Grip Sensor for Spinal Cord Stimulation Parameter Optimization
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Solution Overview
Problem
Current spinal cord stimulation systems rely on a 'guess-and-check' approach to select therapeutically effective parameters, which is inefficient and lacks a well-defined method for identifying optimal parameters for pain relief, and also struggle to quantify patient pain reliably, often requiring subjective measures and consuming time.
Innovation Solution
A grip sensor system that includes pressure and galvanic skin response sensors to provide real-time, quantitative feedback on pain levels during spinal cord stimulation, allowing for the use of programming algorithms to determine effective stimulation parameters, such as tonic, burst, and high-frequency waveforms, that minimize paresthesia and optimize pain relief.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a 'guess-and-check' approach is used to select stimulation parameters, then parameter selection can be performed, but the process is inefficient and lacks a well-defined method for identifying optimal parameters
Solution Approach 1:
The system implements a feedback mechanism where patient pain responses are quantified and fed back to the controller to automatically adjust stimulation parameters. The grip sensor provides real-time feedback on pain levels, enabling the system to iteratively optimize parameters based on actual patient response rather than relying on guess-and-check methods.
Solution Approach 2:
The patent replaces the manual mechanical process of guess-and-check parameter selection with an automated electronic system that uses algorithms to determine optimal parameters. The controller automatically adjusts stimulation parameters based on quantified pain feedback, substituting the manual iterative process with an automated computational approach.
2Measurement precision
If subjective pain measures are used to quantify patient pain, then pain can be assessed, but the process is time-consuming and the reliability of measures is questionable
Solution Approach 1:
The system replaces subjective manual pain assessment with an automated electronic measurement system. The grip sensor and controller automatically quantify pain levels through objective measurements, eliminating the need for patients to subjectively report pain intensity and reducing the time required for assessment.
Solution Approach 2:
The system enables the patient to self-quantify their pain level through the grip sensor, which automatically measures and communicates pain intensity to the controller. This self-service approach eliminates the need for clinician intervention in pain quantification, reducing time loss while improving measurement consistency.
3Reliability
If stimulation amplitude is increased to achieve pain relief, then pain relief can be achieved, but energy consumption increases and battery life is reduced
Solution Approach 1:
The system dynamically changes stimulation parameters based on real-time pain feedback. Rather than using high fixed amplitude, the controller adjusts amplitude, pulse width, and frequency parameters to the minimum effective levels needed to achieve pain relief, thereby reducing energy consumption while maintaining therapeutic effectiveness.
Solution Approach 2:
The system transitions from static fixed-parameter stimulation to dynamic adaptive stimulation. The controller continuously adjusts stimulation parameters in real-time based on patient pain responses, optimizing energy usage by applying only the necessary stimulation intensity required for pain relief at any given moment.
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
Facilitates efficient and effective adjustment of spinal cord stimulation parameters based on patient feedback, enabling semi-autonomous and rapid determination of therapeutically effective settings, reducing the reliance on subjective measures and extending battery life by minimizing energy delivery while achieving substantial paresthesia-free stimulation.
Implementation Method 1
a pressure sensor embedded in the outer shell and communicatively coupled to the electronics enclosure, the pressure sensor configured to measure a grip strength of the patient as SCS is applied to the patient
Implementation Method 2
a plurality of galvanic skin response sensors communicatively coupled to the electronics enclosure and configured to measure an electrical impedance of the skin of the patient as SCS is applied to the patient
Data Source
AI summary
The present disclosure provides a grip sensor for quantifying pain experienced by a patient during spinal cord stimulation (SCS). The grip sensor includes an electronics enclosure, an annular outer shell substantially surrounding the electronics enclosure and sized to be held by the patient, a pressure sensor embedded in the outer shell and communicatively coupled to the electronics enclosure, the pressure sensor configured to measure a grip strength of the patient as SCS is applied to the patient, and a plurality of galvanic skin response sensors communicatively coupled to the electronics enclosure and configured to measure an electrical impedance of the skin of the patient as SCS is applied to the patient.