Design of Tracking Controllers for Medical Equipment Holders Using AHRS and MEMS Sensors
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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:59806", author = "Seung You Na and Joo Hyun Jung and Jin Young Kim and Mohammad AhangarKiasari", title = "Design of Tracking Controllers for Medical Equipment Holders Using AHRS and MEMS Sensors", 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.", volume = "6", number = "12", pages = "1697-5", }