Session Time: 12:30pm-2:00pm
Location: Exhibit Hall located in Hall B, Level 2
Objective: To test whether measures of everyday sit-to-walk and walk-to-sit differ between patients with Parkinson’s disease (PD) and healthy older adults (HOA) and between mild and severe patients.
Background: A safe and successful transition from sitting to walking and from walking to sitting requires muscle strength, balance and motor control. It is not surprising, therefore, that the ability to smoothly and effectively move from the sitting position to standing or walking is a key component of a number of widely used clinical tests, e.g., the Timed Up and Go test. Previous work demonstrated the utility and added value of assessing transitions measured in a single session in the laboratory using the instrumented Timed Up and Go in patients with PD, however, to date, the possibility of evaluating transitions using a body-fixed sensor continuously worn in the home and community environment has not yet been assessed in patients with PD.
Methods: 99 patients and 38 HOA wore a body-fixed-sensor for 3 days. Sit-to-walk (n=3,286) and walk-to-sit (n=2,858) transitions were analyzed and machine learning algorithm were applied to distinguish between the groups.
Results: Significant differences in transitions were observed between PD patients and HOA, between mild and severe PD, and between mild PD and HOA, both in temporal and distribution features. Machine learning algorithm discriminated patients from HOA (accuracy=92.3%), mild from severe patients (accuracy=89.8%), and mild patients from HOA (accuracy=85.9%). For all group comparisons, accuracy, sensitivity and specificity were much higher when using the transition metrics as compared with more traditional performance-based measures of mobility.
Conclusions: These initial results suggest that body-fixed sensor derived metrics of everyday transitions can characterize disease severity and differentiate mild PD patients from healthy HOA. Perhaps they can help evaluate PD course and conversion from health to a diseased state in at-risk populations.
To cite this abstract in AMA style:J.M. Hausdorff, H. Bernad-Elazari, T. Herman, A. Mirelman, E. Gazit, N. Giladi. Quantifying daily living transitions in patients with Parkinson’s disease using a body-fixed sensor [abstract]. Mov Disord. 2016; 31 (suppl 2). https://www.mdsabstracts.org/abstract/quantifying-daily-living-transitions-in-patients-with-parkinsons-disease-using-a-body-fixed-sensor/. Accessed December 6, 2023.
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MDS Abstracts - https://www.mdsabstracts.org/abstract/quantifying-daily-living-transitions-in-patients-with-parkinsons-disease-using-a-body-fixed-sensor/