Gastric Electrical Stimulation Using CNAP Feedback
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Solution Overview
Problem
Current gastric electrical stimulation (GES) systems for treating gastroparesis lack a patient-specific approach to determine optimal stimulation parameters, leading to a time-consuming and non-targeted method for alleviating symptoms.
Innovation Solution
A system and method utilizing vagal nerve recording and feedback to statistically correlate compound nerve action potential (CNAP) parameters with gastric symptoms, allowing for personalized GES parameter selection based on individual patient data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If open-loop approach with physician selecting GES parameters is used, then device complexity is reduced, but treatment time and efficiency deteriorate
Solution Approach 1:
The system implements closed-loop feedback by continuously monitoring CNAP parameters during GES and using this information to automatically adjust stimulation parameters. The processor receives CNAP data from the vagus nerve sensor and modifies GES parameters in real-time based on the measured responses, creating a self-regulating system that eliminates the need for manual physician adjustment and significantly reduces optimization time.
Solution Approach 2:
The system performs self-optimization of GES parameters without requiring external intervention. The processor automatically analyzes CNAP data and adjusts stimulation parameters based on pre-programmed algorithms and patient-specific models, enabling the device to serve itself in the parameter optimization process and eliminating the time-consuming manual tuning required in conventional approaches.
2Ease of operation
If open-loop approach with manual parameter adjustment is used, then ease of operation is maintained, but productivity deteriorates
Solution Approach 1:
The system maintains ease of operation through automated feedback control. The processor continuously monitors CNAP parameters and automatically adjusts GES parameters based on real-time feedback, eliminating the need for manual intervention while significantly improving treatment efficiency and productivity compared to conventional manual adjustment methods.
Solution Approach 2:
The system replaces the manual mechanical process of physician parameter selection with an automated electronic control system. The processor uses algorithms and pre-programmed models to automatically determine optimal GES parameters based on CNAP data, substituting human expertise with automated computational processes that improve productivity while maintaining operational simplicity through user-friendly interfaces.
3Reliability
If patient-specific targeted solution is implemented, then treatment effectiveness is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-programming patient-specific models and algorithms before actual treatment. The processor uses pre-established CNAP parameter thresholds and stimulation parameter combinations that have been optimized for individual patients based on their specific physiological characteristics, enabling personalized treatment without requiring complex real-time computational analysis during delivery.
Solution Approach 2:
The system introduces an intermediary layer in the form of pre-computed patient-specific models and lookup tables. These intermediaries store optimized parameter combinations and CNAP characteristics for individual patients, allowing the processor to quickly retrieve and apply appropriate parameters without performing complex calculations in real-time, thus reducing computational complexity while maintaining treatment effectiveness.
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 non-invasive, data-driven optimization of GES parameters, predicting symptom improvements and managing side effects, thereby providing a more effective and efficient treatment for gastroparesis symptoms.
Implementation Method 1
Experiments in anesthetized rodents show that GES of the antrum and stimulation of the cervical vagus nerve produce vagal compound nerve action potentials (CNAPs) that can be measured with implanted cuff electrodes and with Ag/AgCl disk electrodes positioned on the skin surface over the mid cervical vagal nerves.
Implementation Method 2
Gastric electrical stimulation (GES) of the stomach, including presumably local vagal branches is an effective treatment for nausea and vomiting
Data Source
AI summary
A gastric electric stimulation (GES) system is disclosed which includes a processing system, and at least one of a left vagus nerve sensor (L/R Sensors) and a right vagus nerve sensor coupled to the processing system, the processing system is configured to receive a model which statistically correlates sensed compound nerve action potential (CNAP) parameters measured from at least one of left and right vagus nerves of subjects within a population to feedback surveys of the subjects corresponding to a plurality of gastric symptoms and symptom parameters, receive one or more gastric symptoms of a subject outside of the population (Subjectout), determine CNAP parameters that correspond to the gastric symptoms with least severity (CNAPmin), measure CNAP activity of the Subjectout from the L/R sensors while modifying GES parameters for the Subjectout, select the GES parameters that corresponds to the CNAPmin (GESout), and output the GESout.