Closed-Loop Brain Stimulation System with Real-Time EEG Feedback
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Solution Overview
Problem
Open loop brain stimulation systems lack real-time feedback and adjustment capabilities, making them ineffective in optimizing brain stimulation parameters for individual differences and changing brain dynamics, which limits their therapeutic and enhancement applications.
Innovation Solution
A closed loop brain stimulation system that continuously monitors brain and biometric signals using electrophysiological and biometric data, and adjusts stimulation parameters via a control algorithm to minimize a reference utility function, optimizing brain and biometric states in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If open loop brain stimulation is used, then the system is simple to operate, but it cannot optimize stimulation parameters for individual differences and changing brain dynamics
Solution Approach 1:
The patent implements a closed-loop brain stimulation system that continuously monitors brain activity via EEG and adjusts stimulation parameters in real-time based on the measured response. The control algorithm processes the EEG signals and modifies stimulation intensity, frequency, or duration dynamically, creating a feedback mechanism that enables adaptability to individual differences and changing brain states without requiring complex manual intervention.
Solution Approach 2:
The system transitions from static, pre-programmed stimulation parameters to dynamic parameter adjustment. The stimulation regime becomes adaptive, with parameters that automatically evolve based on real-time brain state monitoring. This dynamic approach allows the system to respond to individual variability and temporal changes in brain physiology while maintaining automated control.
2Manufacturing precision
If closed loop brain stimulation with real-time monitoring is implemented, then optimization of brain stimulation parameters is achieved, but device complexity increases
Solution Approach 1:
The system employs continuous EEG monitoring during stimulation sessions, measuring brain activity to assess the effect of applied stimulation. A control algorithm processes these EEG signals in real-time and automatically adjusts stimulation parameters to optimize therapeutic effect. This feedback-driven approach achieves precise parameter optimization while automating the process to manage system complexity.
Solution Approach 2:
The closed-loop system performs self-adjustment of stimulation parameters based on real-time EEG feedback and control algorithm processing. The system autonomously optimizes its own operation without requiring continuous manual intervention or complex external control, thereby achieving precise parameter optimization while keeping the operational complexity manageable through automation.
3Productivity
If continuous monitoring of brain signals is performed, then real-time adjustment of stimulation parameters is enabled, but loss of time for data processing increases
Solution Approach 1:
The system maintains continuous EEG monitoring and continuous control algorithm processing throughout the stimulation session, eliminating interruptions for data analysis. The real-time processing pipeline continuously transforms incoming EEG data into stimulation parameter adjustments without batch processing delays, ensuring uninterrupted therapeutic action and maximizing productivity while keeping processing time minimal through ongoing operation.
Solution Approach 2:
The control algorithm is pre-configured with the necessary processing logic and decision rules before the stimulation session begins. This preliminary preparation enables rapid real-time processing of EEG data during the session, as the computational framework is already in place to immediately translate brain state measurements into parameter adjustments without requiring complex on-the-fly decision-making, thus reducing processing time delays.
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
This approach enables more efficacious treatment of brain pathologies and enhancement of non-pathological functions by accounting for individual differences and dynamic changes in brain anatomy and physiology, providing a more personalized and adaptive stimulation regime.
Implementation Method 1
this is carried out via the amplification of the small currents that the brain generates on the surface of the scalp (EEG)
Implementation Method 2
In the primary embodiment of this document, this stimulation is in the form of transcranial electrical stimulation (TES)
Data Source
AI summary
A closed loop brain stimulation system includes a means for reading electrophysiological signals from the brain; means for reading other biometric signals; means for stimulating the brain; and a control algorithm that dynamically adjusts the parameters of stimulation to minimize a reference utility function that computes the difference between the current and desired brain states, and current and desired biometric states.