Title: Assessing motor performance in Parkinson's disease: Applications of hybrid control theory

Speaker: Prof. Meeko Oishi, U. British Columbia

Date/Time: Tuesday, March 1, 2011, 9:00 am              

Location: CSRI Building/Room 90 (Sandia NM)

Brief Abstract: Parkinson's disease (PD) is a progressive neurodegenerative disorder that impairs motor skills, speech, and other voluntary movement.  A lack of the neurochemical dopamine causes tremor, rigidity, bradykinesia (slowness of movement), and postural instability, by altering feedback paths through the basal ganglia and the cerebellum.  Both PD subjects (on and off L-dopa medication) and age-matched controls completed a series of manual pursuit tracking tasks performed concomitantly with brain mapping techniques.  We describe the use of control theoretic measures, obtained from experimentally obtained tracking data, to help elucidate compensatory mechanisms in PD.  With the desired trajectory as the input, and the subject's motor response as the output, second-order LTI models are identified for each subject.  L-dopa medication is shown to reduce the damping ratio and make the range in natural frequency across individuals approach that of normal subjects.  For a hybrid task, in which the dynamics of the task change covertly (the tracking error is attenuated, exaggerated, or unchanged over distinct intervals), multiple model adaptive estimation (MMAE) was used to reverse-engineer whether the subject detected a change in the tracking dynamics.  PD subjects showed considerably more difficulty in detecting the switch (especially off medication), and did not switch into the new mode as quickly as normal subjects.  Our results suggest that switched LTI systems can be an effective method for quantitative assessment of motor performance, as well as yield insight into compensatory mechanisms in Parkinson's disease.

CSRI POC: Danny Rintoul, 505-844-5670