| Literature DB >> 25571201 |
Xiaoqing Jia, Nathalie Duroseau, Vivian Chan, Christina Ciraco, Rui Wang, Sarah Mostafa Nia, Kayla Ho, John P Govindavari, Farshid Delgosha, Thomas Chan, Kathleen Mangunay Pergament, Bhuma Krishnamachari, Aydin Farajidavar.
Abstract
Two tri-axial accelerometers were placed on the wrists (one on each hand) of the patients with Parkinson's disease (PD) and a non-PD control group. Subjects were asked to perform three of the upper extremity motor function tasks from the Unified Parkinson's Disease Rating Scale (UPDRS) test. The tasks were: 1) finger tapping, 2) opening and closing of palms, and 3) pronation-supination movements of the forearms. The inertia signals were wirelessly received and stored on a computer for further off-line analysis. Various features such as range, standard deviation, entropy, time to accomplish the task, and maximum frequency present in the signal were extracted and compared. The results showed that among the studied population, "standard deviation", "range", "entropy", "time" and "max frequency" are the best to worst features, respectively, to distinguish between the non-PD and PD subjects. Furthermore, using the mentioned features, it is more probable to distinguish between the non-PD and PD subjects from tasks 2 and 3 as opposed to task 1.Entities:
Mesh:
Year: 2014 PMID: 25571201 DOI: 10.1109/EMBC.2014.6944833
Source DB: PubMed Journal: Conf Proc IEEE Eng Med Biol Soc ISSN: 1557-170X