based on the shared key and timestamp, it generates an expected first token using the same method as generating the first dynamic token on the doctor's terminal. The received first dynamic token and the expected first token are matched. If the match is successful, the verification is considered successful. When verifying the second dynamic token, the center obtains a pre-stored shared key bound to the device identifier. Based on the shared key and timestamp, it generates an expected second token using the same method as generating the second dynamic token on the millimeter wave therapy device. The received second dynamic token and the expected second token are matched. If the match is successful, the verification is considered successful.

[0083] In one specific embodiment, the doctor's terminal generates a first dynamic token and also performs the following steps:

[0084] Obtain the pre-stored shared key, obtain the current timestamp, divide the timestamp by the preset time step to obtain the first result value, round down the first result value to obtain the first quantity, and generate the first dynamic token based on the shared key and the first quantity using the preset key generation algorithm.

[0085] Specifically, the process involves obtaining the pre-stored shared key and the current timestamp. Dividing the timestamp by a preset time step yields the first result value. Assuming the timestamp is in milliseconds and the time step is 500, this means the first result value will remain unchanged for the next 500ms. Therefore, the security authentication center will receive the same first result value within 500ms. Based on the same key generation algorithm and shared key, this ensures that the security authentication center and the doctor's terminal generate the same token. If the first dynamic token is tampered with or intercepted during transmission, the security authentication center may not receive it within 500ms. In this case, the security authentication center cannot generate the same expected dynamic token as the doctor's terminal, resulting in verification failure. Similarly, the principle for verifying the second dynamic token is the same.

[0086] When verifying the first dynamic token, the security authentication center looks up the shared key corresponding to the doctor's identifier in the database, reads the current timestamp, divides the current timestamp by a preset time step, and rounds the result down to obtain the expected first quantity. The time step is negotiated in advance between the security authentication center and the doctor's terminal. Based on the shared key and the expected first quantity, the same key generation algorithm, such as the TOTP algorithm, is used to generate the expected first token. The method for verifying the second dynamic token is the same as the method for verifying the first dynamic token.

[0087] The method by which the millimeter wave therapy device generates the second dynamic token is the same as the method by which the doctor's terminal generates the first dynamic token.

[0088] The above describes the remote communication method of the millimeter-wave therapy device in the embodiments of this application. The following describes the remote communication system of the millimeter-wave therapy device in the embodiments of this application. Please refer to [link / reference]. Figure 2 One embodiment of the millimeter-wave therapy device remote communication system in this application includes:

[0089] The data acquisition module is used to collect treatment data from the millimeter wave therapy device. The treatment data includes treatment parameters, device status, and patient physiological feedback data. Based on the treatment data, multiple different treatment data segments are obtained, and a unique data tag is assigned to each treatment data segment.

[0090] The data communication module is used to establish a corresponding copy data segment for each treatment data segment in the first time stage, encrypt the original treatment data segment and the copy data segment and send them to the doctor's terminal in sequence according to the pre-set initial time interval. During the data segment sending process, the frequency of establishing the copy data segment is dynamically modified, and the time interval is also dynamically updated.

[0091] The parameter adjustment module is used to record the bidirectional transmission duration and predict the future bidirectional transmission duration based on multiple bidirectional transmission durations in the past time period, and adjust the usage parameters of the millimeter wave therapy device in advance based on the predicted value.

[0092] The anomaly monitoring module is used to collect communication data between the millimeter-wave therapy device and the doctor's terminal during the interaction between the two, perform anomaly detection based on the communication data, and take different countermeasures for different anomalies when an anomaly is detected.

[0093] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0094] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0095] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A remote communication method for a millimeter-wave therapy device, characterized in that, The method includes: A secure communication channel based on device characteristics is established between millimeter-wave therapy devices and doctor terminals through a dual-authentication method. The treatment data of the millimeter wave therapy device is collected, and multiple different treatment data segments are obtained based on the treatment data. The treatment data includes treatment parameters, device status and patient physiological feedback data. A unique data tag is configured for each treatment data segment. In the first phase, a corresponding copy data segment is created for each data segment with data tags. The original treatment data segment and the copy data segment are sent to the doctor's terminal through a secure communication channel according to a pre-set initial time interval. During the data segment sending process, the frequency of creating the copy data segment is dynamically modified, and the time interval is also dynamically updated. The doctor's terminal receives treatment data, records the bidirectional transmission duration of data segments, and predicts future bidirectional transmission durations based on multiple bidirectional transmission durations over past time periods. This includes: acquiring the bidirectional transmission durations of several recently transmitted treatment data segments; performing exponential smoothing on the bidirectional transmission durations to obtain the average bidirectional duration; calculating the duration difference between two adjacent average bidirectional durations; inputting multiple duration differences into a multi-level filtering model for smoothing to obtain the first-level output and the final-level output; determining an adaptive threshold based on the first-level output; comparing the final-level output with the adaptive threshold to determine the current network state; calculating the first and second predicted values; evaluating network stability based on historical network state data; and selecting different methods based on network stability to determine the predicted values ​​of future bidirectional transmission durations. The first predicted value is a deterioration prediction, indicating a more severe bidirectional transmission duration in the future; the second predicted value is an improvement prediction, indicating a lower bidirectional transmission duration in the future. The operating parameters of the millimeter-wave therapy device are adjusted in advance based on the predicted values.

2. The method according to claim 1, characterized in that, The frequency of creating replica data segments can be dynamically modified during the transmission of data segments, including: A preset sliding window length is used to continuously calculate the packet loss rate within the sliding window length. When the packet loss rate is less than a first threshold, the creation of replica data segments is stopped, and only the original data segments are sent. When the packet loss rate is greater than or equal to the first threshold but less than a second threshold, for every first number of data segments generated, one data segment is randomly selected to create a corresponding replica data segment. When the packet loss rate is greater than or equal to the second threshold, for every second number of data segments generated, one data segment is randomly selected to create a corresponding replica data segment. The second number is less than the first number.

3. The method according to claim 1, characterized in that, Dynamic update time intervals include: The data packet loss rate within the most recent first time period is obtained, and the continuous average number of packet losses within the first time period is calculated. The first time period is divided by the total number of transmitted data segments within the first time period to obtain the average packet loss duration. The average packet loss duration is multiplied by the average number of packet losses to obtain the estimated total packet loss duration. The total packet loss duration is added to the preset second time period to obtain the updated time interval. Subsequently, when sending the original data segment with the replica data segment, the corresponding replica data segment is sent after the updated time interval has elapsed after sending the original data segment.

4. The method according to claim 1, characterized in that, The final output is compared with an adaptive threshold to determine the current network state, including: If the final output is greater than the adaptive threshold, it is determined to be in a changing state; if the final output is less than or equal to the adaptive threshold, it is determined to be in a stable state. If the state is changing, obtain several recently obtained duration differences. If the duration differences exceeding the first proportion are all greater than zero, it is determined that the state is in the duration increase state. If the duration differences exceeding the first proportion are all less than zero, it is determined that the state is in the duration decrease state.

5. The method according to claim 1, characterized in that, Network stability is assessed based on historical network state data, including: Set corresponding state values ​​for the duration increase state, duration decrease state, and stable state, and calculate the cumulative value of historical state values; If the current time is in a state of increasing duration, the absolute value of the difference between the first predicted value and the latest average two-way duration is used as the reference value. If the current time is in a state of decreasing duration, the absolute value of the difference between the second predicted value and the latest average two-way duration is used as the reference value. If the current time is in a stable state, zero is used as the reference value. Different weights are assigned to the cumulative value and the reference value, and the weighted sum of the cumulative value and the reference value is calculated. The weighted sum is used as the state judgment value. If the state judgment value is greater than the preset fluctuation threshold, the network is judged to be in an unstable state; otherwise, the network is judged to be in a stable state.

6. The method according to claim 1, characterized in that, Different methods are selected based on network stability to determine the predicted values ​​of future bidirectional transmission durations, including: When the network is in a stable state, if the current duration is increasing, the first predicted value is used as the final predicted value; if the current duration is decreasing, the second predicted value is used as the final predicted value; if the current state is stable, the weighted moving average of the most recent average two-way durations is calculated as the final predicted value; when the network is in an unstable state, the latest average two-way duration is used as the final predicted value.

7. The method according to claim 1, characterized in that, Establish a secure communication channel based on dynamic tokens and device characteristics, including: The doctor's terminal generates a first dynamic token and receives a connection request initiated by the doctor's terminal. The connection request includes the doctor's identity information and the first dynamic token. The doctor requests the security authentication center to verify the validity of the doctor's identity information and the first dynamic token. After successful verification, a one-time session initiation command is generated and sent to the millimeter-wave therapy device. The millimeter-wave therapy device generates a second dynamic token and sends its own device identifier and the second dynamic token to the security authentication center. The security authentication center verifies the device identifier and the second dynamic token. After successful verification, the doctor's terminal and the millimeter-wave therapy device negotiate a temporary session key using a key exchange protocol based on elliptic curve cryptography. Subsequent communication data between the two is encrypted and decrypted based on the temporary session key.

8. The method according to claim 1, characterized in that, The doctor's terminal generates the first dynamic token, which also includes: Obtain the pre-stored shared key, obtain the current timestamp, divide the timestamp by the preset time step to obtain the first result value, round down the first result value to obtain the first quantity, and generate the first dynamic token based on the shared key and the first quantity using the preset key generation algorithm.

9. A remote communication system for a millimeter-wave therapy device, used to implement the remote communication method for a millimeter-wave therapy device as described in any one of claims 1-8, characterized in that, The system includes: The channel establishment module is used to establish a secure communication channel between the millimeter-wave therapy device and the doctor's terminal based on dynamic tokens and device characteristics through a dual authentication method. The data acquisition module is used to collect treatment data from the millimeter wave therapy device. Based on the treatment data, multiple different treatment data segments are obtained. The treatment data includes treatment parameters, device status, and patient physiological feedback data. A unique data tag is configured for each treatment data segment. The data communication module is used to establish a corresponding copy data segment for each data segment with data tags in the first time phase, and send the original treatment data segment and the copy data segment to the doctor terminal through a secure communication channel according to a preset initial time interval. During the data segment transmission process, the frequency of establishing the copy data segment is dynamically modified, and the time interval is also dynamically updated. The parameter adjustment module is used by the doctor's terminal to receive treatment data, record the bidirectional transmission duration of the data segment, and predict the future bidirectional transmission duration based on multiple bidirectional transmission durations in the past time period. Based on the predicted value, the operating parameters of the millimeter wave therapy device are adjusted in advance.

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