A Machine Learning-based Application for Remote Diagnosis of Movement Disorder Symptoms

A diagnostic tool has been developed for

essential tremor (ET), the world’s most common MD, through

analysis of a tablet- or mobile-based drawing task that replaces the need for pen-and-paper

drawing tests while permitting advanced quantitative analysis

of drawing smoothness, pressure applied, and other measures.

Data is securely recorded and stored in the cloud, from

which all analysis is conducted remotely. Several features are

extracted and recursive feature elimination applied to rank the

features’ individual contribution to the classifier. Maximum

cross-validated classification accuracy on a preliminary sample

set is 98.3%. This highly promising new technology has the potential to

substantially alleviate the demands placed on both clinicians

and patients by bringing MD treatment more into line with the

era of personalized medicine.