Literature DB >> 21461779

Position error reduction in a mechanical tracking linkage for arthroscopic hip surgery.

Emily Geist1, Kenji Shimada.   

Abstract

PURPOSE: Position tracking is an important aspect of many computer-aided surgical techniques. Given the obstacles of current optical, electromagnetic, and mechanical systems for medical applications, this work investigates error reduction in a new mechanical tracking system developed for arthroscopic hip surgery. This new tracking linkage addresses the current contradictory requirements of a thin, small linkage for ease of surgical use and a large, bulky linkage for increased accuracy by using (1) kinematic redundancy and (2) data averaging and curve fitting.
METHOD: To reduce the position error in the proposed mechanical tracking linkage, four numerical techniques were applied to data from the linkage. Two averaging techniques and two curve fitting techniques were investigated. After implementing each numerical technique, error testing was performed to quantify improvement in performance.
RESULTS: While the simple average and moving average techniques lowered the error by over 30%, these two methods were undesirable for the overall system performance. The lowest error was measured by the linear curve prediction method. This technique measured 0.552 mm of error, roughly half of the error measured by the control case. The quadratic prediction method reduced the error by 35% and had the lowest standard deviation in the measurements.
CONCLUSION: The linear prediction technique was able to significantly lower the error measured by a kinematically redundant mechanical tracking linkage. While further testing is still necessary, this data suggests that a thin, small mechanical tracking linkage could achieve a high level of accuracy to be an appropriate choice for a surgical tracking application.

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Mesh:

Year:  2011        PMID: 21461779     DOI: 10.1007/s11548-011-0555-7

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  6 in total

1.  A virtual-reality training system for knee arthroscopic surgery.

Authors:  Pheng-Ann Heng; Chun-Yiu Cheng; Tien-Tsin Wong; Yangsheng Xu; Yim-Pan Chui; Kai-Ming Chan; Shiu-Kit Tso
Journal:  IEEE Trans Inf Technol Biomed       Date:  2004-06

2.  Robotic hip arthroscopy in human anatomy.

Authors:  Jens Kather; Monika E Hagen; Philippe Morel; Jean Fasel; Sheraz Markar; Michael Schueler
Journal:  Int J Med Robot       Date:  2010-09       Impact factor: 2.547

3.  Robotic vascular surgery, 150 cases.

Authors:  P Stádler; L Dvoracek; P Vitasek; P Matous
Journal:  Int J Med Robot       Date:  2010-12       Impact factor: 2.547

4.  Computer-aided navigation for arthroscopic hip surgery using encoder linkages for position tracking.

Authors:  Emily Monahan; Kenji Shimada
Journal:  Int J Med Robot       Date:  2006-09       Impact factor: 2.547

5.  A robot-guided minimally invasive approach for cochlear implant surgery: preliminary results of a temporal bone study.

Authors:  Omid Majdani; Thomas S Rau; Stephan Baron; Hubertus Eilers; Claas Baier; Bodo Heimann; Tobias Ortmaier; Sönke Bartling; Thomas Lenarz; Martin Leinung
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-06-13       Impact factor: 2.924

6.  Calibration of tracking systems in a surgical environment.

Authors:  W Birkfellner; F Watzinger; F Wanschitz; R Ewers; H Bergmann
Journal:  IEEE Trans Med Imaging       Date:  1998-10       Impact factor: 10.048

  6 in total
  1 in total

1.  Augmented reality-based navigation system for wrist arthroscopy: feasibility.

Authors:  Ahmed Zemirline; Vincent Agnus; Luc Soler; Christophe L Mathoulin; Miryam Obdeijn; Philippe A Liverneaux
Journal:  J Wrist Surg       Date:  2013-11
  1 in total

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