Automated Neurostimulation Program Group Generation

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Solution Overview

Problem

The process of selecting optimal neurostimulation therapy programs for patients is time-consuming and prone to error, requiring significant trial and error to achieve effective symptom management while minimizing side effects and power consumption, especially when delivering therapy through program groups.

Innovation Solution

Automated generation of neurostimulation therapy program groups based on rating information and comparison of actual therapy effects to target therapy effects, allowing for the selection and combination of high-rated programs that match desired therapeutic outcomes, reducing the need for manual assembly and minimizing clinician error.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual assembly of programs into groups is performed, then the clinician can create customized program groups, but the time and effort required for programming sessions increases significantly

Engineering Contradiction:

Improvecustomization of program groupsVSAvoidprogramming session duration

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system automatically generates program groups by having the computer system perform the assembly task that would otherwise require the clinician's manual effort. The system uses stored program information and patient feedback to autonomously create optimized program groups, eliminating the time-consuming manual assembly process while maintaining customization capabilities.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-stores program information, patient feedback, and performance data in a database before programming sessions. This preliminary organization of data allows the system to quickly retrieve and assemble program groups during clinical sessions, significantly reducing the time required for program creation while maintaining adaptability.

Inventive Principle:

Principle #10Preliminary action

2Ease of operation

If manual assembly of programs into groups is performed, then the clinician can select preferred programs, but the likelihood of errors increases due to reliance on memory and handwritten notes

Engineering Contradiction:

Improveprogram selection capabilityVSAvoidaccuracy of program assembly

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system incorporates patient feedback and performance data into the program group generation process. By continuously monitoring therapy outcomes and using this feedback to refine program selections, the system ensures accurate and reliable program assembly that adapts to patient needs while eliminating errors associated with manual memory-based selection.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system replaces the manual mechanical process of note-taking and memory-based selection with an automated computerized system. The computer retrieves program information directly from stored data, eliminating the need for clinicians to rely on memory or handwritten notes, thereby significantly improving accuracy and reliability.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If a great deal of trial and error is performed to discover preferred programs, then adequate therapeutic results can be achieved, but the programming process becomes time consuming

Engineering Contradiction:

Improvetherapeutic efficacyVSAvoidprogramming efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system pre-stores performance data and therapeutic outcomes for multiple programs in a database. This preliminary collection and organization of effectiveness data allows the system to quickly identify and select the most effective programs during clinical sessions, eliminating the need for extensive trial and error while maintaining high therapeutic efficacy.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system uses stored feedback data from previous therapy sessions to guide program selection. By analyzing past performance data and patient responses, the system can predict which programs are most likely to be effective, significantly reducing the trial and error process while maintaining reliable therapeutic outcomes.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS7774067B2Autogeneration of neurostimulation therapy program groups

Publication Date: 2010.08.10 MEDTRONIC INC

AI summary

Techniques for automatically generating neurostimulation therapy program groups are disclosed. The techniques may include receiving rating information and information describing actual therapy effects for a plurality of tested programs, and receiving target therapy data describing target therapy effects. The techniques may include automatically generating plurality of program groups based on the rating information and a comparison of actual effects to the target therapy effects. Actual effects and target therapy effects may be, for example, actual paresthesia areas and target paresthesia areas. The techniques may also include determining whether a sufficient number of programs have been tested to generate a desired number of programs groups and, if a sufficient number have not been tested, automatically generating additional programs based on the tested programs, and automatically generating program groups from the tested and automatically generated programs.