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Identification of capacitive MEMS accelerometer structure parameters for human body dynamics measurements
Vincas Benevicius1, Vytautas Ostasevicius, Rimvydas Gaidys
1Institute for Hi-Tech Development, Faculty of Mechanical Engineering and Mechatronics, Kaunas University of Technology, Kaunas LT-51369, Lithuania. vincas.benevicius@gmail.com
Sensors (Basel, Switzerland)
|August 27, 2013
Summary
This study identifies an optimal Micro-Electro-Mechanical Systems (MEMS) accelerometer structure for measuring human body dynamics. The research focused on a 3D capacitive design, validated through simulation and experimental comparison for accurate motion tracking.
Area of Science:
- Mechanical Engineering
- Biomedical Engineering
- Sensor Technology
Background:
- Micro-Electro-Mechanical Systems (MEMS) accelerometers offer advantages like small size, low weight, and low power consumption.
- These sensors have broad commercial applications, driving research into specialized designs.
- Accurate measurement of human body dynamics is crucial for various applications, including biomechanics and healthcare.
Purpose of the Study:
- To identify and optimize a MEMS accelerometer structure specifically for human body dynamics measurements.
- To ensure the selected structure provides sensitive and equal measurement capabilities across all three axes (3D).
Main Methods:
- Photogrammetry was employed to determine maximum human body part accelerations and signal bandwidth.
- A 3D capacitive accelerometer configuration was chosen as the primary structure.
- Hill climbing optimization was used to refine structural parameters, followed by simulations of proof-mass displacement.
- The final model was developed in Comsol Multiphysics, including eigenfrequency analysis and response to base excitation.
- Model outputs were experimentally validated against vibration stand data.
Main Results:
- An optimized 3D capacitive MEMS accelerometer structure was identified.
- Simulations confirmed proof-mass displacements within defined acceleration constraints.
- Eigenfrequency analysis and response simulations provided insights into the model's dynamic behavior.
- Experimental validation demonstrated good agreement between model predictions and real-world data across various excitation frequencies.
Conclusions:
- The developed 3D capacitive MEMS accelerometer structure is suitable for human body dynamics measurements.
- The optimization and validation process ensures the sensor's reliability and accuracy for biomechanical applications.
- This research contributes to the advancement of wearable sensor technology for health and performance monitoring.
