Cortical Spreading Depolarization Detection via Multimodal Signal Fusion
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Solution Overview
Problem
Current methods for detecting cortical spreading depolarization in the brain are inefficient and prone to false positives due to the difficulty in accurately identifying a direct current shift in electroencephalogram (EEG) signals, which can be caused by factors other than cortical spreading depolarization, such as electrode contact changes or noise.
Innovation Solution
A method and system that acquire waveform data from multiple brain sites for direct current components, hemoglobin concentration, and cerebral blood flow, calculate feature amounts like permutation entropy and power density, perform threshold processing to extract event timings, and determine the occurrence of cortical spreading depolarization based on frequency distributions across multiple sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct current shift detection in EEG signals is used to identify cortical spreading depolarization, then detection capability is provided, but false positives increase due to electrode contact changes and noise
Solution Approach 1:
The patent combines multiple signal sources (EEG direct current component, NIRS hemoglobin concentration, and LDF cerebral blood flow) into a unified detection system. By requiring concurrent detection across all three modalities, the system distinguishes true cortical spreading depolarization events from artifacts caused by electrode contact changes or noise, thereby reducing false positives while maintaining detection accuracy.
Solution Approach 2:
The system implements cross-validation feedback mechanisms where each measurement modality serves as a verification for the others. When EEG detects a direct current shift, NIRS and LDF provide feedback to confirm whether this represents a true physiological event or an artifact, enabling real-time discrimination between genuine cortical spreading depolarization and false positives.
2Measurement precision
If multiple signal modalities are combined for detection, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent employs intracranial sensors that serve multiple functions simultaneously - the same sensor array detects EEG electrical signals, NIRS optical signals, and LDF blood flow signals. This multi-functionality approach enables combined modalities detection without proportionally increasing device complexity, as a single integrated sensor system performs all three measurement types.
3Measurement precision
If feature amount calculation with windowing is applied, then event detection precision improves, but processing time increases
Solution Approach 1:
The system applies windowing and feature amount calculation selectively to detected events rather than continuously processing all data. When a potential cortical spreading depolarization event is detected, the system performs detailed feature analysis with windowing on that specific time segment, while using faster methods for routine monitoring, thus balancing precision with processing efficiency.
Data Source
AI summary
A cortical spreading depolarization sensing method includes: acquiring, for each of a plurality of sites of the brain, waveform data indicating a temporal change in one or more types of biological information including at least any one of a direct current component of an electroencephalogram, hemoglobin concentration in the brain, cerebral blood flow, and brain temperature; determining windows set at predetermined time intervals on the waveform data and calculating a predetermined feature amount for each of the windows; performing threshold processing on the feature amounts to extract a timing of the occurrence of an event in which a value of the waveform data temporarily changes due to cortical spreading depolarization; acquiring the frequency distribution of the timings extracted based on the plurality of waveform data acquired in relation to a plurality of sites of the brain; and determining whether cortical spreading depolarization has occurred, based on the frequency distribution.