DocumentCode
141168
Title
Gait as a biomarker? Accelerometers reveal that reduced movement quality while walking is associated with Parkinson´s disease, ageing and fall risk
Author
Brodie, Matthew A. ; Lovell, Nigel H. ; Canning, Colleen G. ; Menz, Hylton B. ; Delbaere, Kim ; Redmond, Stephen J. ; Latt, Mark ; Sturnieks, Daina L. ; Menant, Jasmine ; Smith, Stuart T. ; Lord, Stephen R.
Author_Institution
Neurosci. Res. Australia, UNSW Australia, Sydney, NSW, Australia
fYear
2014
fDate
26-30 Aug. 2014
Firstpage
5968
Lastpage
5971
Abstract
Humans are living longer but morbidity has also increased; threatening to create a serious global burden. Our approach is to monitor gait for early warning signs of morbidity. Here we present highlights from a series of experiments into gait as a potential biomarker for Parkinson´s disease (PD), ageing and fall risk. Using body-worn accelerometers, we developed several novel camera-less methods to analyze head and pelvis movements while walking. Signal processing algorithms were developed to extract gait parameters that represented the principal components of vigor, head jerk, lateral harmonic stability, and oscillation range. The new gait parameters were compared to accidental falls, mental state and co-morbidities. We observed: 1) People with PD had significantly larger and uncontrolled anterioposterior (AP) oscillations of the head; 2) Older people walked with more lateral head jerk; and, 3) the combination of vigorous and harmonically stable gait was demonstrated by non-fallers. Our findings agree with research from other groups; changes in human gait reflect changes to well-being. We observed; different aspects of gait reflected different functional outcomes. The new gait parameters therefore may be complementary to existing methods and may have potential as biomarkers for specific disorders. However, further research is required to validate our observations, and establish clinical utility.
Keywords
accelerometers; biomedical equipment; diseases; gait analysis; geriatrics; medical disorders; medical signal processing; PD; Parkinson´s disease; ageing biomarker; body-worn accelerometers; camera-less method; fall risk; gait parameters; head movements; human gait; lateral harmonic stability; lateral head jerk; older people; pelvis movements; principal components; signal processing algorithms; uncontrolled anterioposterior oscillations; vigor; walking; Acceleration; Accelerometers; Electronic mail; Harmonic analysis; Legged locomotion; Pelvis; Stability analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location
Chicago, IL
ISSN
1557-170X
Type
conf
DOI
10.1109/EMBC.2014.6944988
Filename
6944988
Link To Document