Abstract
In the capture of biomechanical signals, the application of Kalman filters allows a correction ofthe error caused by disturbances or noise in the system.This article presents a comparison of the performance of an Unscented Kalman Filter and an Extended Kalman Filter with the objective of identifying which of the two has a better performance for use in the area of the analysis of human movement.The results of the analysis of the measurement of flexion and extension of the arm, taken with inertial and magnetic sensors, show a Root Mean-Square Error (RMSE)of 2.43º in the Unscented Filter versus a 3.88º in the Extended one. The analysis was done with angular velocities between 1 and 15 rad/s, ideal for biomechanicalapplications.
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References
Šprdlík O (2012) Detection and Estimation of Human Movement Using Inertial Sensors: Applications in Neurology. Czech Technical University in Prague, Prague
Julier S, UhlmannJ(1997) New Extension of the Kalman Filter to Nonlinear Systems, SPIE Proc. vol. 6, Sig. Process., Sens. Fusion &Target Recognit. VI, Orlando, USA, 1997
Khoder W, Jida B(2014) A Quaternion Scaled Unscented Kalman Estimator for Inertial Navigation States Determination Using INS/GPS/Magnetometer Fusion,J. Sens. Technol. vol. 4, Tripoli, Lebanon, 2014, pp 101-117
Roetenberg D, et al. (2005) Compensation of Magnetic Disturbances Improves Inertial and Magnetic Sensing of Human Body Segment Orientation. IEEE Trans Neural SystRehabilEng3:395-405
Laviola J(2015) A Comparison of Unscented and Extended Kalman Filtering for Estimating Quaternion Motion, Am. Control Conf. Proc. vol. 3, Adv. Sci. Comput. & Visualization, Brown Univ. Technol. Center, Providence, USA,2003, pp 2435-2440
D’alfonso L, et al. (2015) Mobile robot localization via EKF and UKF: A comparison based on real data, Rob. Auton. Syst. vol. 74, Universitàdella Calabria, Rende, Italy, 2015,pp 122-127
Toloei A, Niazi S(2015) Estimation of LOS Rates for Target Tracking Problems using EKF and UKF Algorithms- a Comparative Study, Int. J. Eng. Trans. B. vol. 28, Department of Aerospace, ShahidBeheshtiUniversity, Tehran, Iran,2015, pp 172-178
Giannitrapani A,et al. (2011) Comparison of EKF and UKF for Spacecraft Localization via Angle Measurements, IEEE Trans. Aerosp. Electron. Syst. vol. 47, Universita di Siena, Siena, Italy, 2011,pp 75-84
Allota B, et al. (2015) A comparison between EKF-based and UKF-based navigation algorithms for AUVs localization, OCEANS-Genova, ISME - Interuniversity Center of Integrated Systems for the Marine Env, Florence, Italy, 2015
Callejas-CuervoM, Alvarez J.C, Alvarez D (2016) Capture and analysis of biomechanical signals with inertial and magnetic sensors as support in physical rehabilitation processes, Proc. IEEE EMBS 13th Annu. Int. Body Sensor Networks Conf., San Francisco, USA, 2016, pp 119–123
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Callejas Cuervo, M., Vélez Guerrero, M.A., Alarcón-Aldana, A.C. (2017). Nonlinear estimators of human movement in biomechanical signals: Comparison between Extended Kalman Filter and Unscented Kalman Filter. In: Torres, I., Bustamante, J., Sierra, D. (eds) VII Latin American Congress on Biomedical Engineering CLAIB 2016, Bucaramanga, Santander, Colombia, October 26th -28th, 2016. IFMBE Proceedings, vol 60. Springer, Singapore. https://doi.org/10.1007/978-981-10-4086-3_130
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DOI: https://doi.org/10.1007/978-981-10-4086-3_130
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