Artificial Intelligence in Medicine Conference 2013

Luca Palmerini and Lorenzo Chiari from lead consortium member attended the Artificial Intelligence in Medicine Conference 2013 in Spain to present Classification of early-mild subjects with Parkinson’s disease by using sensor-based measures of posture, gait, and transitions.

The presentation was then was published in a book containing all the proceedings titled Artificial Intelligence in Medicine, Lecture Notes in Computer Science Volume 7885.

The presentation focused on the evaluation of posture, gait, turning, and different kind of transitions, are key components of the clinical evaluation of Parkinson’s disease (PD). The aim of this study is to assess the feasibility of using accelerometers to classify early PD subjects (two evaluations over a 1-year follow-up) with respect to age-matched control subjects. Classifying PD subjects in an early stage would permit to obtain a tool able to follow the progression of the disease from the early phases till the last ones and to evaluate the efficacy of different treatments. Two functional tests were instrumented by a single accelerometer (quiet standing, Timed Up and Go test); such tests carry quantitative information about impairments in posture, gait, and transitions (i.e. Sit-to-Walk, and Walk-to-Sit, Turning). Satisfactory accuracies are obtained in the classification of PD subjects by using an ad hoc wrapper feature selection technique.