Universal Neurostimulator Programming via Auto-Identification
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Solution Overview
Problem
Current neurostimulation systems require specific knowledge of the type and configuration of implanted neurostimulators to program them effectively, which can be limiting in clinical settings where different systems and software packages are needed, and lead configuration information is often not readily available for follow-up programming sessions.
Innovation Solution
An external control device capable of identifying and programming multiple types of neurostimulators with different numerical ranges, using memory and processing circuitry to store and access look-up tables for various types and configurations, allowing it to adapt and program neurostimulators without prior knowledge of their type or configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specific software packages are used for each neurostimulator type, then programming accuracy is improved, but device complexity and clinical workflow complexity increase
Solution Approach 1:
The external control device is designed with a universal programming interface that can identify and program multiple types of neurostimulators through a single device. The system automatically detects the neurostimulator type and configures appropriate programming parameters, eliminating the need for multiple specialized software packages while maintaining programming accuracy across different device types
Solution Approach 2:
The system stores configuration information and programming parameters in memory that can be retrieved and applied to different neurostimulator types. By copying and adapting programming templates for various device types, the system maintains accuracy without requiring separate software packages for each device
2Adaptability or versatility
If lead configuration information is stored externally, then programming flexibility is improved, but information reliability deteriorates when lead information is not readily available
Solution Approach 1:
The system automatically captures and stores lead configuration information during the initial implantation procedure. By performing this data collection action in advance, the information is preserved in the external control device's memory, ensuring both flexibility for future programming and reliability of the stored configuration data
Solution Approach 2:
The external control device acts as an intermediary that stores and manages lead configuration information between the implantation procedure and follow-up programming sessions. This intermediary storage ensures the information remains reliably available even when not directly connected to the implantation system
3Adaptability or versatility
If multiple neurostimulator types are supported, then adaptability is improved, but device complexity increases
Solution Approach 1:
The external control device incorporates automatic identification capabilities that allow it to self-configure when connected to different neurostimulator types. The system automatically detects the device type, retrieves appropriate programming parameters from stored templates, and configures itself without requiring manual intervention or complex user navigation, thereby managing multi-device support without proportionally increasing operational complexity
Solution Approach 2:
The programming interface dynamically adapts its configuration based on the detected neurostimulator type. The system automatically adjusts available parameters, programming options, and interface elements to match the specific device being programmed, providing broad compatibility while maintaining a consistent and manageable user experience
Data Source
AI summary
External control devices, neurostimulation systems, and programming methods. A neurostimulator includes a feature having a numerical range. Information identifying a type of the neurostimulator is transmitted to an external control device. The external control device receives the information from the neurostimulator, identifies the type of the neurostimulator based on the received information, and programs the neurostimulator in accordance with the numerical range of the feature corresponding to the identified type of the neurostimulator.