Spinal Cord Stimulation Feedback Control Using ECAP Morphology
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Solution Overview
Problem
Existing spinal cord stimulation systems lack effective closed-loop control mechanisms to adapt stimulation parameters in response to changes in the environment between the electrodes and neural tissue, such as variations in cerebrospinal fluid thickness, leading to suboptimal therapeutic outcomes.
Innovation Solution
Incorporating sensing electrodes to monitor neural responses and using feedback control algorithms, such as Kalman filters and PID control models, to adjust stimulation parameters based on sensed neural features, including amplitude, shape, and environmental changes, thereby enhancing the precision of spinal cord stimulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If open-loop spinal cord stimulation is used, then the device complexity is low, but the therapeutic efficacy is suboptimal due to inability to adapt to environmental changes
Solution Approach 1:
The patent implements closed-loop control by sensing neural responses (such as ECAPs) and using this feedback information to adjust stimulation parameters. The system continuously monitors the neural tissue response and modifies stimulation amplitude, pulse width, or frequency based on the sensed feedback, thereby adapting to environmental changes like CSF thickness variations and maintaining optimal therapeutic efficacy.
Solution Approach 2:
The stimulation system performs self-adjustment by automatically sensing its own output effects on neural tissue and correcting stimulation parameters without external intervention. The implanted device autonomously monitors neural responses and modifies its own stimulation delivery, enabling adaptive therapy while the patient performs normal activities.
2Adaptability or versatility
If stimulation parameters are fixed, then the ease of operation is high, but the adaptability to environmental changes is poor
Solution Approach 1:
The patent transforms fixed stimulation parameters into dynamic, adjustable parameters that automatically adapt to environmental changes. The system continuously modifies stimulation amplitude, pulse width, or frequency based on real-time sensing of neural responses, enabling the device to adapt to varying CSF thickness, electrode position, and tissue properties without requiring manual reprogramming.
Solution Approach 2:
The system changes stimulation parameters (amplitude, pulse width, frequency) based on sensed neural response characteristics. When environmental changes are detected through feedback sensing, the control algorithm automatically adjusts one or more stimulation parameters to maintain optimal therapeutic effect, thereby achieving adaptability without complex manual operation.
3Measurement precision
If sensing electrodes are added for neural response monitoring, then the measurement precision of neural features improves, but the device complexity increases
Solution Approach 1:
The patent makes the stimulation electrodes multi-functional by using them for both delivering electrical stimulation and sensing neural responses. The same electrode contacts that provide therapeutic stimulation also serve as sensing electrodes to detect evoked compound action potentials and other neural features, thereby achieving precise measurement without adding separate sensing electrode arrays.
Solution Approach 2:
The system merges the stimulation and sensing functions into a single integrated circuit and electrode structure. The stimulation circuitry and sensing circuitry share common electrodes and are integrated within the same implanted pulse generator, reducing overall device complexity while enabling precise neural response measurement through the combined functionality.
Data Source
AI summary
Methods and systems for using sensed neural responses for informing aspects of stimulation therapy are disclosed. For example, features of evoked neural responses, such as evoked compound action potentials (ECAPs) can be used for closed-loop feedback control of stimulation parameters. Aspects of the disclosed methods and systems can differentiate between changes in the sensed neural responses that are caused by the environment at stimulating electrodes and changes in the neural responses that are caused by the environment at sensing electrodes. Embodiments determine changes in the morphology of the neural responses, which morphology changes indicate a degree of change in the stimulating environment. Algorithms and systems for assigning and tracking likelihoods for underlying electrode-tissue changes based on sensed neural responses are disclosed. The feedback control modality may be updated based on such likelihoods. Also disclosed are methods and systems for determining which features of evoked neural responses are more sensitive to changes in the stimulating environment and less sensitive to changes in the sensing environment.