Automatic detection of wakefulness and rest intervals in actigraphic signals: A data-driven approach

• Published in: Medical engineering & physics Vol. 36; no. 12; pp. 1585 - 1592
• Main Authors: Martín-Martínez, D., Casaseca-de-la-Higuera, P., Andrés-de-Llano, J.M., Garmendia-Leiza, J.R., Alberola-López, S., Alberola-López, C.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.12.2014
• Subjects: Actigraphy; Actigraphy - methods; Algorithms; Child; Expectation–maximization algorithm; Humans; Intervals; Masks; Maximization; Normal Distribution; Pattern Recognition, Automated - methods; Probability density function; Radiology; Rest; Signal Processing, Computer-Assisted; Splitting; Statistics, Nonparametric; Thresholds; Wakefulness; Wakefulness/Rest detection; Actigraphy; Probability density function; Wakefulness/Rest detection; Expectation–maximization algorithm

Actigraphy is an useful tool for evaluating the activity pattern of a subject; activity registries are usually processed by first splitting the signal into its wakefulness and rest intervals and then analyzing each one in isolation. Consequently, a preprocessing stage for such a splitting is needed....