EEG-Guided fMRI Acquisition for Real-Time Task Compliance
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Solution Overview
Problem
Functional magnetic resonance imaging (fMRI) data acquisition is challenged by noise and the need to ensure patient compliance with tasks, as non-compliance often leads to invalid data that can only be identified post-acquisition, requiring costly and time-consuming re-scans.
Innovation Solution
A system combining fMRI with EEG data acquisition and real-time processing to determine patient compliance, providing feedback to ensure valid data collection by analyzing EEG data to identify periods of compliance or non-compliance during fMRI tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fMRI data acquisition is performed without real-time compliance monitoring, then the system is simpler and faster, but the data quality deteriorates due to undetected patient non-compliance
Solution Approach 1:
The patent combines EEG monitoring with fMRI data acquisition into an integrated system. The EEG device monitors patient compliance in real-time during the fMRI scan, and the processing unit correlates EEG signals with fMRI data to identify compliant periods. This merging of two separate monitoring systems enables comprehensive compliance detection without requiring separate procedures, thereby improving data quality while managing system complexity through integration.
Solution Approach 2:
The system implements real-time feedback by continuously analyzing EEG data during fMRI acquisition and providing immediate information about patient compliance status. The processing unit detects compliance based on EEG patterns and can trigger alerts or adjust the acquisition process dynamically. This feedback mechanism allows the system to adapt to patient state changes in real-time, ensuring high data quality by identifying and excluding non-compliant periods from the final dataset.
2Productivity
If fMRI scanning continues without interruption, then productivity is higher, but loss of time increases due to required re-scans when non-compliance is detected
Solution Approach 1:
The system performs preliminary compliance assessment by analyzing EEG data in real-time during the fMRI scan before the scan is fully completed. The processing unit continuously evaluates compliance metrics and identifies compliant time periods ahead of time, allowing the system to determine which portions of the scan are valid without needing to wait for post-processing analysis. This preliminary detection prevents unnecessary completion of non-compliant scans and avoids repeated scanning.
Solution Approach 2:
Real-time feedback from EEG analysis allows the system to immediately detect compliance issues during the scan and adjust the acquisition process accordingly. When non-compliance is detected, the system can alert the operator or automatically adjust parameters, preventing further waste of scanning time. This continuous feedback loop ensures that only compliant data is collected, maximizing productivity by eliminating the need for time-consuming re-scans.
3Reliability
If EEG monitoring is added to fMRI system, then reliability of data selection improves, but device complexity increases
Solution Approach 1:
The patent merges EEG and fMRI systems into a unified platform where both modalities operate simultaneously within the same physical space. The EEG electrodes are positioned on the patient's scalp and connected to recording equipment that is integrated with the fMRI scanner's control system. This merging allows compliance monitoring and brain imaging to be performed concurrently using a single integrated system, improving reliability through multi-modal verification while managing complexity through unified hardware and software architecture.
Solution Approach 2:
The processing unit is designed with multi-functionality, serving both to analyze EEG signals for compliance detection and to process fMRI data for brain activity mapping. This universal processor handles multiple tasks including real-time EEG signal processing, compliance determination, fMRI data correlation, and quality control. By making the processing unit universal rather than specialized for a single function, the system achieves high reliability through comprehensive analysis while avoiding the complexity of having separate dedicated systems for each function.
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
Enables real-time identification and correction of non-compliant fMRI data, minimizing invalid data acquisition and reducing the need for repeat scans by using EEG data to monitor and prompt patients to comply with tasks.
Implementation Method 1
A blood-oxygen-level dependent (BOLD) contrast signal is frequently used, where neural activity in the brain or spinal cord of humans or other animals is mapped by imaging the change in blood flow (hemodynamic response) related to energy use by brain cells
Implementation Method 2
The EEG device is configured to acquire EEG data relating to electrical activity of the brain of the patient
Data Source
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AI summary
The present invention relates to a system (10) for functional magnetic resonance image data acquisition. The system comprises an input unit (20), a magnetic resonance imaging "MRI" device (30), an electroencephalography "EEG" data acquisition device (40), and a processing unit (50). The input unit is configured to provide task based information to a patient, wherein the task based information extends over a period of time. The MRI device is configured to acquire functional magnetic resonance imaging "fMRI" data relating to brain activity of the patient, wherein the fMRI data extends over the period of time. The EEG device is configured to acquire EEG data relating to electrical activity of the brain of the patient, wherein the EEG data extends over the period of time. The processing unit is configured to utilize the task based information that extends over the period of time and the EEG data that extends over the period of time to determine at least one first sub-set period of time over the period of time. The processing unit is configured to determine an action associated with acquisition of the fMRI data over the at least one first sub-set period of time.