Neuromodulation Artifact Removal via Predictive Signal Compensation

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Solution Overview

Problem

Persistent stimulation artifacts in neuromodulation systems distort recorded signals, making it challenging to achieve effective neuromodulation treatments for neurological disorders.

Innovation Solution

A method that involves receiving brain activity data with stimulus artifact signals, predicting artifact-free brain activity, inserting the predicted activity into the data, determining a brain stimulus based on the predicted activity, and applying the stimulus to improve treatment efficacy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If electrical stimulation pulses are applied to the brain using electrodes, then brain function is altered and enhanced, but stimulation artifacts distort recorded signals

Engineering Contradiction:

Improveneuromodulation treatment efficacyVSAvoidstimulation artifact distortion

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary actions by recording brain activity before stimulation occurs and using this pre-stimulation data to predict expected brain activity patterns. This prediction is then used to identify and remove stimulation artifacts from recorded signals, allowing the system to compensate for the harmful artifact distortion before it affects treatment efficacy.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback by continuously monitoring brain activity during stimulation, comparing actual recordings against predicted patterns, and using this information to adjust future stimulation parameters. The artifact removal process feeds back modified signals that are used to refine subsequent neuromodulation treatments.

Inventive Principle:

Principle #23Feedback

2Measurement precision

If artifact removal techniques are applied to recorded signals, then signal quality is improved, but system complexity increases

Engineering Contradiction:

Improverecorded signal qualityVSAvoidartifact removal system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs self-service by using its own recorded brain activity data and built-in prediction algorithms to remove artifacts automatically. The neuromodulation device leverages its inherent capabilities to generate predictions from its own sensor data, eliminating the need for external artifact removal systems and reducing overall system complexity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces complex mechanical or hardware-based artifact removal mechanisms with computational algorithms that process electrical signals. By substituting physical artifact removal hardware with software-based prediction and removal algorithms, the system achieves signal cleaning while maintaining device simplicity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Ease of operation

If constant repeating electrical stimulation pulses are applied, then treatment is simplified, but energy consumption increases

Engineering Contradiction:

Improvestimulation protocol simplicityVSAvoidenergy consumption

Core Design Contradiction:

Ease of operationVSUse of energy by moving object

Solution Approach 1:

The system transitions from static constant stimulation to dynamic adaptive stimulation by continuously adjusting pulse parameters based on real-time brain activity predictions and artifact removal results. This dynamic approach allows the system to optimize energy consumption by applying stimulation only when and where needed, while maintaining operational simplicity through automated adaptation.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes stimulation parameters dynamically based on predicted brain activity patterns and artifact characteristics. By adjusting parameters such as pulse frequency, amplitude, and duration according to real-time neural data, the system optimizes energy efficiency while maintaining treatment effectiveness, replacing simple constant stimulation with parameter-optimized adaptive stimulation.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250135204A1System and method for removing stimulation artifact in neuromodulation systems

Publication Date: 2025.05.01 JOHNS HOPKINS UNIVERSITY

AI summary

A method, computer system, and a non-transitory computer readable medium are disclosed that performs instructions including receiving, from one or more electrodes, information identifying brain activity with a stimulus artifact signal for a first time period; predicting, based on the information identifying the brain activity for the first time period, predicted brain activity without the stimulus artifact signal for a second time period that is to occur after the first time period; inserting the predicted brain activity into the information for a second time period; determining, based on the predicted brain activity for the second time period, a brain stimulus for the second time period; and causing the brain stimulus to be applied the second time period.