A novel automatic method for monitoring

(2010) A novel automatic method for monitoring Tourette motor tics through a wearable device. A novel automatic method for monitoring Tourette motor tics through a wearable device. This version is made available in accordance with publisher policies. Please cite only the published version using the reference above. Financial disclosure: none of the authors presents conflict of interests or has received financial support for carrying out the present research. ABSTRACT The aim of this study was to propose a novel automatic method for quantifying motor-tics caused by the Tourette Syndrome (TS). In this preliminary report, the feasibility of the monitoring process was tested over a series of standard clinical trials in a population of 12 subjects affected by TS. A wearable instrument, with an embedded three-axial accelerometer was used to detect and classify motor tics during standing and walking activities. An algorithm was devised to analyze acceleration data by: eliminating noise; detecting peaks connected to pathological events; classifying intensity and frequency of motor tics into quantitative scores. These indexes were compared with the video-based ones, provided by expert clinicians, which were taken as the gold-standard. Sensitivity, specificity and accuracy of tic detection were estimated, and an agreement analysis was performed through the least square regression and the Bland-Altman test. The tic recognition algorithm showed sensitivity=80.8±8.5% (mean±sd), specificity=75.8±17.3%, accuracy=80.5±12.2%. The agreement study showed that automatic detection tended to overestimate the number of tics occurred. Though, it appeared this may be a systematic error due to the different recognition principles of the wearable and video-based systems. Furthermore there was substantial concurrency with the gold-standard in estimating the severity indexes. The proposed methodology gave promising performances in terms of automatic motor-tics detection and classification in a standard clinical context. The system may provide physicians with a quantitative aid for TS assessment. Further developments will focus on the extension of its application to everyday long term monitoring out of clinical environments.