DBS Parameter Tuning via Biokinetic Sensor Feedback
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Solution Overview
Problem
Current deep brain stimulation (DBS) therapies face challenges in optimizing electrode placement and stimulation parameters due to the lack of tools that combine physiological, electrical, and behavioral data, leading to inefficient and costly procedures, with limited access to trained professionals and suboptimal patient outcomes.
Innovation Solution
A system that uses objective biokinetic data to provide semi-automated or automated adjustment of DBS parameters, incorporating sensors like gyroscopes and accelerometers to quantify movement disorder symptoms, allowing for remote and intelligent tuning of therapy devices, reducing the need for extensive clinical visits and expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual clinical assessment and programming sessions are used for DBS parameter optimization, then clinician expertise and judgment are applied, but the process requires many clinical visits, is financially burdensome, and has limited access for geographically disparate patients
Solution Approach 1:
The system enables self-service through automated symptom monitoring and parameter adjustment. Sensors continuously collect biokinetic data, and algorithms automatically analyze this data to optimize DBS parameters without requiring frequent manual clinical visits, allowing the system to serve itself
Solution Approach 2:
The patent replaces the mechanical system of manual clinical assessment with an automated electronic system. Objective biokinetic sensors and computational algorithms substitute for clinician judgment and manual programming sessions, enabling remote monitoring and adjustment without physical presence
2Reliability
If extensive manual programming sessions are conducted to optimize DBS parameters, then thorough parameter tuning is achieved, but treatment time and costs increase significantly
Solution Approach 1:
The system implements continuous monitoring and adjustment of DBS parameters through sensors that continuously collect biokinetic data and algorithms that continuously analyze this data. This continuous useful action maintains reliable parameter optimization without requiring multiple discrete programming sessions, improving treatment efficiency
Solution Approach 2:
The patent employs feedback mechanisms where sensor data about patient symptoms continuously feeds back to the control system, which automatically adjusts DBS parameters in response. This closed-loop feedback maintains parameter optimization quality while reducing the need for extensive manual programming
3Measurement precision
If multiple sensors and algorithms are integrated for automated symptom monitoring, then objective quantitative data is obtained, but device complexity increases
Solution Approach 1:
The patent merges multiple sensors (accelerometers, gyroscopes, electromyography sensors) and algorithms into an integrated monitoring system. This consolidation achieves objective quantitative measurement of movement symptoms while managing complexity through unified system architecture that processes data from all sensors together
Data Source
AI summary
The present invention relates to methods for remotely and intelligently tuning movement disorder of therapy systems. The present invention still further provides methods of quantifying movement disorders for the treatment of patients who exhibit symptoms of such movement disorders including, but not limited to, Parkinson's disease and Parkinsonism, Dystonia, Chorea, and Huntington's disease, Ataxia, Tremor and Essential Tremor, Tourette syndrome, stroke, and the like. The present invention yet further relates to methods of remotely and intelligently or automatically tuning a therapy device using objective quantified movement disorder symptom data to determine the therapy setting or parameters to be transmitted and provided to the subject via his or her therapy device. The present invention also provides treatment and tuning intelligently, automatically and remotely, allowing for home monitoring of subjects.