Automated Spinal Cord Stimulation Programming via Patient Feedback
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Solution Overview
Problem
The manual approach for programming spinal cord stimulation systems with multiple electrodes is time-consuming and lacks accuracy due to the exponential increase in electrode and parameter combinations, making it inefficient for healthcare professionals to establish optimal protocols for pain relief.
Innovation Solution
A system and method utilizing a programming device that performs automated and systematic sweeps to determine electrode perception thresholds and pain areas, using patient feedback to develop a protocol for therapeutic electrical stimulation, thereby reducing the time and increasing the accuracy of protocol establishment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a manual approach is used for programming spinal cord stimulation systems, then the clinician can establish a protocol, but the process becomes time-consuming and inefficient due to the exponential increase in electrode and parameter combinations
Solution Approach 1:
The system enables self-service by allowing the patient to provide feedback about their own sensation in response to electrical stimulation. The processor automatically analyzes this feedback and determines perception thresholds without requiring manual intervention from the clinician for each electrode, thereby reducing programming time while maintaining accuracy
Solution Approach 2:
The system implements feedback by capturing patient responses to electrical stimulation and using this information to automatically adjust and determine optimal stimulation parameters. The processor uses the feedback loop between stimulation delivery and patient response to efficiently identify perception thresholds across multiple electrodes
2Adaptability or versatility
If the number of electrodes in medical leads is increased, then the coverage and effectiveness of pain relief can be improved, but the complexity of programming and the time required to establish protocols increases exponentially
Solution Approach 1:
The system reduces programming complexity by enabling the patient to self-report sensation feedback, which the processor then uses to automatically determine which electrodes provide effective pain relief coverage. This eliminates the need for the clinician to manually test and evaluate each electrode combination
Solution Approach 2:
The system uses patient feedback as input to automatically determine the optimal subset of electrodes for pain relief. The processor analyzes feedback patterns across multiple electrodes to identify which combinations provide the best coverage, thereby managing complexity while maintaining adaptability
3Measurement precision
If a manual approach is used for electrode programming, then the clinician can select parameters, but the accuracy of determining optimal perception thresholds and pain areas is reduced
Solution Approach 1:
The system improves measurement precision by having the patient directly report their own perception of stimulation, eliminating the need for the clinician to manually interpret subtle physiological responses. The patient's direct feedback provides more accurate data for determining perception thresholds
Solution Approach 2:
The system enhances accuracy by implementing a structured feedback mechanism where patient responses to systematic electrode stimulation are captured and analyzed by the processor. This feedback loop enables precise determination of perception thresholds and pain area mapping through automated interpretation of patient reports
Data Source
AI summary
A computer assisted programming method includes ramping up a stimulation current for a plurality of contacts on a lead. Patient feedback is received while the stimulation current is being ramped up. Patient feedback indicates that the patient is beginning to feel stimulation. Based on the patient feedback, amplitude of the stimulation current that resulted in the patient feedback is recorded, and contacts are divided into groups. The contacts are activated one group at a time to the recorded amplitude. For each activated group of contacts, whether the patient can feel stimulation is determined. Thereafter, the target group that caused the patient to feel stimulation is then sub-divided into sub-groups. This process repeats a plurality of cycles until one or more contacts that caused the patient to feel stimulation are identified. The recorded amplitude is assigned as a perception threshold for the identified one or more contacts.