EM Wave Stimulation Optimization Using Human Phantom Simulation
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Solution Overview
Problem
Existing EM wave stimulation technologies lack the ability to derive optimal stimulation conditions tailored to individual patients, leading to variable effects due to differences in patient characteristics such as height, weight, age, muscle mass, and body fat mass.
Innovation Solution
An electromagnetic wave stimulation optimization system and method that simulates a human body's response to EM wave stimulation by applying received patient and EM wave information to a pre-stored human phantom, using numerical analysis methods like FDTD, to predict optimal changes in body temperature and blood flow, thereby determining the optimal EM wave stimulation conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If EM waves of the same intensity are applied to a part of the body, then the stimulation intensity is consistent, but the effects appear differently for each target person due to differences in height, weight, ages, muscle mass, and body fat mass
Solution Approach 1:
The system performs preliminary simulation actions by applying EM wave information to a pre-stored human phantom database before actual treatment. This preliminary simulation predicts individual body responses (temperature change, blood flow change) based on patient-specific parameters (height, weight, age, muscle mass, body fat mass), allowing optimization of stimulation conditions in advance without exposing the patient to trial-and-error stimulation.
Solution Approach 2:
The system creates a virtual copy of the human body using a digital phantom that replicates the physical human body's electromagnetic properties. This digital phantom is generated based on patient-specific anatomical parameters and serves as a surrogate for predicting EM wave interaction, eliminating the need for repeated physical trials on the actual patient.
2Duration of action of moving object
If EM waves are applied for a set period of time, then the treatment duration is standardized, but side effects such as tickling or hot sensations occur due to changes in body temperature or blood flow
Solution Approach 1:
The system applies preliminary anti-action by predicting adverse effects (excessive temperature increase, abnormal blood flow changes) before actual treatment through simulation. By pre-calculating the body's thermal and hemodynamic response to proposed EM wave parameters, the system can adjust stimulation conditions to prevent side effects before they occur, rather than reacting to them after they manifest.
Solution Approach 2:
The system incorporates feedback mechanisms by using predicted body response data (temperature change, blood flow change) to iteratively optimize EM wave stimulation parameters. The simulation results feed back into the parameter optimization process, allowing the system to adjust frequency, amplitude, and duration to achieve therapeutic effects while staying within safe physiological boundaries.
3Reliability
If individualized EM wave stimulation conditions are derived for each target person, then treatment effectiveness is optimized, but the complexity of determining optimal parameters increases
Solution Approach 1:
The system achieves universality by creating a multi-functional integrated platform that combines patient data input, digital phantom generation, EM wave simulation, and parameter optimization into a single system. This universal platform handles multiple functions (anatomical modeling, electromagnetic simulation, thermal analysis, blood flow prediction) that would otherwise require separate complex systems, thereby reducing overall system complexity while maintaining individualized treatment capability.
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 system provides a precise guideline for generating and applying optimal EM waves, considering individual patient information, which enhances the effectiveness of EM wave stimulation for rehabilitation, healthcare, or exercise prescription.
Implementation Method 1
The simulation unit may apply the received information on the target person and the received information on the EM wave to a pre-stored human body phantom to perform a human body response simulation based on a Finite-difference time-domain (FDTD) and predict a change in local body temperature of the stimulation area and a change in local blood flow of the stimulation area.
Implementation Method 2
EM waves stimulate a molecular movement of a material in the process of passing through the material, thereby generating heat
Data Source
AI summary
The present disclosure relates to electromagnetic wave stimulation optimization system and method. The electromagnetic wave stimulation optimization system includes an input unit configured to receive information on a target person and information on an EM wave; a simulation unit configured to apply the received information on the target person and the received information on the EM wave to a previously stored human phantom to perform a simulation and configured to predict a human body response to EM wave stimulation; and an output unit configure dot output an optimal EM wave stimulation condition from the human body response of the EM wave stimulation for the information on the at least one EM wave.