Design of Tracking Controllers for Medical Equipment Holders Using AHRS and MEMS Sensors

Authors: Seung You Na, Joo Hyun Jung, Jin Young Kim, Mohammad AhangarKiasari

Abstract:

There are various kinds of medical equipment which requires relatively accurate positional adjustments for successful treatment. However, patients tend to move without notice during a certain span of operations. Therefore, it is common practice that accompanying operators adjust the focus of the equipment. In this paper, tracking controllers for medical equipment are suggested to replace the operators. The tracking controllers use AHRS sensor information to recognize the movements of patients. Sensor fusion is applied to reducing the error magnitudes through linear Kalman filters. The image processing of optical markers is included to adjust the accumulation errors of gyroscope sensor data especially for yaw angles. The tracking controller reduces the positional errors between the current focus of a device and the target position on the body of a patient. Since the sensing frequencies of AHRS sensors are very high compared to the physical movements, the control performance is satisfactory. The typical applications are, for example, ESWT or rTMS, which have the error ranges of a few centimeters.

Keywords: AHRS, Sensor fusion, Tracking control, Position and posture.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075840

References:

[1] Sonardyne web site, Radian AHRS unit, http://www.sonardyne.com /Products/Inertial/8041.html.
[2] P. Mahacek, T. Berk, A. Cassanova, C. Kitts, W. Kirkwood, and G. Wheat, "Development and Initial Testing of a SWATH Vessel for Shallow-water Bathymetry," Proceedings of IEEE/MTS Oceans Conference, 2008.
[3] D. W. Kang, J. S. Choi, and G. R. Tack, "A study on real-time sports activity classification & monitoring using a tri-axial accelerometer," J. of Korean Society of Sports Biomechanics, vol. 18, no. 2, 2008, pp. 59-64.
[4] V. C. Carlijn, B. Karel, T. M. Koekkoek, M. Verduin, R. Kodde, and J. D. Janssen, "A Triaxial Accelerometer and Portable Data Processing Unit for the Assessment of Daily Physical Activity," IEEE Trans. Biomed. Eng., vol. 44, 1997, pp. 136-147.
[5] G. T. Kang, K. T. Park, G. R. Kim, B. C. Choi, and D. K. Jung, "Real time gait analysis using acceleration signal," J. of the Korean Sensors Society, vol. 18, no. 6, Nov. 2009, pp. 449-454.
[6] D. M. Karantonis, M. R. Narayanan, M. M. Mathie, N. H. Lovell, and B. G. Celler, "Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring," IEEE Trans. Biomed., vol. 10, no. 1, 2006, pp. 156-165.
[7] D. U. Jeong, and W. Y. Chung, "Posture and activity monitoring using 3-axis accelerometer," J. of the Korean Sensors Society, vol. 16, no. 6, Nov. 2007, pp. 467-474.
[8] M. J. Mathie, A. C. F. Coster, B. G. Celler, and N. H. Lovell, "Classification of basic daily movements using a triaxial accelerometer," Med. Biol. Eng. Computation. vol. 42, 2004, pp. 679-687.
[9] A. K. Bourk, and J.V. O'Brien, "Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm," Gait & Posture, vol. 26, 2007, pp. 194-199.
[10] S. Sessa, M. Zecca, Z. Lin, T. Sasaki, K. Itoh, and A. Takanishi, "Waseda Bioinstrumentation System #3 as a tool for objective rehabilitation measurement and assessment," Proceedings IEEE 11th International Conference on Rehabilitation Robotics, Japan, 2009, pp. 115-120.
[11] N. L. Dudek, O. D. Khan, E. D. Lemarire, and M. B. Marks, "Ambulation monitoring of transtibial amputation subjects with patient activity monitor versus pedometer," JRRD. vol. 45, no. 4, 2008, pp. 577-586.
[12] E. L. Melanson, J. R. Knoll, M. L. Bell, W. T. Donahoo, J. O. Hill, and L. J. Nysse, "Commercially available pedometers: considerations for accurate step counting," Prevntive Medicine, vol. 39, 2004, pp. 361-368.
[13] S. P. Kim, Understanding of Kalman filters with MATLAB, Ajin Press, Korea, pp. 129-158.