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Sensors 2012, 12(5), 5791-5814; doi:10.3390/s120505791

Detection of (In)activity Periods in Human Body Motion Using Inertial Sensors: A Comparative Study

1
Department of Signal Theory, Networking and Communications, University of Granada, ETSIIT, C/ Periodista Daniel Saucedo Aranda s/n, E-18071, Granada, Spain
2
Department of Computer Architecture and Computer Technology, University of Granada, ETSIIT, C/Periodista Daniel Saucedo Aranda s/n, E-18071, Granada, Spain
*
Author to whom correspondence should be addressed.
Received: 8 March 2012 / Revised: 7 April 2012 / Accepted: 27 April 2012 / Published: 4 May 2012
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Abstract

Determination of (in)activity periods when monitoring human body motion is a mandatory preprocessing step in all human inertial navigation and position analysis applications. Distinction of (in)activity needs to be established in order to allow the system to recompute the calibration parameters of the inertial sensors as well as the Zero Velocity Updates (ZUPT) of inertial navigation. The periodical recomputation of these parameters allows the application to maintain a constant degree of precision. This work presents a comparative study among different well known inertial magnitude-based detectors and proposes a new approach by applying spectrum-based detectors and memory-based detectors. A robust statistical comparison is carried out by the use of an accelerometer and angular rate signal synthesizer that mimics the output of accelerometers and gyroscopes when subjects are performing basic activities of daily life. Theoretical results are verified by testing the algorithms over signals gathered using an Inertial Measurement Unit (IMU). Detection accuracy rates of up to 97% are achieved. View Full-Text
Keywords: activity detection; inertial sensors; human body monitoring; activity recognition; IMU; ZUPT; calibration activity detection; inertial sensors; human body monitoring; activity recognition; IMU; ZUPT; calibration
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Olivares, A.; Ramírez, J.; Górriz, J.M.; Olivares, G.; Damas, M. Detection of (In)activity Periods in Human Body Motion Using Inertial Sensors: A Comparative Study. Sensors 2012, 12, 5791-5814.

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