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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.



Abstract Determination of inactivity periods when monitoring human body motion is a mandatory preprocessing step in all human inertial navigation and position analysis applications. Distinction of inactivity 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





Autor: Alberto Olivares 1,* , Javier Ramírez 1, Juan M. Górriz 1, Gonzalo Olivares 2 and Miguel Damas 2

Fuente: http://mdpi.com/



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