Neurostimulation Signal Correlation via Intermediary Trigger Events
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Solution Overview
Problem
Biophysical signals in neurostimulation systems, such as local field potentials and tremor activity, are noisy, making data analysis challenging due to the lack of external trigger events for ensemble averaging, which is necessary to increase the signal-to-noise ratio.
Innovation Solution
A neurostimulation system with a first sensor for movement measurements and a second sensor for neural measurements, where one signal serves as a trigger and the other as the signal of interest, allowing the computing device to detect trigger events and use the signal of interest for improved analysis, such as ensemble averaging to enhance signal fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ensemble averaging is performed to increase signal-to-noise ratio, then measurement precision is improved, but device complexity increases due to lack of external trigger events for aligning responses
Solution Approach 1:
The patent uses one biophysical signal (e.g., movement signal from accelerometer) as an intermediary trigger to align and ensemble-average another biophysical signal (e.g., neural signal from LFP sensor). This intermediary trigger event enables systematic alignment of spontaneous neural responses without requiring external triggers, thereby improving signal-to-noise ratio while maintaining a relatively simple implantable device architecture.
2Measurement precision
If multiple sensors are added to provide trigger events for ensemble averaging, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent makes existing sensors in the neurostimulation system serve multiple functions: they not only provide their primary measurement data but also serve as trigger sources for ensemble averaging of other signals. For example, the accelerometer serves both as a motion sensor and as a trigger source for aligning LFP responses, eliminating the need for additional dedicated trigger sensors and reducing overall system complexity.
Data Source
AI summary
The present disclosure provides systems and methods for correlating measurement in neurostimulation systems. A neurostimulation system includes a first sensor configured to acquire movement measurements for a subject, a second sensor configured to acquire neural measurements for the subject, and a computing device communicatively coupled to the first and second sensors. The computing device is configured to receive a movement signal from the first sensor, and receive a neural signal from the second sensor, wherein one of the movement signal and the neural signal is a trigger signal and the other of the movement signal and the neural signal is a signal of interest. The computing device is further configured to detect at least one trigger event in the trigger signal, and use the signal of interest based on the at least one trigger event.