title: A low-power fall detection algorithm based on triaxial acceleration and barometric pressure.
abstract: This paper proposes a low-power fall detection algorithm based on triaxial accelerometry and barometric pressure signals. The algorithm dynamically adjusts the sampling rate of an accelerometer and manages data transmission between sensors and a controller to reduce power consumption. The results of simulation show that the sensitivity and specificity of the proposed fall detection algorithm are both above 96% when applied to a previously collected dataset comprising 20 young actors performing a combination of simulated falls and activities of daily living. This level of performance can be achieved despite a 10.9% reduction in power consumption.
authors.forename: Changhong
authors.initials: C
authors.lastname: Wang
authors.forename: Michael R
authors.initials: MR
authors.lastname: Narayanan
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Lord
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Redmond
authors.forename: Nigel H
authors.initials: NH
authors.lastname: Lovell
mesh_terms: D000054:Acceleration; D061725:Accelerometry; D000058:Accidental Falls; D000465:Algorithms; D006801:Humans; D011312:Pressure; D012815:Signal Processing, Computer-Assisted