Neurostimulation Efficacy Assessment Using ECAP Statistical Measures
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current spinal cord stimulation (SCS) therapies for conditions like chronic pain and Parkinson's disease face high failure rates due to the lack of reliable methods to predict therapeutic efficacy, leading to unnecessary trials and subsequent explantations, with existing assessments relying on subjective measures like the Visual Analogue Scale (VAS).
Innovation Solution
A system and method for assessing therapeutic efficacy through neuromodulation devices that deliver electrical stimulation, capture neural responses, and process these responses to calculate statistical measures of neural activation, providing an objective indication of efficacy using ECAP amplitude measures and normalization techniques to guide therapy optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subjective outcome measures like Visual Analogue Scale (VAS) are used to assess SCS efficacy, then the assessment method is simple to implement, but the measurement precision and reliability are insufficient leading to high failure rates
Solution Approach 1:
The patent replaces subjective mechanical/paper-based assessment methods (VAS scales) with objective electrophysiological measurement systems that detect neural responses electronically. This substitution enables precise quantification of therapeutic efficacy through ECAP amplitude measurements and statistical analysis, directly resolving the contradiction between measurement precision and implementation simplicity.
Solution Approach 2:
The patent introduces an intermediary measurement system that captures neural responses as intermediate data between stimulus delivery and efficacy assessment. This intermediary layer of objective neural response data serves as a mediator that translates complex physiological effects into quantifiable statistical measures, improving assessment accuracy without requiring direct complex intervention.
2Reliability
If SCS trials are performed without reliable prediction methods, then patient selection can be done quickly, but the reliability of therapeutic outcome prediction is poor resulting in high explantation rates
Solution Approach 1:
The patent applies preliminary action by performing neural response measurements and statistical analysis during the trial period to predict future therapeutic outcomes before permanent implantation. This preliminary assessment of ECAP characteristics and neural response patterns enables early identification of likely responders, improving predictive reliability while potentially shortening the trial period needed for accurate prediction.
Solution Approach 2:
The patent implements feedback by continuously measuring neural responses during stimulation and using statistical analysis to provide feedback on predicted therapeutic efficacy. This feedback loop allows clinicians to assess likely outcomes based on objective neural activation patterns, improving the reliability of patient selection and reducing unnecessary trials.
3Measurement precision
If statistical measures of neural activation are calculated from multiple recordings, then the measurement precision of therapeutic efficacy is improved, but the complexity of data processing increases
Solution Approach 1:
The patent applies parameter changes by transforming multiple raw neural response recordings into standardized statistical parameters (mean, standard deviation, coefficient of variation). This parameter transformation process converts complex time-series data into concise quantitative measures that improve measurement precision while managing processing complexity through established statistical methods.
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 improves the success rate of SCS by predicting responders and optimizing therapy settings, reducing trial failures and explantations, and maintaining effective neural activation within a therapeutic window, thereby enhancing pain management.
Implementation Method 1
measurement circuitry configured to capture recordings of neural responses evoked by the electrical neurostimulation therapy
Implementation Method 2
the processor configured to process the recordings of the neural responses evoked by the delivered electrical neurostimulation therapy, in order to obtain a plurality of measures of neural activation
Data Source
Figure 1~2
Figure 3~4A
Figure 4B
AI summary
Assessing therapeutic efficacy of electrical neurostimulation therapy. A neuromodulation device delivers the electrical neurostimulation therapy. Measurement circuitry captures recordings of neural responses evoked by the electrical neurostimulation therapy. A processor processes the recordings of the neural responses in order to obtain a plurality of measures of neural activation in response to a plurality of stimuli delivered over time, and calculates from the plurality of measures of neural activation at least one statistical measure of neural activation. From the at least one statistical measure the processor produces and outputs an indication of therapeutic efficacy.