Artif Intell Med - An automated methodology for levodopa-induced dyskinesia: assessment based on gyroscope and accelerometer signals.

Tópicos

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Resumo

JECTIVE: In this study, a methodology is presented for an automated levodopa-induced dyskinesia (LID) assessment in patients suffering from Parkinson's disease (PD) under real-life conditions.METHODS AND MATERIAL: The methodology is based on the analysis of signals recorded from several accelerometers and gyroscopes, which are placed on the subjects' body while they were performing a series of standardised motor tasks as well as voluntary movements. Sixteen subjects were enrolled in the study. The recordings were analysed in order to extract several features and, based on these features, a classification technique was used for LID assessment, i.e. detection of LID symptoms and classification of their severity.RESULTS: The results were compared with the clinical annotation of the signals, provided by two expert neurologists. The analysis was performed related to the number and topology of sensors used; several different experimental settings were evaluated while a 10-fold stratified cross validation technique was employed in all cases. Moreover, several different classification techniques were examined. The ability of the methodology to be generalised was also evaluated using leave-one-patient-out cross validation. The sensitivity and positive predictive values (average for all LID severities) were 80.35% and 76.84%, respectively.CONCLUSIONS: The proposed methodology can be applied in real-life conditions since it can perform LID assessment in recordings which include various PD symptoms (such as tremor, dyskinesia and freezing of gait) of several motor tasks and random voluntary movements.

Resumo Limpo

jectiv studi methodolog present autom levodopainduc dyskinesia lid assess patient suffer parkinson diseas pd reallif conditionsmethod materi methodolog base analysi signal record sever acceleromet gyroscop place subject bodi perform seri standardis motor task well voluntari movement sixteen subject enrol studi record analys order extract sever featur base featur classif techniqu use lid assess ie detect lid symptom classif severityresult result compar clinic annot signal provid two expert neurologist analysi perform relat number topolog sensor use sever differ experiment set evalu fold stratifi cross valid techniqu employ case moreov sever differ classif techniqu examin abil methodolog generalis also evalu use leaveonepatientout cross valid sensit posit predict valu averag lid sever respectivelyconclus propos methodolog can appli reallif condit sinc can perform lid assess record includ various pd symptom tremor dyskinesia freez gait sever motor task random voluntari movement

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