Detection of (In)activity Periods in Human Body Motion Using Inertial Sensors: A Comparative Study
Metadatos
Afficher la notice complèteAuteur
Olivares, Alberto; Ramírez Pérez De Inestrosa, Javier; Olivares Ruiz, Gonzalo; Damas Hermoso, MiguelEditorial
MDPI
Materia
Activity detection Inertial sensors Human body monitoring Activity recognition IMU ZUPT Calibration
Date
2012Referencia bibliográfica
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]
Patrocinador
This work was partly supported by the MICINN under the TEC2008-02113/TEC project and the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía, Spain) under the Excellence Projects P07-TIC-02566, P09-TIC-4530 and P11-TIC-7103.Résumé
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.