Gyroscopic corrections improve wearable sensor data prior to measuring dynamic sway in the gait of people with Multiple Sclerosis
Matthew A. D. Brodie,
Michael Psarakis and
Phu Hoang
Computer Methods in Biomechanics and Biomedical Engineering, 2016, vol. 19, issue 12, 1339-1346
Abstract:
Accelerometers are incorporated into many consumer devices providing new ways to monitor gait, mobility, and fall risk. However, many health benefits have not been realised because of issues with data quality that results from gravitational ‘cross-talk’ when the wearable device is tilted. Here we present an adaptive filter designed to improve the quality of accelerometer data prior to measuring dynamic pelvic sway patterns during a six minute walk test in people with and without Multiple Sclerosis (MS). Optical motion capture was used as the gold standard. Improved wearable device accuracy (≤4.4% NRMSE) was achieved using gyroscopic corrections and scaling filter thresholds by step frequency. The people with MS presented significantly greater pelvis sway range to compensate for their lower limb weaknesses and joint contractures. The visualisation of asymmetric pelvic sway in people with MS illustrates the potential to better understand their mobility impairments for reducing fall risk.
Date: 2016
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2016.1140747 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:19:y:2016:i:12:p:1339-1346
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20
DOI: 10.1080/10255842.2016.1140747
Access Statistics for this article
Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton
More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().