Modeling, Detecting, and Tracking Freezing of Gait in Parkinson Disease Using Inertial SensorsShow others and affiliations
2018 (English)In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 65, no 10, p. 2152-2161Article in journal (Refereed) Published
Abstract [en]
In this paper. we develop new methods to automatically detect the onset and duration of freezing of gait (FOG) in people with Parkinson disease (PD) in real time, using inertial sensors. We first build a physical model that describes the trembling motion during the FOG events. Then, we design a generalized likelihood ratio test framework to develop a two-stage detector for determining the zero-velocity and trembling events during gait. Thereafter, to filter out falsely detected FOG events, we develop a point-process filter that combines the output of the detectors with information about the speed of the foot, provided by a foot-mounted inertial navigation system. We computed the probability of FOG by using the point-process filter to determine the onset and duration of the FOG event. Finally, we validate the performance of the proposed system design using real data obtained from people with PD who performed a set of gait tasks. We compare our FOG detection results with an existing method that only uses accelerometer data. The results indicate that our method yields 81.03% accuracy in detecting FOG events and a threefold decrease in the false-alarm rate relative to the existing method.
Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2018. Vol. 65, no 10, p. 2152-2161
Keywords [en]
Parkinson disease; freezing of gait; inertial sensors; accelerometer; gyroscopes; point-process filter
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-151765DOI: 10.1109/TBME.2017.2785625ISI: 000445233200003PubMedID: 29989948OAI: oai:DiVA.org:liu-151765DiVA, id: diva2:1254169
Note
Funding Agencies|NIH [R01NS077959, K12055931]; Greater St. Louis American Parkinson Disease Association (APDA); APDA Advanced Center for PD Research
2018-10-082018-10-082018-10-08