Head Alignment Detection for Unsupervised Cognitive Assessment
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Solution Overview
Problem
Current cognitive tests for attentional deficits, such as hemispatial neglect, require a trained professional to ensure the patient's head remains aligned with the test image, limiting the ability to conduct unsupervised assessments and reducing the frequency of recovery monitoring.
Innovation Solution
A system comprising a user interaction subsystem, camera, and analysis subsystem that presents a test image on a display, captures the geometric relation between the subject's head and display, analyzes deviations, and outputs data to compensate for misalignments, allowing for unsupervised assessments without a trained professional.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a trained professional is present during the assessment to ensure proper head alignment, then measurement precision is improved, but device complexity and ease of operation are worsened due to requiring professional supervision
Solution Approach 1:
The system enables patients to perform the assessment independently without professional supervision. The camera automatically detects head alignment and provides real-time feedback, allowing the patient to self-correct their position. This transforms a previously professional-only task into a self-service activity that can be performed at home.
Solution Approach 2:
The system incorporates real-time feedback through visual indicators (such as colored zones or alignment markers) that show the patient whether their head is properly aligned with the display. This continuous feedback loop enables the patient to maintain correct positioning throughout the assessment without professional intervention.
2Measurement precision
If a trained professional is required for the assessment, then measurement precision is improved, but productivity is worsened due to reduced monitoring frequency
Solution Approach 1:
By enabling unsupervised self-administration of the cognitive tests, the system removes the bottleneck of professional availability. Patients can complete assessments at home on their own schedule, allowing for frequent monitoring without requiring therapist time for each session.
Solution Approach 2:
The system allows for continuous monitoring of patient recovery by enabling frequent assessments in the home setting. Rather than discrete clinic visits, the therapy process becomes continuous with regular data collection points, maintaining measurement precision while dramatically increasing productivity.
3Ease of operation
If the patient's head position is not properly aligned with the display, then measurement precision deteriorates, but ease of operation is improved by allowing more freedom of movement
Solution Approach 1:
The camera system continuously monitors head position and provides real-time visual feedback to guide the patient into the correct alignment zone. This feedback mechanism maintains measurement precision by ensuring proper positioning while preserving patient freedom through intuitive, self-guided adjustment rather than rigid constraints.
Solution Approach 2:
The system dynamically adjusts and monitors head position throughout the assessment rather than requiring fixed positioning. The feedback system adapts to patient movements and guides them back to the optimal position, maintaining precision while allowing natural movement patterns during the test.
Data Source
AI summary
A system and method are provided for use in the assessment of an attentional deficit. During the assessment, a test image is presented to a subject on a display. A camera image is obtained from a camera which is indicative of a geometric relation between the head of the subject and the display during the assessment. The camera image is analyzed to determine a deviation in the geometric relation between the head of the subject and the display from a reference geometric relation. Deviation data is then generated and output which is indicative of the deviation. Advantageous uses of the deviation data include providing visual feedback to the user, adjusting the test image, and taking the deviation into account when processing test data of the assessment. Advantageously, the need for a trained professional to be present during the assessment is reduced or avoided.