Abstract
The assessment of latent variables in neurology is mostly achieved using clinical rating scales. Mobile applications can simplify the use of rating scales, providing a quicker quantitative evaluation of these latent variables. However, most health mobile apps do not provide user input validation, they make mistakes at their recommendations, and they are not sufficiently transparent in the way they are run. The goal of the paper was to develop a novel mobile app for cerebellar syndrome quantification and clinical phenotype characterization. SARAEasy is based on the Scale for Assessment and Rating of Ataxia (SARA), and it incorporates the clinical knowledge required to interpret the patient status through the identified phenotypic abnormalities. The quality of the clinical interpretation achieved by the app was evaluated using data records from anonymous patients suffering from SCA36, and the functionality and design was assessed through the development of a usability survey. Our study shows that SARAEasy is able to automatically generate high-quality patient reports that summarize the set of phenotypic abnormalities explaining the achieved cerebellar syndrome quantification. SARAEasy offers low-cost cerebellar syndrome quantification and interpretation for research and clinical purposes, and may help to improve evaluation.
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Acknowledgment
The authors would like to thank Dr. Manuel Arias and Dr. Ángel Sesar for participating in the validation process to test the validity of SARAEasy.
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Maarouf, H., López, V., Sobrido, M.J., Martínez, D., Taboada, M. (2018). SARAEasy: A Mobile App for Cerebellar Syndrome Quantification and Characterization. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10813. Springer, Cham. https://doi.org/10.1007/978-3-319-78723-7_2
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DOI: https://doi.org/10.1007/978-3-319-78723-7_2
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