Detection of (In)activity Periods in Human Body Motion Using Inertial Sensors: A Comparative Study Olivares, Alberto Ramírez Pérez De Inestrosa, Javier Olivares Ruiz, Gonzalo Damas Hermoso, Miguel Activity detection Inertial sensors Human body monitoring Activity recognition IMU ZUPT Calibration This article belongs to the Special Issue Select papers from UCAmI 2011 - the 5th International Symposium on Ubiquitous Computing and Ambient Intelligence (UCAmI'11) 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. 2013-10-18T09:54:35Z 2013-10-18T09:54:35Z 2012 info:eu-repo/semantics/article Olivares, A.; et al. Detection of (In)activity Periods in Human Body Motion Using Inertial Sensors: A Comparative Study. Sensors, 12(5): 5791-5814 (2012). [http://hdl.handle.net/10481/28451] 1424-8220 http://hdl.handle.net/10481/28451 10.3390/s120505791 eng http://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License MDPI