Document
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Accelerometers; Automatic motor tic detection; Automatic screening; Decision support system; Tourette syndrome Alternative approach; Automatic Detection; Automatic motor tic detection; Automatic screening; Clinical environments; Clinical observation; Decision supports; Energy operators; Median filter; Neurological disorders; Time variant; Tourette syndrome; Triaxial accelerometer; Accelerometers; Artificial intelligence; Decision making; Decision theory; Signal processing; Signal to noise ratio; Video recording; Decision support systems; acceleration; adolescent; adult; algorithm; ambulatory monitoring; article; automated pattern recognition; decision support system; female; Gilles de la Tourette syndrome; human; male; methodology; middle aged; pathophysiology; regression analysis; sensitivity and specificity; tic; videorecording; Acceleration; Adolescent; Adult; Algorithms; Decision Support Systems, Clinical; Female; Humans; Male; Middle Aged; Monitoring, Ambulatory; Pattern Recognition, Automated; Regression Analysis; Sensitivity and Specificity; Tics; Tourette Syndrome; Video Recording
Automatic detection of tic activity in the Tourette Syndrome
This study presents a simple decision-support system for the detection of tic events during the Tourette Syndrome (TS). The system is based on a triaxial accelerometer placed on the patient's trunk. TS is a neurological disorder that emerges during childhood and that is characterized by a large spectrum of involuntary/compulsive movements and sounds. 12 subjects with chronic TS participated in the study and the tic events were both measured by the proposed device and visually classified through video recording. 3D-acceleration timeseries were combined through a module operator and their noise was eliminated by a median filter. Signal to noise ratio was improved by a nonlinear energy operator. Finally, a timevariant threshold was used to detect tic events. The automatic tic recognition showed a performance around 80 %25 in terms of sensitivity, specificity and accuracy. In conclusion, this simple, automatic and unobtrusive method offers an alternative approach to quantitatively assess the tic events in clinical and non clinical environments. This overcomes the limitations of the current motor tic evaluation which is done by clinical observation and/or video-inspection in specialized neurological centres. © 2010 IEEE.
This study presents a simple decision-support system for the detection of tic events during the Tourette Syndrome (TS). The system is based on a triaxial accelerometer placed on the patient%27s trunk. TS is a neurological disorder that emerges during childhood and that is characterized by a large spectrum of involuntary/compulsive movements and sounds. 12 subjects with chronic TS participated in the study and the tic events were both measured by the proposed device and visually classified through video recording. 3D-acceleration timeseries were combined through a module operator and their noise was eliminated by a median filter. Signal to noise ratio was improved by a nonlinear energy operator. Finally, a timevariant threshold was used to detect tic events. The automatic tic recognition showed a performance around 80 %25 in terms of sensitivity, specificity and accuracy. In conclusion, this simple, automatic and unobtrusive method offers an alternative approach to quantitatively assess the tic events in clinical and non clinical environments. This overcomes the limitations of the current motor tic evaluation which is done by clinical observation and/or video-inspection in specialized neurological centres. © 2010 IEEE.
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