Personalized Electromagnetic Treatment Protocol Generation
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Solution Overview
Problem
Current methods for electromagnetic treatment of the nervous system lack a systematic approach to generate personalized protocols for impaired functionalities, relying on empirical data rather than data-driven analysis of neural activity.
Innovation Solution
A system that uses neural activity sensors to collect data, processes it to identify specific neural network frequencies associated with impaired functionalities, and generates a treatment protocol for an electromagnetic field to address these impairments, with adjustable characteristics like amplitude and duration, and monitors patient response for protocol modification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If empirical data and general protocols are used for electromagnetic treatment, then treatment can be applied without personalized analysis, but treatment efficacy is reduced due to lack of personalization
Solution Approach 1:
The system performs preliminary neural activity analysis and protocol customization before treatment begins. Neural activity sensors collect baseline data, the processor analyzes this data to identify impaired functionalities and generate personalized treatment protocols, and only then is treatment applied. This preliminary personalized analysis ensures treatment efficacy while maintaining efficient workflow.
2Reliability
If personalized treatment protocols are generated through systematic neural activity analysis, then treatment efficacy is improved, but system complexity increases
Solution Approach 1:
The system divides the complex treatment protocol generation process into distinct functional modules: neural activity sensors for data collection, a processor for analysis, a protocol generation module for customization, and a treatment delivery system. This segmentation allows each component to perform its specific function efficiently, reducing overall system complexity while enabling personalized treatment.
Solution Approach 2:
The system automatically collects neural activity data, analyzes it to identify impaired functionalities, generates personalized treatment protocols, and adjusts treatments based on real-time feedback without requiring manual intervention. This self-service automation reduces the complexity burden on operators while maintaining high treatment efficacy through systematic personalization.
3Adaptability or versatility
If neural activity sensors and systematic analysis are implemented, then personalized treatment can be achieved, but measurement and detection difficulty increases
Solution Approach 1:
The system uses universal neural activity sensors that can measure multiple types of neural signals (electrical and magnetic fields) across different brain regions. These multi-functional sensors simplify the measurement process by consolidating multiple detection capabilities into single devices, reducing the complexity of setting up and managing multiple specialized measurement systems while enabling comprehensive personalized analysis.
Data Source
Figure 1
Figure 2A~2C
Figure 3A
AI summary
A system includes a communication interface for receiving information that includes data collected from an array of neural activity sensors that were placed on a patient during a session of applied stimuli. A processor is configured to analyze the received information to obtain a frequency spectrum for each sensor for a given stimulus of the applied stimuli. Neural network frequencies that correspond to an indicated impaired functionality of the nervous system of the patient are selected. For each selected frequencies, a spatial map of neural activity is generated. Each of the generated spatial maps is compared with retrieved corresponding spatial maps to identify treatment frequencies from among the selected neural network frequencies. A treatment protocol is generated for input into an electromagnetic field generator to cause the generator to apply to the patient an electromagnetic field at each identified treatment frequency.