Square Wave Jerk Detection in Oculomotor Diagnosis
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Solution Overview
Problem
Current methods lack effective tools for differentiating eye movement patterns between healthy individuals and those with neurological diseases, particularly for diagnosing oculomotor and neurological disorders like progressive supranuclear palsy, due to the prevalence of square wave jerks in both groups.
Innovation Solution
A method and apparatus that characterize square wave jerks by identifying and analyzing pairs of saccades for direction, magnitude, and temporal relationships, using high-resolution eye tracking systems to distinguish between healthy and PSP patients through specific criteria such as direction difference, magnitude similarity, and inter-saccadic intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional eye movement analysis methods are used, then the evaluation process is simple, but the ability to differentiate between healthy individuals and those with neurological diseases is insufficient
Solution Approach 1:
The patent segments the eye movement analysis into distinct components: detecting individual saccades, identifying pairs of consecutive saccades, evaluating direction opposition, comparing magnitude similarity, and measuring temporal intervals. This segmentation transforms a complex differentiation problem into manageable analytical steps, enabling precise identification of square wave jerks while maintaining systematic analysis.
Solution Approach 2:
The patent employs multiple parameters to characterize square wave jerks, including direction difference, magnitude ratio, and inter-saccadic time intervals. By analyzing changes across these multiple parameters rather than relying on a single metric, the method achieves superior differentiation accuracy between healthy individuals and neurological disease patients.
2Reliability
If square wave jerks are analyzed without specific criteria, then the analysis process is faster, but the diagnostic accuracy for neurological diseases decreases
Solution Approach 1:
The patent establishes predetermined criteria for square wave jerk identification before analysis begins, including direction opposition requirements, magnitude comparability thresholds, and temporal interval ranges. These preliminary criteria enable rapid automated filtering of saccade pairs during analysis, achieving both high diagnostic accuracy and efficient processing without requiring complex post-processing evaluation.
3Measurement precision
If detailed characterization of square wave jerks is performed, then differential diagnosis capability is improved, but the complexity of the detection system increases
Solution Approach 1:
The patent implements automated algorithms that self-evaluate saccade pairs against predetermined criteria without requiring manual intervention. The system automatically detects saccades, pairs them consecutively, evaluates direction and magnitude relationships, and identifies square wave jerks based on temporal intervals. This self-service automation achieves detailed characterization while minimizing the operational complexity burden on users.
Data Source
AI summary
A method and apparatus are provided for characterizing square wave jerks in the eye movements of a person, which may provide a powerful tool in the differential diagnosis of oculomotor and neurological disease. The method includes the steps of a) providing a sequence of saccades, b) identifying pairs of consecutive saccades of the sequence, c) determining whether each saccade of each identified pair is opposite the direction of the other saccade and, if not, then discarding the pair, d) determining whether a magnitude of each saccade of each identified pair is comparable and, if not, then discarding the pair, e) determining whether the pair of saccades of each identified pair are temporally related by a predetermined time period and, if not, then discarding the pair and f) collecting any remaining pairs of saccades as square wave jerks.