title: Video analysis validation of a real-time physical activity detection algorithm based on a single waist mounted tri-axial accelerometer sensor.
abstract: We have validated a real-time activity classification algorithm based on monitoring by a body worn system which is potentially suitable for low-power applications on a relatively computationally lightweight processing unit. The algorithm output was validated using annotation data generated from video recordings of 20 elderly volunteers performing both a semi-structured protocol and a free-living protocol. The algorithm correctly identified sitting 75.1% of the time, standing 68.8% of the time, lying 50.9% of the time, and walking and other upright locomotion 82.7% of the time. This is one of the most detailed validations of a body worn sensor algorithm to date and offers an insight into the challenges of developing a real-time physical activity classification algorithm for a tri-axial accelerometer based sensor worn at the waist.
authors.forename: Alan K
authors.initials: AK
authors.lastname: Bourke
authors.forename: Espen A F
authors.initials: EA
authors.lastname: Ihlen
authors.forename: Pepijn
authors.initials: P
authors.lastname: Van de Ven
authors.forename: John
authors.initials: J
authors.lastname: Nelson
authors.forename: Jorunn L
authors.initials: JL
authors.lastname: Helbostad
mesh_terms: D061725:Accelerometry / Q000295:instrumentation*; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003199:Computer Systems; D015444:Exercise / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D014741:Video Recording