Rogan Magee1, Benjamin Yang1, Jeff Ratliff1. 1. Department of Neurology, Sidney Kidney Medical College at Thomas Jefferson University, Philadelphia, PA, USA.
Abstract
BACKGROUND: We built a web-based application of the Archimedes spiral exam that implements clinically validated spiral metrics and tested drawing instructions to define a clinical workflow. METHODS: We designed an HTML5 and Javascript implementation of the spiral exam to run on mobile touchscreen devices. We then recruited 10 volunteers each for 2 experiments designed to validate the programmed spiral metrics and assess how instructions or drawing implement affect the results. In task one, volunteers drew 5 spirals each while following 6 different instruction sets (n=30 spirals each, n=300 spirals total) that varied by support of the drawing hand and tracing condition (either tracing a spiral template, drawing in-between it, or freehand). In task two, volunteers drew 5 spirals each while following 2 instruction sets and drawing using a stylus or their dominant index finger (n=20 spirals each, n=200 spirals total). RESULTS: Principal components analysis of calculated metrics revealed that the experiments grouped by instruction set and by subject. Mean Euclidean distance between experiments represented as 11-dimensional vectors revealed that consistency varied among instruction tasks and that drawing with a stylus produced more consistent results than did using the dominant index finger. Using experimental data and simulated abnormal spirals, we designed a decision support system that accurately identifies potentially abnormal spirals. CONCLUSIONS: We built and validated a robust digital implementation of the Archimedes spiral exam and recommend a sensitive and specific workflow on the basis of data gathered from healthy volunteers. 2022 mHealth. All rights reserved.
BACKGROUND: We built a web-based application of the Archimedes spiral exam that implements clinically validated spiral metrics and tested drawing instructions to define a clinical workflow. METHODS: We designed an HTML5 and Javascript implementation of the spiral exam to run on mobile touchscreen devices. We then recruited 10 volunteers each for 2 experiments designed to validate the programmed spiral metrics and assess how instructions or drawing implement affect the results. In task one, volunteers drew 5 spirals each while following 6 different instruction sets (n=30 spirals each, n=300 spirals total) that varied by support of the drawing hand and tracing condition (either tracing a spiral template, drawing in-between it, or freehand). In task two, volunteers drew 5 spirals each while following 2 instruction sets and drawing using a stylus or their dominant index finger (n=20 spirals each, n=200 spirals total). RESULTS: Principal components analysis of calculated metrics revealed that the experiments grouped by instruction set and by subject. Mean Euclidean distance between experiments represented as 11-dimensional vectors revealed that consistency varied among instruction tasks and that drawing with a stylus produced more consistent results than did using the dominant index finger. Using experimental data and simulated abnormal spirals, we designed a decision support system that accurately identifies potentially abnormal spirals. CONCLUSIONS: We built and validated a robust digital implementation of the Archimedes spiral exam and recommend a sensitive and specific workflow on the basis of data gathered from healthy volunteers. 2022 mHealth. All rights reserved.
Entities:
Keywords:
Archimedes spiral; mobile device; movement disorders; tremor; web application
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