The Module for Prescribing Motion Scenarios in Hardware-Software Tools for Inertial Sensors Assessment

Computer Science & Engineering

Authors

First and Last Name Academic degree E-mail Affiliation
Yurii Stets No yuriy.y.stets [at] protonmail.com Lviv Polytechnic National University
Lviv, Ukraine
Tetyana Marusenkova Ph.D. tetyana.marus [at] gmail.com Lviv Polytechnic National University
Lviv, Ukraine

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 01.07.2019 - 22:29
Abstract

The work presents an OpenGL-based software module for prescribing motions scenarios. It is developed as a part of a hardware-software tool that helps the developer conclude whether a set of inertial sensors with specific technical characteristics is applicable for a defined application or not.

References

1.     Buke, A., Gaoli, F., Yongcai, W., Lei, S., & Zhiqi, Y. (2015). Healthcare algorithms by wearable inertial sensors: a survey. China Communications, 12(4), 1-12. doi: 10.1109/cc.2015.7114054.

2.     Nemec, D., Janota, A., Hrubos, M., & Simak, V. (2016). Intelligent Real-Time MEMS Sensor Fusion and Calibration. IEEE Sensors Journal, 16(19), 7150-7160. doi: 10.1109/jsen.2016.2597292.

3.     Lima, P. (2007). A Bayesian Approach to Sensor Fusion in Autonomous Sensor and Robot Networks. IEEE Instrumentation & Measurement Magazine, 10(3), 22-27. doi: 10.1109/mim.2007.4284253.

4.     Madgwick, S., Harrison, A.  &Vaidyanathan, R. (2011). Estimation of IMU and MARG orientation using a gradient descent algorithm. 2011 IEEE International Conference on Rehabilitation Robotics. DOI: 10.1109/ICORR.2011.5975346.

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Comments

Secretary CSE
researcher, secretary

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Thu, 10/17/2019 - 13:24