Neurostimulation Waveform Composer Interface
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Solution Overview
Problem
Current neurostimulation systems are limited by their inability to deliver customized, complex patterns of neurostimulation pulses that mimic natural neural signals, often resulting in unintended sensations and movements due to the use of pre-defined waveforms, which can reduce efficacy and increase side effects.
Innovation Solution
A user interface system that allows for the composition and customization of neurostimulation waveforms using building blocks such as pulses, bursts, and sequences, enabling users to create and edit patterns tailored to individual patients, thereby enhancing programmability and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-defined uniform waveforms are used for neurostimulation, then device complexity is reduced and ease of operation is improved, but adaptability to individual patients deteriorates and therapeutic efficacy is reduced
Solution Approach 1:
The waveform is segmented into reusable building blocks (e.g., pulse shapes, modulation patterns, amplitude envelopes) that can be independently configured and combined. This allows clinicians to construct customized waveforms from standardized components, improving adaptability while maintaining operational simplicity through modular assembly rather than requiring complex de novo waveform design.
Solution Approach 2:
Waveform building blocks are nested hierarchically, where smaller functional units (e.g., individual pulses) are contained within larger structures (e.g., bursts, trains, or sequences). This nested architecture enables multi-level customization where clinicians can adjust parameters at different hierarchical levels, achieving high adaptability without overwhelming the user with excessive controls at any single level.
2Device complexity
If simple periodic pulse patterns are delivered, then device complexity is minimized, but the ability to emulate natural neural signals deteriorates, reducing therapeutic efficacy
Solution Approach 1:
The neurostimulation system transitions from static, fixed waveforms to dynamic, adaptable waveforms that can change parameters in real-time based on physiological feedback or pre-programmed sequences. Building blocks include variable amplitude modulation, frequency modulation, and time-varying pulse patterns that emulate the dynamic characteristics of natural neural signals, improving therapeutic efficacy without requiring excessively complex hardware.
Solution Approach 2:
The system enables independent adjustment of multiple waveform parameters (amplitude, pulse width, frequency, phase, modulation depth) through configurable building blocks. This parameter flexibility allows the generation of sophisticated pulse patterns that mimic natural neural activity, achieving high therapeutic efficacy while maintaining reasonable device complexity through software-based parameter control rather than hardware complexity.
3Adaptability or versatility
If sophisticated pulse patterns are customized for individual patients, then adaptability and therapeutic efficacy are improved, but device complexity and programming difficulty increase
Solution Approach 1:
Standardized waveform building blocks are pre-configured with common therapeutic patterns and parameter settings that have been optimized through clinical experience or research. Clinicians can select from pre-built templates (e.g., standard burst patterns, modulation schemes) and make minor adjustments rather than programming complex waveforms from scratch, reducing programming difficulty while maintaining the ability to achieve patient-specific customization.
Solution Approach 2:
Successfully configured waveforms can be copied and reused across different patients or treatment sessions. The building block architecture allows for easy duplication and modification of proven waveform patterns, reducing the programming burden for subsequent patients while maintaining adaptability through selective parameter adjustment of the copied templates.
Data Source
AI summary
An example of a system for programming a neurostimulator may include a storage device and a user interface. The storage device may be configured to store waveform building blocks. The user interface may include a display screen, a user input device, and an interface control circuit. The interface control circuit may include a waveform composer configured to allow for composition of one of more building blocks and composition of a pattern of neurostimulation pulses using selected one or more waveform building blocks. The waveform composer may include a library controller and waveform building block editors. The library controller may be configured to display a library management area on the screen. The displayed library management area allows a user to manage the stored waveform building blocks. The waveform building block editors may each be configured to allow the user to compose a type of the waveform building blocks.