title: Gait as a biomarker? Accelerometers reveal that reduced movement quality while walking is associated with Parkinson's disease, ageing and fall risk.
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.
authors.forename: Matthew A
authors.initials: MA
authors.lastname: Brodie
authors.forename: Nigel H
authors.initials: NH
authors.lastname: Lovell
authors.forename: Colleen G
authors.initials: CG
authors.lastname: Canning
authors.forename: Hylton B
authors.initials: HB
authors.lastname: Menz
authors.forename: Kim
authors.initials: K
authors.lastname: Delbaere
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Redmond
authors.forename: Mark
authors.initials: M
authors.lastname: Latt
authors.forename: Daina L
authors.initials: DL
authors.lastname: Sturnieks
authors.forename: Jasmine
authors.initials: J
authors.lastname: Menant
authors.forename: Stuart T
authors.initials: ST
authors.lastname: Smith
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Lord
mesh_terms: D061725:Accelerometry / Q000295:instrumentation / Q000379:methods*; D000058:Accidental Falls / Q000517:prevention & control*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D000465:Algorithms; D015415:Biomarkers / Q000032:analysis; D005684:Gait / Q000502:physiology*; D006257:Head / Q000502:physiology; D006801:Humans; D008875:Middle Aged; D008991:Monitoring, Physiologic; D010300:Parkinson Disease / Q000503:physiopathology*; D010388:Pelvis / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D016138:Walking
chemical_list: D015415:Biomarkers