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Sensors 2013, 13(9), 11184-11195; doi:10.3390/s130911184

Identification of Capacitive MEMS Accelerometer Structure Parameters for Human Body Dynamics Measurements

*  and
Institute for Hi-Tech Development, Faculty of Mechanical Engineering and Mechatronics, Kaunas University of Technology, Studentu 65-209, Kaunas LT-51369, Lithuania
* Author to whom correspondence should be addressed.
Received: 19 July 2013 / Revised: 12 August 2013 / Accepted: 16 August 2013 / Published: 22 August 2013
(This article belongs to the Special Issue Modeling, Testing and Reliability Issues in MEMS Engineering 2013)
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Due to their small size, low weight, low cost and low energy consumption, MEMS accelerometers have achieved great commercial success in recent decades. The aim of this research work is to identify a MEMS accelerometer structure for human body dynamics measurements. Photogrammetry was used in order to measure possible maximum accelerations of human body parts and the bandwidth of the digital acceleration signal. As the primary structure the capacitive accelerometer configuration is chosen in such a way that sensing part measures on all three axes as it is 3D accelerometer and sensitivity on each axis is equal. Hill climbing optimization was used to find the structure parameters. Proof-mass displacements were simulated for all the acceleration range that was given by the optimization problem constraints. The final model was constructed in Comsol Multiphysics. Eigenfrequencies were calculated and model’s response was found, when vibration stand displacement data was fed into the model as the base excitation law. Model output comparison with experimental data was conducted for all excitation frequencies used during the experiments.
Keywords: capacitive; accelerometer; MEMS; optimization; proof-mass; L-shaped beam capacitive; accelerometer; MEMS; optimization; proof-mass; L-shaped beam
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Benevicius, V.; Ostasevicius, V.; Gaidys, R. Identification of Capacitive MEMS Accelerometer Structure Parameters for Human Body Dynamics Measurements. Sensors 2013, 13, 11184-11195.

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