Stimulation Electrode Selection Using Bioelectrical Signals and Physiological Models
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Solution Overview
Problem
Current medical devices for electrical stimulation in the brain lack an efficient method to select the optimal electrode configuration for delivering therapy, often relying on manual selection and trial-and-error, which is time-consuming and requires significant clinical expertise.
Innovation Solution
A system that selects a stimulation electrode combination based on a bioelectrical signal sensed in the brain and a physiological model indicating anatomical structures and therapy fields, using algorithms to determine the most effective electrode configuration for delivering electrical stimulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection and trial-and-error methods are used to select electrode configuration, then clinical expertise can guide the selection process, but the time required and complexity of the procedure increases significantly
Solution Approach 1:
The system enables automatic selection of stimulation electrode combinations by analyzing sensed bioelectrical signals and comparing them against a physiological model, allowing the device to self-determine optimal electrode configurations without requiring manual clinician intervention for each selection decision
Solution Approach 2:
The system continuously senses bioelectrical signals from the brain and uses this feedback to automatically adjust and select the most appropriate electrode configuration, creating a closed-loop system that adapts to real-time physiological conditions
2Measurement precision
If manual selection and trial-and-error methods are used to select electrode configuration, then clinical expertise can guide the selection process, but the required clinical expertise and training increases
Solution Approach 1:
The system performs automatic electrode configuration selection through algorithmic analysis of bioelectrical signals, eliminating the need for clinicians to manually evaluate multiple electrode combinations and reducing the operational burden on medical professionals
Solution Approach 2:
The physiological model acts as an intermediary between the sensed bioelectrical signals and the electrode configuration selection, translating complex physiological data into actionable electrode selection decisions that guide the stimulation device
3Productivity
If automatic selection based on bioelectrical signals and physiological models is implemented, then the time and expertise required is reduced, but the device complexity increases
Solution Approach 1:
The physiological model serves multiple functions by simultaneously representing anatomical structures, predicting therapy field distributions, and guiding electrode selection decisions, thereby reducing the need for separate specialized systems for each function
Solution Approach 2:
The physiological model acts as a computational intermediary that processes raw bioelectrical signals and translates them into clinically actionable electrode configuration recommendations, managing the complexity of signal analysis algorithms
Data Source
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AI summary
One or more stimulation electrodes may be selected based on a bioelectrical signal sensed in a brain of a patient with a sense electrode combination that comprises at least one electrode and a physiological model that indicates one or more anatomical structures of the brain of the patient that are proximate the implanted at least one electrode. In some examples, the bioelectrical brain signal indicates which electrodes are located closest to a target tissue site. The physiological model can be generated based on a location of implanted at least one electrode within a patient and patient anatomy data, which can, for example, indicate one or more characteristics of patient tissue proximate to the implanted at least one electrode. In some examples, the physiological model includes a therapy field model that represents a region of the tissue of the patient to which therapy is delivered via a selected set of electrodes.