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Monitoring and Analyzing of Circadian and Ultradian Locomotor Activity Based on Raspberry-Pi

Psychology Department—Neuroscience Section Medicine and Psychology Faculty, “Sapienza” University, Via dei Marsi n.78, 00185 Rome, Italy
Department of Physics, University of Illinois at Urbana Champaign, 1110 W Green St., Urbana, 61801 IL, USA
Department of Physics, “Sapienza” University, P.le Aldo Moro 2, 00185 Rome, Italy
Norwegian Polar Institute, Fram Center, Hjalmar Johansen gt.14, NO-9296 Tromsø, Norway
Department of Arctic and Marine Biology, Faculty of Biosciences, Fisheries and Economy, University of Tromsø, NO-9037 Tromsø, Norway
Science Department, University of “Roma Tre”, Via della Vasca Navale 84, 00146 Rome, Italy
Author to whom correspondence should be addressed.
Academic Editors: Simon J. Cox and Steven J. Johnston
Electronics 2016, 5(3), 58;
Received: 1 June 2016 / Revised: 24 August 2016 / Accepted: 12 September 2016 / Published: 15 September 2016
(This article belongs to the Special Issue Raspberry Pi Technology)
A new device based on the Raspberry-Pi to monitor the locomotion of Arctic marine invertebrates and to analyze chronobiologic data has been made, tested and deployed. The device uses infrared sensors to monitor and record the locomotor activity of the animals, which is later analyzed. The software package consists of two separate scripts: the first designed to manage the acquisition and the evolution of the experiment, the second designed to generate actograms and perform various analyses to detect periodicity in the data (e.g., Fourier power spectra, chi-squared periodograms, and Lomb–Scargle periodograms). The data acquisition hardware and the software has been previously tested during an Arctic mission with an arctic marine invertebrate. View Full-Text
Keywords: Raspberry-Pi; I/O (Input/Output) board; data-logger; locomotor activity; single-board computer Raspberry-Pi; I/O (Input/Output) board; data-logger; locomotor activity; single-board computer
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Pasquali, V.; Gualtieri, R.; D’Alessandro, G.; Granberg, M.; Hazlerigg, D.; Cagnetti, M.; Leccese, F. Monitoring and Analyzing of Circadian and Ultradian Locomotor Activity Based on Raspberry-Pi. Electronics 2016, 5, 58.

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