EMC-EMI RF Signal Processing for Adaptive Ablation Energy Control
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Solution Overview
Problem
Current radio frequency ablation devices lack accurate signal tracking and adaptive feedback, leading to energy loss and electromagnetic noise, and training methods for young doctors are inadequate, making it difficult to control ablation effectively and safely.
Innovation Solution
An adaptive EMC-EMI radio frequency signal data processing method and device that segments and preprocesses signals, performs Hilbert-Huang transform, and adjusts energy parameters based on time-frequency characteristics to ensure accurate and safe energy control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If RMS current measurement is used to track radio frequency power and energy transmission, then the measurement method is simple, but it causes energy loss and electromagnetic noise in radio frequency energy transmission
Solution Approach 1:
The patent introduces an EMC-EMI sensor as an intermediary device to measure radio frequency signals without directly interfering with the energy transmission path. The sensor captures electromagnetic field information indirectly, allowing accurate measurement while minimizing energy loss and electromagnetic noise in the primary transmission channel.
Solution Approach 2:
The patent replaces traditional electrical measurement methods (RMS current measurement) with electromagnetic field-based measurement using EMC-EMI sensors. This substitution allows non-intrusive measurement of radio frequency parameters, reducing the impact on energy transmission and eliminating the need for direct electrical contact that causes energy loss.
2Ease of manufacture
If traditional training methods (knowledge point explanation, video introduction) are used for young doctors, then the training approach is simple, but long-term operation experience cannot be accurately expressed and beginners cannot understand operation steps and control parameters well
Solution Approach 1:
The patent creates a virtual copy of the surgical operation environment and parameters through signal processing and analysis. By capturing and analyzing electromagnetic signals during surgery, the system reconstructs operation states and parameters, allowing beginners to study and understand complex surgical techniques without direct mentorship, thus preserving and transmitting operational experience accurately.
Solution Approach 2:
The patent implements adaptive feedback mechanisms that provide real-time information about operation parameters and tissue responses. This feedback loop allows trainees to understand the relationship between their actions and surgical outcomes, accelerating the acquisition of operational skills and experience that would otherwise require years of practice.
3Ease of operation
If radio frequency ablation device operates without adaptive feedback, then the device operation is simple, but accurate signal tracking and adaptive control cannot be achieved
Solution Approach 1:
The patent performs preliminary signal processing and analysis before the actual ablation operation. By pre-processing electromagnetic signals and establishing baseline characteristics, the system prepares adaptive feedback mechanisms in advance, enabling accurate signal tracking during surgery without complicating the core operation for the user.
Solution Approach 2:
The patent segments the complex signal processing task into distinct stages: signal acquisition by EMC-EMI sensor, preprocessing, Hilbert-Huang transform analysis, and adaptive feedback generation. This segmentation allows sophisticated measurement and control functions to be implemented while keeping the user interface and basic operation simple for clinicians.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method and device enable precise tracking and control of radio frequency signals, reducing neuromuscular shaking by over 98% and enhancing surgical safety, especially in deep tissue cutting.
Implementation Method 1
responding to a radio frequency signal of a radio frequency ablation device acquired by an EMC-EMI sensor
Implementation Method 2
performing Hilbert-Huang transform on signals of the two window stages of ablation and cutting, and coagulation and heat control after segmentation, to obtain time-frequency characteristics of electromagnetic signals
Implementation Method 3
performing Hilbert-Huang transform on signals of the two window stages of ablation and cutting, and coagulation and heat control after segmentation
Data Source
AI summary
A method and a device of adaptive EMC-EMI radio frequency signal data processing are provided. The method includes: performing segmentation and preprocessing in response to a radio frequency signal; performing Hilbert-Huang transform on signals after segmentation; calculating EMC power, EMI radio frequency energy and mode, and a radio frequency signal-to-noise mode, and comparing the EMC power, the EMI radio frequency energy and mode, and the radio frequency signal-to-noise mode with corresponding thresholds; and adaptively adjusting energy parameters of a radio frequency ablation device, or prompting a user to adjust the energy parameters of the radio frequency ablation device. Instantaneous and dynamic radio frequency plasma is qualitatively and quantitatively detected and classified according to a signal-to-noise mode and pattern recognition of radio frequency emission, and an actual state of the knife head is perceived, to performs adaptive control or prompt the user to perform an adjustment operation.