Shape tracing app for movement disorder detection

Abstract

Shape tracing tests for the detection and assessment of hand movement disorders are predominantly performed manually in the presence of a clinician. These procedures are therefore labour intensive, expensive, and subjective. Digital tests have been proposed to automate this assessment process, to answer the need of affordable healthcare for all. A straightforward automation solution is a conversion of the shape tracing tests from pen and paper to a mobile device. This study implemements realtime dynamic touch detection on a mid-range tablet for shape tracing. The tracing app developed was tested on 20 movement disorder patients and 10 control subjects. The results convey that the interface allows for successful self-administration of the tests. For all subjects, the accuracy was successfully preserved in the real-time dynamic acquisition of the tracing process.