Open Access
MATEC Web Conf.
Volume 198, 2018
2018 Asia Conference on Mechanical Engineering and Aerospace Engineering (MEAE 2018)
Article Number 04010
Number of page(s) 7
Section Electronic Engineering and Mechatronics
Published online 12 September 2018
  1. O T. Moeslund, A. Hilton and V. Krüger, “A survey of advances in vision-based human motion capture and analysis,” Comput. Vis. Image Und., vol. 104, no. 2-3, pp. 90–126 (2006) [CrossRef] [Google Scholar]
  2. S. Won, F. Golnaraghi and W. Melek, “A Fastening Tool Tracking System Using an IMU and a Position Sensor With Kalman Filters and a Fuzzy Expert System,” IEEE Trans. Ind. Electron., vol. 56, no. 5, pp. 1782–1792 (2009) [CrossRef] [Google Scholar]
  3. D. Roetenberg, H. Luinge and P. Slycke, “Xsens MVN: full 6DOF human motion tracking using miniature inertial sensors,” Xsens Motion Technologies BV, Tech. Rep. (2009) [Google Scholar]
  4. S. Komada, Y. Hashimoto, N. Okuyama, T. Hisada and J. Hirai, “Development of a Biofeedback Therapeutic-Exercise-Supporting Manipulator,” IEEE Trans. Ind. Electron. vol. 56, no. 10, pp. 3914–3920 (2009) [CrossRef] [Google Scholar]
  5. R. Zhu and Z. Zhou, “A Real-Time Articulated Human Motion Tracking Using Tri-Axis Inertial/Magnetic Sensors Package,” IEEE Trans. Neur. Sys. Reh., vol. 12, no. 2, pp. 295–302 (2004) [CrossRef] [Google Scholar]
  6. Y. Nakamura, K. Yamane, Y. Fujita and I. Suzuki, "Somatosensory computation for man-machine interface from motion-capture data and musculoskeletal human model," IEEE Trans. Robot., vol. 21, no. 1, pp. 58–66 (2005) [CrossRef] [Google Scholar]
  7. A. Sabatini, “Estimating Three-Dimensional Orientation of Human Body Parts by Inertial/Magnetic Sensing,” Sensors, vol. 11, no. 12, pp. 1489–1525 (2011) [CrossRef] [Google Scholar]
  8. J. K. Lee and E. Park, “A Fast Quaternion-Based Orientation Optimizer via Virtual Rotation for Human Motion Tracking,” IEEE Trans. Biomed. Eng., vol. 56, no. 5, pp. 1574–1582 (2009) [CrossRef] [Google Scholar]
  9. A. Kim and M. Golnaraghi, “A quaternion-based orientation estimation algorithm using an inertial measurement unit,” in PLANS., pp. 268–272 (2004) [Google Scholar]
  10. SP. Tseng, WL. Li, CY. Sheng, JW. Hsu and CS. Chen. “Motion and attitude estimation using inertial measurements with complementary filter,” in ASCC., Kaohsiung, Taiwan, pp. 863–868 (2011) [Google Scholar]
  11. AM. Sabatini, “Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing,” IEEE Trans. Biomed. Eng., vol. 53, no. 7, pp. 1346–1356 (2006) [CrossRef] [Google Scholar]
  12. X. Yun and ER. Bachmann, “Design, implementation, and experimental results of a quaternion-based Kalman filter for human body motion tracking,” IEEE Trans. Robot., vol. 22, no. 6, pp. 1216–1227 (2006) [CrossRef] [Google Scholar]
  13. H. Harms, O. Amft, R. Winkler, J. Schumm, M. Kusserow and G. Tröster, “Ethos: Miniature orientation sensor for wearable human motion analysis.” Sensors, pp. 1037–1042 (2010) [Google Scholar]
  14. C. Brigante, N. Abbate, A. Basile, A. Faulisi and S. Sessa, “Towards Miniaturization of a MEMS-Based Wearable Motion Capture System,” IEEE Trans. Ind. Electron., vol. 58, no. 8, pp. 3234–3241 (2011) [CrossRef] [Google Scholar]
  15. N. Abbate, A. Basile, C. Brigante and A. Faulisi, “Development of a MEMS based wearable motion capture system,” in HSI, Catania, pp. 255–259 (2009) [Google Scholar]
  16. C. Cifuentes, A. Braidot, L. Rodríguez, M. Frisoli, A. Santiago and A. Frizera, “Development of a wearable ZigBee sensor system for upper limb rehabilitation robotics,” in BioRob, Rome, pp. 1989–1994 (2012) [Google Scholar]
  17. P. Kinney, “Zigbee technology: Wireless control that simply works,” Communications design conference. vol. 2, pp. 1–7 (2003) [Google Scholar]
  18. J. Lee, Y. Su and C. Shen, “A Comparative Study of Wireless Protocols: Bluetooth, UWB, ZigBee, and Wi-Fi,” in IECON, pp. 46–51 (2007) [Google Scholar]
  19. J. Suykens and J. Vandewalle, "Least squares support vector machine classifiers," Neural Processing Letters, vol. 9, no. 3, pp. 293–300 (1999) [CrossRef] [Google Scholar]
  20. VN. Vapnik, and V. Vlamimir, Statistical learning theory, New York: Wiley, pp 123–129.0 (1998) [Google Scholar]

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