Implantable pulse generator for providing a neurostimulation therapy using complex impedance measurements
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Solution Overview
Problem
Existing implantable medical devices face challenges in accurately estimating patient-specific impedance for precise neural stimulation, leading to potential undesired side effects and inefficiencies, particularly during MRI scans or exposure to electromagnetic interference (EMI), and lack effective methods to emulate passive discharge without causing unintended neural stimulation.
Innovation Solution
An implantable medical device with measurement circuitry and a programmable neurostimulation system that calculates impedance models using voltage measurements, adjusts therapy based on these models, and employs an active discharge method with exponentially decaying current to mimic passive discharge, maintaining a high impedance loop during MRI or EMI exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional impedance estimation methods are used, then the device structure remains simple, but measurement precision is insufficient leading to inaccurate patient-specific impedance estimation
Solution Approach 1:
The impedance measurement is segmented into multiple frequency points (e.g., 5 different frequencies) rather than a single measurement. This allows construction of a complete impedance spectrum and enables accurate patient-specific impedance estimation through multi-point measurements while maintaining manageable system complexity through modular measurement circuitry.
Solution Approach 2:
The system implements feedback by using measured impedance values to automatically adjust stimulation parameters. The processor continuously monitors impedance at multiple frequencies and adjusts stimulation voltage or current based on the calculated patient-specific impedance, creating a closed-loop control system that improves measurement precision through iterative optimization.
2Manufacturing precision
If segmented electrodes are used to precisely control electrical field, then stimulation precision is improved, but device complexity increases
Solution Approach 1:
The electrode is divided into multiple segmented contacts (e.g., 4 segmented electrodes) that can be independently controlled. This segmentation allows precise control of the electrical field by selecting specific segments based on impedance measurements at different frequencies, achieving accurate neural stimulation while managing complexity through systematic electrode configuration.
Solution Approach 2:
Different segments of the electrode are activated based on local impedance characteristics measured at specific frequency points. The system applies stimulation locally to the most responsive tissue region identified through multi-frequency impedance spectroscopy, optimizing stimulation precision while minimizing unnecessary complexity by activating only relevant electrode segments.
3Loss of energy
If active discharge with exponentially decaying current is used, then battery power usage is minimized, but circuit complexity increases
Solution Approach 1:
The discharge circuit uses dynamic control with exponentially decaying current rather than static constant current discharge. The current magnitude varies over time according to an exponential decay function, optimizing energy efficiency by matching the natural discharge characteristics of the tissue-electrode interface while managing circuit complexity through programmable current control.
Solution Approach 2:
The system changes the discharge current parameter over time, transitioning from high initial current to progressively lower current levels following an exponential decay profile. This parameter variation optimizes battery power usage by delivering necessary discharge function with minimal total energy consumption while using programmable logic to manage the time-varying current control.
4Measurement precision
If multi-frequency impedance spectroscopy is implemented, then patient-specific impedance estimation accuracy is improved, but measurement time increases
Solution Approach 1:
The impedance measurement is performed periodically at multiple frequency points in a systematic sequence rather than continuously. The system cycles through predetermined frequency points (e.g., 5 frequencies) and uses these periodic measurements to construct the impedance spectrum, achieving accurate patient-specific impedance estimation while minimizing measurement time through efficient periodic sampling.
Solution Approach 2:
The system performs preliminary impedance measurements at multiple frequency points before initiating stimulation therapy. These preliminary multi-frequency measurements establish the patient-specific impedance baseline, allowing subsequent stimulation to be optimized without requiring repeated time-consuming measurements during therapy delivery.
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 enhances precision in neural stimulation, reduces undesired side effects, and ensures continuous therapy delivery during MRI or EMI by mimicking passive discharge, minimizing battery power usage and avoiding unintended neural recruitment.
Implementation Method 1
measurement circuitry for determining characteristics of the at least one lead... receive a plurality of voltage measurements associated with the electrodes... calculate component values for an impedance model of the electrodes
Implementation Method 2
employs an active discharge method with exponentially decaying current to mimic passive discharge, maintaining a high impedance loop during MRI or EMI exposure
Data Source
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AI summary
Embodiments are directed to an implantable medical device comprising therapeutic stimulation circuitry for controlling delivery of a medical therapy to a patient, the therapeutic stimulation circuitry having at least one lead having electrodes for delivering the medical therapy. The implantable medical device further comprises measurement circuitry for determining characteristics of the at least one lead, a processor for controlling the IMD according to executable code, and memory for storing data and executable code, wherein the executable code comprises instructions for causing the processor to receive a plurality of voltage measurements associated with the electrodes, and calculate values for an impedance model of the electrode/tissue interface.