DISCRIMINATIVE POWER OF SWAY AREA MEASURES FOR FALL RISK IDENTIFICATION IN PARKINSON'S DISEASE

摘要

Over half a million people in the United States are currently diagnosed with Parkinson's disease (PD). People with PD are at an increased risk for falls after the onset of disease due to postural instability and their developed gait disability. In this study, 58 participants diagnosed with idiopathic PD were recruited (age = 68.7 ± 8.5; 44 males and 14 females). Participants included in the study were required to be able to ambulate without assistance and have a Mini-Mental Status Examination (MMSE) score greater than 25. Computerized dynamic posturography was collected using the Sensory Organization Test (SOT) of the SMART EquiTest System (Neurocom International Inc., Clackamas, OR, USA). Assessments occurred while the patients were "on" medication. There are six test conditions performed for SOT, but only the first two tests, (1) Eyes open with fixed surrounding and support and (2) Eyes closed with fixed support, were used in the calculations. The sway area was calculated using two different ellipse algorithms and a convex hull algorithm. We found that the area calculated from all three algorithms during eyes closed tasks could differentiate between fallers and non-fallers. None of the Romberg coefficient calculations could differentiate between fallers and non-faller PD patients while they were "on" medication.