{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T12:54:04Z","timestamp":1774184044032,"version":"3.50.1"},"reference-count":21,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2010,7,28]],"date-time":"2010-07-28T00:00:00Z","timestamp":1280275200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Movement Disorders"],"published-print":{"date-parts":[[2010,9,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The aim of this study was to propose a novel automatic method for quantifying motor\u2010tics 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\u2010axial 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; and classifying intensity and frequency of motor tics into quantitative scores. These indexes were compared with the video\u2010based ones provided by expert clinicians, which were taken as the gold\u2010standard. Sensitivity, specificity, and accuracy of tic detection were estimated, and an agreement analysis was performed through the least square regression and the Bland\u2010Altman test. The tic recognition algorithm showed sensitivity = 80.8% \u00b1 8.5% (mean \u00b1 SD), specificity = 75.8% \u00b1 17.3%, and accuracy = 80.5% \u00b1 12.2%. The agreement study showed that automatic detection tended to overestimate the number of tics occurred. Although, it appeared this may be a systematic error due to the different recognition principles of the wearable and video\u2010based systems. Furthermore, there was substantial concurrency with the gold\u2010standard in estimating the severity indexes. The proposed methodology gave promising performances in terms of automatic motor\u2010tics 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\u2010term monitoring out of clinical environments. \u00a9 2010 Movement Disorder Society<\/jats:p>","DOI":"10.1002\/mds.23188","type":"journal-article","created":{"date-parts":[[2010,7,28]],"date-time":"2010-07-28T20:15:35Z","timestamp":1280348135000},"page":"1967-1972","source":"Crossref","is-referenced-by-count":13,"title":["A novel automatic method for monitoring Tourette motor tics through a wearable 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