EEG-Guided Random-Interval TMS for Adaptive Brain Modulation
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Solution Overview
Problem
Existing TMS treatments deliver a single frequency at a set intensity, which may not effectively modulate brain activity for various psychological and medical disorders, lacking adaptability to individual patient's EEG characteristics.
Innovation Solution
Administer TMS with random variable pulse intervals derived from a patient's EEG signal, using wavelet transform algorithms to filter out noise and generate a unique EEG pattern, programming the TMS apparatus with TTL pulses for variable pulse intervals and intensities, following an idealized probability distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If TMS delivers a single frequency at a set intensity, then the treatment protocol is simple and easy to implement, but it cannot effectively modulate brain activity for various psychological and medical disorders due to lack of adaptability to individual patient's EEG characteristics
Solution Approach 1:
The patent transforms the static single-frequency TMS protocol into a dynamic adaptive protocol by continuously monitoring patient EEG characteristics and adjusting stimulation frequency and intensity in real-time. The system dynamically adapts to individual patient responses, changing parameters based on measured brain activity rather than using fixed predetermined settings.
Solution Approach 2:
The patent implements a feedback loop where patient EEG signals are continuously recorded during TMS treatment, analyzed to determine brain response characteristics, and used to adjust subsequent stimulation parameters. This closed-loop feedback system enables the TMS device to respond to actual patient brain activity and optimize treatment in real-time.
2Reliability
If TMS uses variable pulse intervals derived from EEG signals with wavelet transform analysis, then brain activity modulation is enhanced and targeted brain wave amplitudes increase, but the treatment protocol becomes more complex requiring advanced signal processing
Solution Approach 1:
The patent performs wavelet transform analysis and EEG signal processing in advance to identify optimal stimulation parameters before delivering TMS pulses. By pre-analyzing EEG characteristics and determining variable pulse intervals beforehand, the system reduces the computational burden during actual treatment while maintaining enhanced modulation effectiveness.
Solution Approach 2:
The patent employs periodic TMS pulse trains with variable intervals rather than continuous or uniformly spaced pulses. The pulse delivery follows rhythmic patterns with varying periods based on EEG analysis, creating periodic stimulation that enhances brain wave modulation while allowing for parameter variation within each periodic cycle.
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 enhances brain activity modulation, leading to improvements in conditions such as ASD, PTSD, depression, Parkinson's disease, and others, by increasing targeted brain wave amplitudes and power density, outperforming traditional single-frequency protocols.
Implementation Method 1
Transcranial magnetic stimulation (TMS) wherein the TMS is administered with variable pulse intervals
Implementation Method 2
wavelet transform algorithms to filter out noise and generate a unique EEG pattern
Data Source
AI summary
A method of modulating a brain activity of a mammal is achieved by subjecting the mammal to transcranial magnetic stimulation (TMS) with a TMS apparatus at random variable pulse intervals for a time sufficient to modulate said brain activity. The method can also be used by administering electric stimulation to the brain. Improvement in a physiological condition or a clinical condition is achieved. Conditions to be treated include but are not limited to PTSD, autism spectrum disorder addiction (SUD) and Alzheimer's disease.