Stimulation Therapy User Interface with Field Shape Programming
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Solution Overview
Problem
The process of selecting optimal electrode combinations and stimulation parameters for implantable electrical stimulators is time-consuming and requires significant trial and error, especially with complex electrode array geometries and fixed reimbursement schedules, limiting the efficiency of electrical stimulation therapy programming.
Innovation Solution
A user interface with a toolbar or menu that allows clinicians to adjust stimulation fields by selecting and placing field shapes representing current density, activation functions, and neuron models, enabling the generation of appropriate electrical stimulation parameters without manually setting individual parameters like electrode configuration, pulse width, and amplitude.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual selection of electrode combinations and stimulation parameters is used, then the clinician can test and evaluate different programs, but the programming process becomes time-consuming and tedious
Solution Approach 1:
The system performs automatic electrode combination selection and parameter optimization through algorithms that evaluate multiple combinations and predict therapeutic outcomes without requiring manual testing by the clinician. The processor automatically identifies optimal electrode configurations based on patient-specific factors and therapeutic goals.
Solution Approach 2:
The patent replaces the manual mechanical process of clinician-based parameter selection with an automated computational system. The processor executes algorithms that automatically select electrode combinations and optimize stimulation parameters, substituting human manual work with automated computing processes.
2Adaptability or versatility
If the number of possible electrode combinations is increased to improve therapy optimization, then the ability to finely adjust therapy is enhanced, but the burden of optimizing device parameters increases
Solution Approach 1:
The system automatically manages the complexity of multiple electrode combinations through self-service algorithms that evaluate all possible configurations and select optimal ones. The processor handles the burden of analyzing numerous combinations without requiring the clinician to manually test each possibility.
Solution Approach 2:
The system dynamically adjusts stimulation parameters including electrode selection, polarities, amplitudes, pulse widths, and pulse rates based on automated evaluation. The processor modifies multiple parameters simultaneously to optimize therapeutic outcomes while managing the complexity of parameter interactions.
3Productivity
If multiple programs are delivered simultaneously or time-interleaved to improve therapy efficacy, then the ability to address different tissue targets is enhanced, but the complexity of programming and parameter management increases
Solution Approach 1:
The system merges multiple electrode combinations and stimulation parameters into integrated programs that can be delivered simultaneously or time-interleaved. The processor coordinates multiple programs, managing their interactions and optimizing their combined therapeutic effect while simplifying the overall programming process.
Data Source
AI summary
The disclosure is directed to a user interface with a menu that facilitates stimulation therapy programming. The user interface displays a representation of the electrical leads implanted in the patient and at least one menu with icons that the user can use to adjust the stimulation therapy. The user may drag one or more field shapes from a field shape selection menu onto the desired location relative to the electrical leads. A manipulation tool menu may also allow the user to adjust the field shapes placed on the electrical leads, which represent the stimulation region. The programmer that includes the user interface then generates electrical stimulation parameter values for the stimulator to deliver stimulation according to the field shapes or field shape groups defined/located by the user. The field shapes may represent different types of stimulation representations, such as current density, activation functions, and neuron models.