3D Landmark Alignment for Precise Neurophysiological Sensors
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Solution Overview
Problem
Existing methods for aligning neurophysiological sensors, such as EEG sensors, on the head are inefficient and lack precision, leading to suboptimal data collection and analysis.
Innovation Solution
A method and system utilizing 3D imaging and machine learning to align neurophysiological sensors by capturing facial and wearable device images, identifying landmarks, and adjusting sensor positions to match scalp coordinates, facilitated by actuators and displacement sensors, with machine learning algorithms to enhance precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual techniques are used to position EEG electrodes on the head, then the process is simple and requires minimal equipment, but the alignment precision and reproducibility are insufficient
Solution Approach 1:
The patent introduces 3D imaging systems, facial landmark detection algorithms, and machine learning models as intermediary tools between the operator and the electrode placement process. These intermediaries automatically capture head geometry, identify anatomical landmarks, and calculate optimal electrode positions, thereby significantly improving alignment precision while the system manages the complexity through automated processing pipelines
Solution Approach 2:
The patent replaces manual mechanical positioning methods with automated computer vision and machine learning systems. Instead of relying on operators to physically locate and mark anatomical landmarks on the subject's head, the system uses 3D facial imaging and AI algorithms to automatically detect landmarks and compute electrode coordinates, thereby improving precision while the software infrastructure handles the complexity
2Measurement precision
If automated or semi-automated techniques are used to position EEG electrodes, then the alignment precision is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The patent creates a multi-functional integrated system that combines 3D facial imaging, landmark detection, head model generation, and electrode position calculation into a single unified platform. This universal system handles multiple tasks that would otherwise require separate devices and procedures, thereby improving precision while consolidating complexity into one coordinated system rather than multiple independent components
Solution Approach 2:
The patent performs preliminary actions by capturing 3D facial images and generating head models before the actual electrode placement process. The system pre-identifies all anatomical landmarks and pre-calculates optimal electrode positions based on the captured geometry, allowing the physical placement to proceed smoothly with minimal real-time decision-making, thereby improving precision while the preprocessing manages the computational complexity
3Measurement precision
If 3D imaging and machine learning are used to align neurophysiological sensors, then the alignment precision and data accuracy are significantly improved, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary 3D facial scanning and landmark detection before sensor placement, generating a complete head model and predetermined electrode positions in advance. This upfront processing allows the actual sensor alignment to proceed quickly by simply following the pre-calculated coordinates, thereby improving final precision while the time investment is concentrated in the initial setup phase rather than during repeated adjustments
Solution Approach 2:
The patent creates a digital 3D copy of the subject's head geometry and anatomical landmarks, which serves as a virtual template for electrode placement. This digital model can be processed computationally to determine optimal sensor positions, and the results can be reused for multiple sensing sessions without repeating the full 3D scanning and analysis, thereby improving precision through accurate digital modeling while reducing repeated processing time
Data Source
AI summary
A method of aligning a wearable device having a set of neurophysiological sensors on a head of a subject, comprises capturing a three-dimensional (3D) facial image of the subject, and a 3D image of the wearable device while being placed on a scalp of the subject. Facial landmarks are identified on the facial image, and the images are co-registered based at least in part on the identified facial landmarks. A trained machine learning procedure is fed with the facial landmarks to produce coordinates of scalp landmarks, and an alignment of the wearable device on the scalp is corrected to match coordinates of the scalp landmarks with locations of the neurophysiological sensors.