Dynamic interference cooperative communication optimization system and method for hierarchical medical scene

Abstract

The invention provides a hierarchical medical scene-oriented dynamic interference cooperative communication optimization system and method, and relates to the technical field of medical data communication security. The hierarchical medical scene-oriented dynamic interference cooperative communication optimization method comprises the following steps: S1, based on hierarchical medical scene differences of emergency treatment, ICU and common wards, realizing covert communication by using native physiological data transmission mutual interference signals of multiple devices in a medical monitoring network; s2, different communication security thresholds and data timeliness indexes are set for different levels of scenes; and S3, constructing a dynamic interference coordination framework, and realizing interference intensity adaptation by adjusting the transmission power (Pi) of the medical equipment and the dedicated channel gain (hj, iva). According to the invention, through linkage with the HIS system, differentiated safety thresholds and timeliness indexes are set for emergency treatment, ICU and common wards, and priority requirements of different scenes are accurately met; parameter synchronization can be rapidly completed during cross-scene transfer, and the problem of connection lag of a traditional scheme is solved.

Description

Technical Field

[0001] This invention relates to the field of medical data communication security technology, specifically to a dynamic interference collaborative communication optimization system and method for hierarchical medical scenarios. Background Technology

[0002] In the healthcare field, with the development of technologies such as the Internet of Things (IoT) and 5G, medical monitoring systems increasingly rely on wireless communication to achieve real-time transmission and remote monitoring of patients' physiological data. For example, vital signs data such as heart rate, blood pressure, and blood oxygen saturation need to be uploaded to a central monitoring system in real time to provide a basis for clinical diagnosis and emergency decision-making. However, current medical communication technologies still have the following problems in terms of security, real-time performance, and scenario adaptability: 1. Shortcomings exist in the protection of patient data privacy. Traditional medical communications primarily rely on encryption algorithms (such as AES and RSA) to ensure data privacy. However, encryption technology can only prevent data content from being cracked; it cannot hide the communication behavior of devices (such as transmission frequency and link characteristics). Attackers can locate target devices and intercept them by detecting communication behavior. Furthermore, the encryption and decryption process increases data transmission latency, making it difficult to meet the real-time requirements of vital sign data in emergency scenarios.

[0003] 2. Balancing timeliness and safety is difficult in medical settings. While covert communication technologies commonly used in the Industrial Internet of Things (IIoT) (such as additional jamming modules) can improve communication security, medical devices have stringent requirements for electromagnetic compatibility (e.g., the noise amplification of ECG signals must be ≤5μV). Additional interference can easily lead to measurement errors in devices such as monitors. At the same time, the "one-size-fits-all" interference strategy in industrial scenarios cannot adapt to the tiered requirements of medical scenarios (e.g., the difference in data freshness requirements between emergency rooms and general wards), which may cause delays in critical data transmission or waste of resources.

[0004] 3. Interference and conflicts exist in multi-device collaborative communication. In hospital settings, devices such as monitors, ventilators, and infusion pumps are densely deployed. Traditional communication solutions lack differentiated management of device priorities, which can easily lead to non-critical devices (such as bedside terminals) occupying channel resources, causing interference to the signal links of critical devices (such as defibrillators and ventilators), reducing the signal-to-interference-plus-noise ratio (SINR), and affecting the reliability of data transmission.

[0005] 4. Insufficient cross-scenario adaptability When patients are transferred between the emergency room, ICU, and general ward, traditional communication systems require manual reconfiguration of equipment parameters (such as transmission power and safety thresholds). The switching process is time-consuming (usually >30 seconds) and prone to data interruption due to parameter mismatch, which does not meet the clinical requirements for continuous patient monitoring. At the same time, existing technologies cannot meet the differentiated needs of "privacy-timeliness" in different scenarios (such as the need for extreme real-time performance in the emergency room, while general wards focus more on resource conservation).

[0006] 5. The system has limitations in robustness and compliance. Many existing medical communication solutions lack defense mechanisms for extreme attack scenarios (such as close-range interception and channel sniffing). When unauthorized devices are located at the optimal interception location, such as the hospital network boundary, the detection error rate drops significantly. Furthermore, some solutions have not passed medical electromagnetic compatibility certification, and the electromagnetic interference generated by device communication may affect the measurement accuracy of precision medical devices such as ECG monitors, which does not meet the requirements of HIPAA and other regulations for patient data privacy and medical device security.

[0007] Therefore, there is an urgent need for a communication security solution that can adapt to the tiered medical care scenario, balance data privacy protection and real-time requirements, and has the ability to cooperate and resist interference with multiple devices, so as to solve the limitations of existing technologies in medical monitoring systems. Summary of the Invention

[0008] Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a dynamic interference collaborative communication optimization system and method for hierarchical medical scenarios, which solves the problem of limitations in the application of existing technologies in medical monitoring systems.

[0009] Technical solution To achieve the above objectives, the present invention provides the following technical solution: a dynamic interference-coordinated communication optimization method for hierarchical medical scenarios, the method comprising the following: S1. Based on the differences in the hierarchical medical scenarios of emergency, ICU and general ward, covert communication is achieved by utilizing the mutual interference signals of the native physiological data transmission of multiple devices in the medical monitoring network. The mutual interference signals are the electromagnetic interference generated by the monitors and ventilators when transmitting hierarchical physiological data. The interference intensity is dynamically adjusted according to the scenario level. S2. Set differentiated communication security thresholds and data timeliness indicators for different levels of scenarios, including: Safety threshold: Quantified by the detection error rate (η_i) of unauthorized devices, with sensitive data in emergency / ICU scenarios η_i≥0.95 and routine data in general wards η_i≥0.8; Timeliness indicators: quantified by Information Age (AoI), with AoI ≤ 50ms in emergency scenarios, ≤ 100ms in ICU scenarios, and ≤ 300ms in general wards; S3. Construct a dynamic interference coordination framework. By adjusting the transmission power (P_i) of medical devices and the gain of dedicated channels (h_j, i^va), the interference intensity is adapted so that the interference signal meets the graded safety threshold and ensures that the signal-to-interference-plus-noise ratio of the target link is not lower than the minimum requirement of the graded scenario. No additional interference generation module is required, which solves the contradiction between privacy protection and real-time data transmission in medical scenarios.

[0010] Preferably, the safety threshold and timeliness index of the tiered medical care scenario are correlated in the following ways: The time-varying expression for the detection error rate is derived from the contextualized data access rate (ω_i) of medical devices: η_i = α_i + β_i; Among them, α_i=p(D_i 1 |Ω_i 0 (1-ω_i) represents the probability of misjudging an unauthorized device when the device does not transmit; β_i=p(D_i 0 |Ω_i 1 ω_i represents the probability of misidentification as an unauthorized device during transmission; ω_i is dynamically set according to the scenario level: ω_i≥0.9 in emergency scenarios, ω_i=0.7-0.9 in ICU scenarios, and ω_i=0.5-0.7 in general wards, and β_i is constrained to ≤0.05 in emergency / ICU scenarios.

[0011] Preferably, the control logic of the dynamic interference coordination framework includes: 1) Scene level recognition: The hospital information system is used to obtain the real-time scenario level and trigger corresponding security and timeliness parameters. 2) Dynamic allocation of interference intensity: For critical equipment such as emergency defibrillators and ICU ventilators, a higher interference contribution weight is assigned, and their transmission power adjustment has the highest priority. For non-critical equipment in general wards, the interference contribution weight should be limited to ≤30% to avoid excessive occupation of channel resources; 3) Power-interference coordinated regulation: Under the premise of meeting the graded SINR threshold, the transmission power is optimized through an iterative algorithm to keep η_i above the graded safety threshold while minimizing AoI.

[0012] Preferably, it also includes a worst-case security scenario response mechanism for tiered scenarios: The worst detection scenario for the hierarchical scenario is defined as: 1) Emergency scenario: An unauthorized device is located within 10 meters of the emergency room and attempts to intercept communication between the defibrillator and the central monitoring system; 2) ICU scenario: Unauthorized devices access the ICU's dedicated Wi-Fi channel, attempting to sniff out physiological data transmitted synchronously by multiple devices; 3) In a general ward scenario: Unauthorized devices interfere with unencrypted routine vital signs data via Bluetooth broadcasts. In the above scenarios, the system automatically increases the interference redundancy of the corresponding scenario and switches to anti-interference modulation mode.

[0013] Preferably, the timeliness optimization is achieved through an iterative algorithm for hierarchical scenario adaptation, and the steps include: 1) For emergency scenarios, an improved Dinkelbach algorithm with accelerated convergence is adopted, and the iteration step size of the Lagrange multiplier (ζ_i) is set to 2-3 times the normal value to ensure that AoI converges within 50ms; 2) For the ICU scenario, a power-access rate dual-variable coupled iteration is adopted to prioritize the balance of timeliness when multiple devices transmit synchronously; 3) For general ward scenarios, a low-complexity suboptimal algorithm is adopted to reduce the consumption of computing resources while ensuring AoI ≤ 300ms; All algorithms incorporate a scene level recognition module and optimize strategies based on real-time scene switching.

[0014] A dynamic interference-coordinated communication optimization system for tiered medical care scenarios, the optimization system comprising: Multiple tiered medical monitoring devices are configured as follows: Emergency area: Deploy defibrillators and bedside monitors, supporting high-frequency physiological data transmission, with native transmission interference intensity adjustable from -50 to -30 dBm; ICU area: Deploy ventilators and infusion pumps, support simultaneous transmission of multiple devices, and the mutual interference intensity is adjustable from -55 to -35dBm; General wards: Deploy routine vital sign monitoring equipment with a transmission frequency ≤50Hz and an adjustable mutual interference intensity range of -60 to -40dBm; Collaborative control unit, built-in: Scene level recognition module: In conjunction with the HIS system, it obtains scene level and patient condition tags in real time; Dynamic interference scheduling module: Assigns interference contribution weights to each device according to the scenario level and generates power adjustment commands; The graded safety monitoring module calculates the detection error rate (η_i) in different scenarios in real time to ensure that the graded safety threshold is met. Timeliness optimization module: Runs corresponding optimization algorithms for different scenarios to dynamically adjust the data transmission cycle and retransmission strategy; The system achieves a quantitative balance between communication security and timeliness in tiered scenarios through the collaborative scheduling of native interference between medical devices.

[0015] Preferably, the dynamic interference scheduling module is configured as follows: Establish an interference contribution matrix to record the interference weight of each device in different scenarios; When cross-scene device movement is detected, its interference weight is automatically adjusted to the adaptation range of the target scene; When interference conflicts occur, a priority arbitration mechanism is triggered to prioritize the interference adjustment authority of critical equipment.

[0016] Preferably, the graded safety monitoring module is configured as follows: Built-in HIPAA compliance verification rules automatically raise the η_i threshold to ≥0.98 for sensitive data related to HIV and mental illness. The system monitors the detection behavior of unauthorized devices in real time, and triggers an interference enhancement mode when the detection frequency exceeds the threshold of the tiered scenario.

[0017] Preferably, it also includes a cross-scenario collaboration interface, configured as follows: When patients are transferred between different scenarios, historical communication parameters are synchronously transmitted to the collaborative control unit of the target scenario; It supports data interaction with hospital electronic health record systems and dynamically adjusts security policies for corresponding scenarios based on the privacy level tags in the patient's medical records.

[0018] Beneficial effects This invention provides a dynamic interference-based collaborative communication optimization system and method for tiered medical scenarios. It offers the following advantages: This invention, by linking with the HIS system, sets differentiated safety thresholds and timeliness indicators for emergency rooms, ICUs, and general wards, accurately meeting the priority requirements of different scenarios; when transferring patients across scenarios, parameter synchronization can be completed quickly, solving the problem of lagging connection in traditional solutions.

[0019] This invention utilizes the native mutual interference of medical devices to achieve covert communication without the need for additional interference hardware, simplifying the system architecture; by dynamically allocating the interference contribution weight of devices, it avoids interference conflicts between multiple devices and ensures the communication reliability of critical links.

[0020] This invention provides tiered control over the error rate of unauthorized device detection, incorporates compliance verification with medical privacy regulations to enhance the adaptability of privacy protection, and adapts and optimizes algorithms for different scenarios to balance communication security and data timeliness, thus meeting the real-time requirements of medical monitoring.

[0021] This invention automatically activates anti-interference strategies for tiered attack scenarios, improving communication stability under extreme conditions; it also works in conjunction with HIS and EHR systems to achieve collaborative optimization of "device-scenario-patient," aligning with medical business processes and enhancing the convenience of clinical applications. Attached Figure Description

[0022] Figure 1 This is a diagram of the overall system architecture of the present invention; Figure 2 This is a flowchart of the dynamic interference coordination and optimization method of the present invention; Figure 3 This is a comparison chart of the hierarchical scene adaptation parameters of the present invention; Figure 4 This is a schematic diagram of the cross-scenario transfer and collaboration mechanism of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Example: like Figures 1-4 As shown, this embodiment of the invention provides a dynamic interference cooperative communication optimization method for hierarchical medical scenarios, which includes the following: S1. Based on the differences in the hierarchical medical scenarios of emergency, ICU and general ward, covert communication is achieved by utilizing the mutual interference signals of the native physiological data transmission of multiple devices in the medical monitoring network. The mutual interference signals are electromagnetic interference generated by devices such as monitors and ventilators when transmitting hierarchical physiological data (such as defibrillation parameters in the emergency scenario and real-time ECG data in the ICU). The interference intensity is dynamically adjusted according to the scenario level. S2. Set differentiated communication security thresholds and data timeliness indicators for different levels of scenarios, including: Safety threshold: Quantified by the detection error rate (η_i) of unauthorized devices, with sensitive data in emergency / ICU scenarios η_i≥0.95 and routine data in general wards η_i≥0.8; Timeliness indicators: quantified by Information Age (AoI), with AoI ≤ 50ms in emergency scenarios, ≤ 100ms in ICU scenarios, and ≤ 300ms in general wards; The safety threshold and timeliness indicators in a tiered healthcare system are linked in the following ways: The time-varying expression for the detection error rate is derived from the contextualized data access rate (ω_i) of medical devices: η_i = α_i + β_i; Among them, α_i=p(D_i 1 |Ω_i 0 (1-ω_i) represents the probability of misjudging an unauthorized device when the device does not transmit; β_i=p(D_i 0 |Ω_i 1 ω_i represents the probability of misidentification as an unauthorized device during transmission; ω_i is dynamically set according to the scenario level: ω_i≥0.9 in emergency scenarios (high-frequency transmission ensures timeliness), ω_i=0.7-0.9 in ICU scenarios, ω_i=0.5-0.7 in general wards, and β_i is constrained to ≤0.05 in emergency / ICU scenarios (to avoid missing critical data). S3. Construct a dynamic interference coordination framework. By adjusting the transmission power (P_i) of medical devices and the gain of dedicated channels (h_j, i^va), the interference intensity is adapted so that the interference signal meets the graded safety threshold and ensures that the signal-to-interference-plus-noise ratio (SINR) of the target link is not lower than the minimum requirement of the graded scenario. No additional interference generation module is required, which solves the contradiction between privacy protection and real-time data transmission in medical scenarios. The control logic of the dynamic disturbance coordination framework includes: 1) Scene level recognition: The hospital information system (HIS) is used to obtain real-time scenario levels (such as emergency resuscitation status and ICU bed occupancy information) and trigger corresponding safety and timeliness parameters. 2) Dynamic allocation of interference intensity: For critical equipment such as emergency defibrillators and ICU ventilators, a higher interference contribution weight (≥60%) is assigned, and their transmission power adjustment has the highest priority. For non-critical equipment in general wards (such as bedside terminals), the interference contribution weight should be limited to ≤30% to avoid excessive occupation of channel resources; 3) Power-interference coordinated regulation: Under the premise of meeting the graded SINR thresholds (emergency ≥12dB, ICU ≥10dB, general ward ≥8dB), the transmission power is optimized through an iterative algorithm to keep η_i above the graded safety threshold while minimizing AoI.

[0025] It also includes worst-case security scenario response mechanisms for tiered scenarios: The worst detection scenario for the hierarchical scenario is defined as: 1) Emergency scenario: An unauthorized device is located within 10 meters of the emergency room and attempts to intercept communication between the defibrillator and the central monitoring system; 2) ICU scenario: Unauthorized devices access the ICU's dedicated Wi-Fi channel, attempting to sniff out physiological data transmitted synchronously by multiple devices; 3) In a general ward scenario: Unauthorized devices interfere with unencrypted routine vital signs data via Bluetooth broadcasts. In the above scenarios, the system automatically increases the interference redundancy of the corresponding scenario (by 20%-50% compared to the normal value) and switches to an anti-interference modulation mode (such as synchronizing the frequency hopping period with the ECG sampling rate).

[0026] Timeliness optimization is achieved through an iterative algorithm that adapts to different scenarios, and the steps include: 1) For emergency scenarios, an improved Dinkelbach algorithm with accelerated convergence is adopted, and the iteration step size of the Lagrange multiplier (ζ_i) is set to 2-3 times the normal value to ensure that AoI converges within 50ms; 2) For the ICU scenario, a power-access rate dual-variable coupled iteration is adopted to prioritize the timeliness balance when multiple devices transmit synchronously (maximum AoI difference ≤ 30ms). 3) For general ward scenarios, a low-complexity suboptimal algorithm is adopted to reduce the consumption of computing resources while ensuring AoI ≤ 300ms; All algorithms incorporate scene-level recognition modules and optimize strategies based on real-time scene switching.

[0027] This invention also includes a dynamic interference collaborative communication optimization system for tiered medical scenarios, the optimization system comprising: Multiple tiered medical monitoring devices are configured as follows: Emergency area: Deploy defibrillators, bedside monitors, etc., supporting high-frequency physiological data transmission (≥100Hz), with native transmission interference intensity adjustable from -50 to -30dBm; ICU area: Deploy ventilators, infusion pumps, etc., support multi-device synchronous transmission (time synchronization error ≤10ms), and the mutual interference intensity is adjustable from -55 to -35dBm; General wards: Deploy routine vital sign monitoring equipment with a transmission frequency ≤50Hz and an adjustable mutual interference intensity range of -60 to -40dBm; Collaborative control unit, built-in: Scene level recognition module: In conjunction with the HIS system, it obtains scene level (emergency room / ICU / general ward) and patient condition tags (such as APACHE score) in real time. Dynamic interference scheduling module: Assigns interference contribution weights to each device according to the scenario level and generates power adjustment commands; The graded safety monitoring module calculates the detection error rate (η_i) in different scenarios in real time to ensure that the graded safety threshold is met. Timeliness optimization module: Runs corresponding optimization algorithms for different scenarios to dynamically adjust the data transmission cycle and retransmission strategy; The system achieves a quantitative balance between communication security and timeliness in tiered scenarios through the collaborative scheduling of native interference between medical devices.

[0028] The dynamic interference scheduling module is configured as follows: Establish an interference contribution matrix and record the interference weight of each device in different scenarios (e.g., the weight of the emergency defibrillator is fixed at 0.7). When cross-scenario device movement is detected (such as a monitor during transport), its interference weight is automatically adjusted to the appropriate range for the target scenario (e.g., when transferring from a general ward to the ICU, the weight is increased from 0.3 to 0.5). When interference conflicts exist (such as multiple devices interfering with each other, resulting in excessively low SINR), a priority arbitration mechanism is triggered to prioritize the interference adjustment authority of critical equipment.

[0029] The graded safety monitoring module is configured as follows: Built-in HIPAA compliance verification rules automatically raise the η_i threshold to ≥0.98 for sensitive data such as HIV and mental illness. Real-time monitoring of the detection behavior of unauthorized devices (such as abnormal channel occupation and repeated connection requests). When the detection frequency exceeds the threshold of the graded scenario (emergency ≥ 5 times / minute), the interference enhancement mode is triggered.

[0030] It also includes a cross-scenario collaboration interface, which is configured as follows: When patients are transferred between different scenarios (such as from the emergency room to the ICU), historical communication parameters (such as interference weights and AoI optimization results) are transmitted synchronously to the collaborative control unit of the target scenario. It supports data interaction with hospital electronic health record (EHR) systems and dynamically adjusts security policies for corresponding scenarios based on the privacy level tags in patient medical records.

[0031] The following are application examples in three typical scenarios: emergency room, ICU, and general ward, detailing the implementation process and effects of the technical solution: Case 1: Optimization of Communication between Defibrillators and Central Monitoring Systems in Emergency Scenarios Scene configuration Medical equipment: Deploy 1 defibrillator (critical equipment) and 2 bedside monitors (auxiliary equipment), all in accordance with the IEC60601 protocol, transmitting data including defibrillation parameters (such as energy value and impedance) and real-time electrocardiogram waveforms (sampling rate 500Hz).

[0032] Scenario Level: Identified as an "emergency resuscitation status" by the HIS system, triggering the highest priority safety and timeliness parameters: Security thresholds: Unauthorized device detection error rate η_i ≥ 0.95 (sensitive data), β_i ≤ 0.05 (to avoid missing critical data); Timeliness metrics: AoI≤50ms, Contextualized data access rate ω_i=0.95 (high-frequency transmission).

[0033] Dynamic interference coordination process Native interference generation: The defibrillator and monitor naturally generate mutual interference signals (intensity range -50 to -30 dBm) when transmitting data, without the need for an additional interference module. Among them, the defibrillator, as the key device, is allocated 60% of the interference contribution weight, and the monitors are each allocated 20%.

[0034] Power-interference coordinated regulation: Initial transmission power: defibrillator P=15dBm, monitor P=12dBm, dedicated channel gain h_j,i^va=25dB (due to the small space in the emergency room, the channel attenuation is low).

[0035] Real-time SINR monitoring: Defibrillator link SINR=14dB (≥12dB threshold), meeting transmission reliability; Detection error rate η_i of unauthorized devices (simulated location 10 meters outside the emergency room)=0.96 (≥0.95 threshold).

[0036] Timeliness optimization algorithm: An improved Dinkelbach algorithm with accelerated convergence is employed, with the Lagrange multiplier ζ_i iteration step size set to three times the conventional value. Algorithm acceleration is triggered when the defibrillator detects a heart rate >180 beats / min. First iteration: Access rate ω_i increased from 0.95 to 0.98, and transmission power was fine-tuned to 15.5dBm; Third iteration (takes 35ms): AoI converges to 42ms, meeting the ≤50ms requirement, and optimization stops.

[0037] worst-case scenario response When an unauthorized device sniffs via Bluetooth (detection frequency reaches 6 times / minute, exceeding the emergency threshold of 5 times / minute), the system automatically increases the interference redundancy by 30%. The defibrillator's transmission power has been increased to 16dBm, the monitor's synchronization power has been increased to 13dBm, and the mutual interference intensity has been improved to -45dBm. Switching to frequency hopping mode, the frequency hopping period is synchronized with the ECG sampling rate (500Hz) (2ms / hop), the unauthorized device detection error rate rises to 0.98, and interception fails.

[0038] Case 2: Optimization of Multi-device Synchronous Transmission in ICU Scenarios Scene configuration Medical equipment: 4 ventilators (critical equipment), 2 infusion pumps (secondary critical equipment), 1 central monitoring terminal. The transmitted data includes airway pressure (sampling rate 100Hz) and drug infusion rate (sampling rate 50Hz). The time synchronization error of multiple devices must be ≤10ms.

[0039] Scene level: HIS system identifies it as "ICU Intensive Care Unit", parameter settings: Safety thresholds: η_i≥0.95 (ventilator data), η_i≥0.9 (infusion pump data); Timeliness indicators: AoI≤100ms, maximum AoI difference≤30ms (to ensure data consistency across multiple devices).

[0040] Dynamic interference coordination process Disturbance contribution weight allocation: The total interference weight for ventilators (4 units) is 70% (17.5% per unit), the total interference weight for infusion pumps (2 units) is 20% (10% per unit), and the weight for the central monitoring terminal is 10%, in order to avoid non-critical equipment occupying too much channel resources.

[0041] Power-access rate bivariate iteration: Initial state: ventilator P=13dBm, infusion pump P=11dBm, ω_i=0.8 (ventilator), 0.75 (infusion pump); Synchronization optimization: After three iterations, the ventilator AoI was 75ms and the infusion pump AoI was 85ms, with a difference of 20ms (≤30ms threshold). The SINR was maintained at 11dB (≥10dB threshold).

[0042] Safety monitoring: The graded safety monitoring module calculates η_i in real time: ventilator data η_i=0.96, infusion pump data η_i=0.92, both meeting the safety threshold; because the ICU uses a dedicated Wi-Fi channel (802.11ax protocol), unauthorized devices attempting to access the network are blocked by the gateway, triggering the interference enhancement mode (mutual interference intensity increased by 20%).

[0043] Case 3: Routine vital sign monitoring in a general ward setting Scene configuration Medical equipment: 1 routine vital signs monitor (transmits heart rate and blood pressure, sampling rate 20Hz), 1 bedside terminal (non-critical equipment, transmits non-sensitive data).

[0044] Scene level: The HIS system identifies it as a "general ward". Parameter settings: Safety threshold: η_i ≥ 0.8 (standard data); Timeliness metric: AoI≤300ms, using a low-complexity suboptimal algorithm.

[0045] Dynamic interference coordination process Interference intensity control: The interference weight for the vital signs monitor is 25% (P=10dBm), and the weight for the bedside terminal is 10% (P=8dBm). The mutual interference intensity range is -60 to -40dBm (due to the large space in the ward and high channel attenuation).

[0046] Low-complexity optimization: Using a simplified iterative algorithm, only 2 iterations are needed to meet AoI=280ms (≤300ms), and the computational resource consumption is reduced by 60% compared with the ICU scenario (suitable for edge computing nodes in wards).

[0047] Privacy level adaptation: When a patient's EHR is marked as "HIV positive" (sensitive data), the graded security monitoring module automatically raises the η_i threshold to 0.98, increases the transmission power of the vital signs monitor to 11dBm, and increases the mutual interference intensity to -50dBm, ensuring that the error rate of unauthorized device detection reaches 0.99.

[0048] Case 4: Cross-scenario patient transfer collaboration (emergency room → ICU) When a patient is transferred from the emergency room to the ICU, the system achieves a seamless switch through a cross-scenario collaborative interface: Ten seconds before the transfer, the emergency collaborative control unit synchronizes historical parameters to the ICU unit: defibrillator interference weight 0.7, AoI optimization result 42ms, and unauthorized device detection records; ICU unit pre-start strategy: Temporarily increase the ventilator interference weight from 17.5% to 25% in advance, and reserve channel resources; During the transfer (approximately 2 minutes), the mobile monitor automatically reduces the transmission frequency to 80Hz (normal value 100Hz), while increasing the interference redundancy by 40% to ensure that the AoI is maintained at 85ms (<100ms threshold). Scene Key Indicators Implementation Results Compared to traditional medical communication solutions Emergency AoI convergence time 35ms (≤50ms) Reduced latency by 65% ​​(traditional encryption latency is 100ms). ICU Multi-device AoI differences 20ms (≤30ms) Reduced by 50% (traditional solution 40ms) General ward Computational resource consumption 60% lower than in ICU settings Adapting to low computing power requirements of edge nodes Cross-scenario transfer Parameter synchronization time 3 seconds Traditional methods require manual configuration (>30 seconds). Safety performance Unauthorized device detection error rate Emergency room 0.98 / ICU 0.96 / Ward 0.99 All are above the medical privacy and security threshold. After connecting to the ICU network, parameter switching is completed within 3 seconds, and data is transmitted synchronously with ICU equipment, with a maximum AoI fluctuation of ≤20ms.

[0049] The above embodiments fully verify the technical feasibility of "hierarchical scenario adaptation", "dynamic interference coordination" and "dual optimization of safety and timeliness" in the claims. All parameters have passed medical electromagnetic compatibility (EMC) certification (ECG signal noise amplification ≤ 5μV), which meets the HIPAA regulations for patient data privacy.

[0050] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising a reference structure" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0051] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A dynamic interference-based collaborative communication optimization method for hierarchical medical scenarios, characterized by: The method includes the following: S1. Based on the differences in the hierarchical medical scenarios of emergency, ICU and general ward, covert communication is achieved by utilizing the mutual interference signals of the native physiological data transmission of multiple devices in the medical monitoring network. The mutual interference signals are the electromagnetic interference generated by the monitors and ventilators when transmitting hierarchical physiological data. The interference intensity is dynamically adjusted according to the scenario level. S2. Set differentiated communication security thresholds and data timeliness indicators for different levels of scenarios, including: Safety threshold: Quantified by the detection error rate (η_i) of unauthorized devices, with sensitive data in emergency / ICU scenarios η_i≥0.95 and routine data in general wards η_i≥0.8; Timeliness indicators: quantified by Information Age (AoI), with AoI ≤ 50ms in emergency scenarios, ≤ 100ms in ICU scenarios, and ≤ 300ms in general wards; S3. Construct a dynamic interference coordination framework. By adjusting the transmission power (P_i) of medical devices and the gain of dedicated channels (h_j, i^va), the interference intensity is adapted so that the interference signal meets the graded safety threshold and ensures that the signal-to-interference-plus-noise ratio of the target link is not lower than the minimum requirement of the graded scenario. No additional interference generation module is required, which solves the contradiction between privacy protection and real-time data transmission in medical scenarios.

2. The dynamic interference cooperative communication optimization method for hierarchical medical scenarios according to claim 1, characterized in that: The safety threshold and timeliness indicators for the tiered medical care scenario are linked in the following ways: The time-varying expression for the detection error rate is derived from the contextualized data access rate (ω_i) of medical devices: η_i = α_i + β_i; Among them, α_i=p(D_i 1 |Ω_i 0 (1-ω_i) represents the probability of misjudging an unauthorized device when the device does not transmit; β_i=p(D_i 0 |Ω_i 1 ω_i represents the probability of misidentification as an unauthorized device during transmission; ω_i is dynamically set according to the scenario level: ω_i≥0.9 in emergency scenarios, ω_i=0.7-0.9 in ICU scenarios, and ω_i=0.5-0.7 in general wards, and β_i is constrained to ≤0.05 in emergency / ICU scenarios.

3. The dynamic interference cooperative communication optimization method for hierarchical medical scenarios according to claim 2, characterized in that: The control logic of the dynamic interference coordination framework includes: 1) Scene level recognition: The hospital information system is used to obtain the real-time scenario level and trigger corresponding security and timeliness parameters. 2) Dynamic allocation of interference intensity: For critical equipment such as emergency defibrillators and ICU ventilators, a higher interference contribution weight is assigned, and their transmission power adjustment has the highest priority. For non-critical equipment in general wards, the interference contribution weight should be limited to ≤30% to avoid excessive occupation of channel resources; 3) Power-interference coordinated regulation: Under the premise of meeting the graded SINR threshold, the transmission power is optimized through an iterative algorithm to keep η_i above the graded safety threshold while minimizing AoI.

4. The dynamic interference cooperative communication optimization method for hierarchical medical scenarios according to claim 3, characterized in that: It also includes worst-case security scenario response mechanisms for tiered scenarios: The worst detection scenario for the hierarchical scenario is defined as: 1) Emergency scenario: An unauthorized device is located within 10 meters of the emergency room and attempts to intercept communication between the defibrillator and the central monitoring system; 2) ICU scenario: Unauthorized devices access the ICU's dedicated Wi-Fi channel, attempting to sniff out physiological data transmitted synchronously by multiple devices; 3) In a general ward scenario: Unauthorized devices interfere with unencrypted routine vital signs data via Bluetooth broadcasts. In the above scenarios, the system automatically increases the interference redundancy of the corresponding scenario and switches to anti-interference modulation mode.

5. The dynamic interference cooperative communication optimization method for hierarchical medical scenarios according to claim 4, characterized in that: The timeliness optimization is achieved through an iterative algorithm for hierarchical scenario adaptation, and the steps include: 1) For emergency scenarios, an improved Dinkelbach algorithm with accelerated convergence is adopted, and the iteration step size of the Lagrange multiplier (ζ_i) is set to 2-3 times the normal value to ensure that AoI converges within 50ms; 2) For the ICU scenario, a power-access rate dual-variable coupled iteration is adopted to prioritize the balance of timeliness when multiple devices transmit synchronously; 3) For general ward scenarios, a low-complexity suboptimal algorithm is adopted to reduce the consumption of computing resources while ensuring AoI ≤ 300ms; All algorithms incorporate a scene level recognition module and optimize strategies based on real-time scene switching.

6. The optimization system of the dynamic interference cooperative communication optimization method for hierarchical medical scenarios according to claim 5, characterized in that: The optimization system includes: Multiple tiered medical monitoring devices are configured as follows: Emergency area: Deploy defibrillators and bedside monitors, supporting high-frequency physiological data transmission, with native transmission interference intensity adjustable from -50 to -30 dBm; ICU area: Deploy ventilators and infusion pumps, support simultaneous transmission of multiple devices, and the mutual interference intensity is adjustable from -55 to -35dBm; General wards: Deploy routine vital sign monitoring equipment with a transmission frequency ≤50Hz and an adjustable mutual interference intensity range of -60 to -40dBm; Collaborative control unit, built-in: Scene level recognition module: In conjunction with the HIS system, it obtains scene level and patient condition tags in real time; Dynamic interference scheduling module: Assigns interference contribution weights to each device according to the scenario level and generates power adjustment commands; The graded safety monitoring module calculates the detection error rate (η_i) in different scenarios in real time to ensure that the graded safety threshold is met. Timeliness optimization module: Runs corresponding optimization algorithms for different scenarios to dynamically adjust the data transmission cycle and retransmission strategy; The system achieves a quantitative balance between communication security and timeliness in tiered scenarios through the collaborative scheduling of native interference between medical devices.

7. The dynamic interference cooperative communication optimization system for hierarchical medical scenarios according to claim 6, characterized in that: The dynamic interference scheduling module is configured as follows: Establish an interference contribution matrix to record the interference weight of each device in different scenarios; When cross-scene device movement is detected, its interference weight is automatically adjusted to the adaptation range of the target scene; When interference conflicts occur, a priority arbitration mechanism is triggered to prioritize the interference adjustment authority of critical equipment.

8. The dynamic interference cooperative communication optimization system for hierarchical medical scenarios according to claim 7, characterized in that: The hierarchical safety monitoring module is configured as follows: Built-in HIPAA compliance verification rules automatically raise the η_i threshold to ≥0.98 for sensitive data related to HIV and mental illness. The system monitors the detection behavior of unauthorized devices in real time, and triggers an interference enhancement mode when the detection frequency exceeds the threshold of the tiered scenario.

9. The dynamic interference collaborative communication optimization system for hierarchical medical scenarios according to claim 8, characterized in that: It also includes a cross-scenario collaboration interface, which is configured as follows: When patients are transferred between different scenarios, historical communication parameters are synchronously transmitted to the collaborative control unit of the target scenario; It supports data interaction with hospital electronic health record systems and dynamically adjusts security policies for corresponding scenarios based on the privacy level tags in the patient's medical records.

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