Mechanical Structural Design of a MEMS-Based Piezoresistive Accelerometer for Head Injuries Monitoring: A Computational Analysis by Increments of the Sensor Mass Moment of Inertia

Marco Messina, James Njuguna, Chrysovalantis Palas
2018 Sensors  
Section 6 of the "Repository policy for OpenAIR @ RGU" (available from http://www.rgu.ac.uk/staff-and-currentstudents/library/library-policies/repository-policies) provides guidance on the criteria under which RGU will consider withdrawing material from OpenAIR. If you believe that this item is subject to any of these criteria, or for any other reason should not be held on OpenAIR, then please contact openair-help@rgu.ac.uk with the details of the item and the nature of your complaint. GOLD
more » ... INA, M., NJUGUNA, J. and PALAS, C. Mechanical structural design of a MEMS-based piezoresistive accelerometer for head injuries monitoring: a computational analysis by increments of the sensor mass moment of inertia. 2018 MESSINA, M., NJUGUNA, J. and PALAS, C. 2018. Mechanical structural design of a MEMS-based piezoresistive accelerometer for head injuries monitoring: a computational analysis by increments of the sensor mass moment of inertia. Sensors [online], 18(1), article ID 289. Available from: https://doi.org/10.3390/s18010289 MESSINA, M., NJUGUNA, J. and PALAS, C. 2018. Mechanical structural design of a MEMS-based piezoresistive accelerometer for head injuries monitoring: a computational analysis by increments of the sensor mass moment of inertia. Sensors, 18(1), article ID 289. Held on OpenAIR [online]. Available from: https://openair.rgu.ac.uk PUBLISHED Abstract: This work focuses on the proof-mass mechanical structural design improvement of a tri-axial piezoresistive accelerometer specifically designed for head injuries monitoring where medium-G impacts are common; for example, in sports such as racing cars or American Football. The device requires the highest sensitivity achievable with a single proof-mass approach, and a very low error (<1%) as the accuracy for these types of applications is paramount. The optimization method differs from previous work as it is based on the progressive increment of the sensor proof-mass mass moment of inertia (MMI) in all three axes. Three different designs are presented in this study, where at each step of design evolution, the MMI of the sensor proof-mass gradually increases in all axes. The work numerically demonstrates that an increment of MMI determines an increment of device sensitivity with a simultaneous reduction of cross-axis sensitivity in the particular axis under study. This is due to the linkage between the external applied stress and the distribution of mass (of the proof-mass), and therefore of its mass moment of inertia. Progressively concentrating the mass on the axes where the piezoresistors are located (i.e., xand y-axis) by increasing the MMI in the xand y-axis, will undoubtedly increase the longitudinal stresses applied in that areas for a given external acceleration, therefore increasing the piezoresistors fractional resistance change and eventually positively affecting the sensor sensitivity. The final device shows a sensitivity increase of about 80% in the z-axis and a reduction of cross-axis sensitivity of 18% respect to state-of-art sensors available in the literature from a previous work of the authors. Sensor design, modelling, and optimization are presented, concluding the work with results, discussion, and conclusion.
doi:10.3390/s18010289 pmid:29351221 pmcid:PMC5795827 fatcat:r2ci3x2nubbxjlhunjv7af7om4