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Sensors 2018, 18(4), 1123; https://doi.org/10.3390/s18041123

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review

1
School of Innovation, Design and Engineering, Mälardalen University, 721 23 Västerås, Sweden
2
Motion Control i Västerås AB, 721 30 Västerås, Sweden
*
Author to whom correspondence should be addressed.
Received: 7 March 2018 / Revised: 2 April 2018 / Accepted: 4 April 2018 / Published: 6 April 2018
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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Abstract

Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented. View Full-Text
Keywords: drift; MEMS gyroscope; motion analysis; motion sensors; noise/error reduction; signal processing algorithms; systematic review drift; MEMS gyroscope; motion analysis; motion sensors; noise/error reduction; signal processing algorithms; systematic review
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Du, J.; Gerdtman, C.; Lindén, M. Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review. Sensors 2018, 18, 1123.

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