Journal of Integrative Natural Science (통합자연과학논문집)

The Basic Science Institute Chosun University (조선대학교 기초과학연구원)
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Analysis of IMU Sensor Sensitivity According to Frequency Variation

주파수 변화에 따른 IMU 센서 민감도 분석

  • Bugeon Lee (Department of Statistics, Daegu University) ;
  • Seongbok Hong (Winitech) ;
  • Doohyun Baek (Winitech) ;
  • Junghyun Lim (Winitech) ;
  • Sanghoo Yoon (Department of Statistics, Chonnam National University)
  • 이부건 (대구대학교 통계학과) ;
  • 홍성복 (위니텍) ;
  • 백두현 (위니텍) ;
  • 임정현 (위니텍) ;
  • 윤상후 (전남대학교 통계학과)
  • Received : 2024.08.18
  • Accepted : 2024.09.05
  • Published : 2024.09.30
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Abstract

Advancements in sensor technology, particularly Inertial Measurement Units (IMU), are crucial in modern pose estimation. IMUs typically consist of accelerometers and gyroscopes (6-axis), with some models including magnetometers (9-axis). This study investigates the impact of sensor frequency on pose estimation accuracy using data from a 256Hz IMU sensor. The data sets analyzed include "spiralStairs," "stairsAndCorridor," and "straightLine," with frequencies varied to 128Hz, 64Hz, and 32Hz, and conditions categorized as stationary or dynamic. The results indicate that sensitivity remains high at lower frequencies under stationary conditions but declines in dynamic conditions. Performance comparison, based on Root Mean Square Error (RMSE) values, showed that lower frequencies lead to increased RMSE, thus diminishing model accuracy. Additionally, the Extended Kalman Filter (EKF) was tested as an alternative to Madgwick's algorithm but faced challenges due to insufficient sensor noise data.

Keywords

Acknowledgement

이 논문은 2022년 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(NRF-2022M3E9A1096505).

References

  1. Kang, J. G., "A Study on the Design and Implementation of a Position Tracking System using Acceleration-Gyro Sensor Fusion.", Journal of The Korea Society of Computer and Information, Vol. 28, pp. 49-54, 2023.
  2. Lee, J., Park, K. E., and Kim, Y., "A study on indoor positioning based on pedestrian dead reckoning using inertial measurement unit. Journal of the Society of Disaster Information", Vol. 17, pp. 521- 534, 2021.
  3. Kim, H., and Jang, B., "Indoor positioning technique using the landmark based on relative AP signal strengths", Journal of The Korea Society of Computer and Information, Vol. 25, pp. 63-69, 2020.
  4. KIM, Dong-Eon, MAI, Ngoc-Dau and HAN, Dong Seog., "On-Device Deep Learning-based Multiple Behavior Detection using IMU Motion Sensors.", In:2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, pp. 194-197, 2023.
  5. Roh, J. H., and Kim, J. H., "Fall detection based on acceleration sensor attached to wrist using feature data in frequency space", Smart Media Journal, Vol. 10, pp. 31-38, 2021.
  6. Madgwick, Sebastian OH, Andrew JL Harrison, and Ravi Vaidyanathan., "Estimation of IMU and MARG orientation using a gradient descent algorithm.", 2011 IEEE international conference on rehabilitation robotics. Ieee, pp. 1-7, 2011.
  7. S. Reddy, M. Mun, J. Burke, D. Estrin, andM. Hansen., "Using Mobile Phones to DetermineTransportation Modes,", ACM Transactions on Sensor Networks, Vol. 6, 2010.
  8. Yang, Hye Kyung, and H. S. Yong., "Real-time physical activity recognition using tri-axis accelerometer of smart phone.", Journal of Korea Multimedia Society, Vol. 17, pp. 506-513, 2014.
  9. Quintero, David, et al., "Real-time continuous gait phase and speed estimation from a single sensor.", 2017 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2017.
  10. Haukkanen, Pentti, et al., "The arithmetic Jacobian matrix and determinant.", Journal of Integer Sequences, Vol. 20, 2017.
  11. WELCH, Greg, et al., "An introduction to the Kalman filter", 1995.
  12. Madgwick, Sebastian., "An efficient orientation filter for inertial and inertial/magnetic sensor arrays.", Report x-io and University of Bristol (UK), Vol. 25, pp. 113-118, 2010.
  13. Kok, Manon, Jeroen D. Hol, and Thomas B. Schon., "Using inertial sensors for position and orientation estimation.", arXiv preprint arXiv:1704.06053, 2017.
  14. H. Durrant-Whyte and T. Bailey., "Simultaneous localization and mapping: part I,", in IEEE Robotics & Automation Magazine, Vol. 13, pp. 99-110, 2006.
  15. Wandinger, Ulla., "Introduction to lidar.", Lidar: range-resolved optical remote sensing of the atmosphere. New York, NY: Springer New York, Vol. 102. pp. 1-18, 2005.