The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Prediction of bodily motion due to respiration was investigated preparatory to implementation of active compensation for respiration in a robot-assisted system for percutaneous kidney surgery. Data for preliminary testing were recorded from the chest wall of a subject using an optical displacement sensor. The weighted-frequency Fourier linear combiner algorithm, an adaptive modeling algorithm, was used to model and predict respiratory movement. Preliminary results are presented, in which the algorithm is shown to track a 0.86 mm rms respiration signal with 0.11 mm rms error. The general robotic system and compensation scheme are also described.

Keywords

compensation, adaptive filtering, robot, surgery

Notes

Sponsor: National Science Foundation

Grant ID: EEC-9731748

Associated Center(s) / Consortia: Medical Robotics Technology Center

Associated Lab(s) / Group(s): Surgical Mechatronics Laboratory

Text Reference

Cameron Riviere, A. Thakral, I. I. Iordachita, G. Mitroi, and D. Stoianovici, "Predicting respiratory motion for active canceling during percutaneous needle insertion," Proc. 23rd Annual Intl. Conf. IEEE Engineering in Medicine and Biology Society, October, 2001, pp. 3477-3480.

BibTeX Reference

@inproceedings{Riviere_2001_4093,
   author = "Cameron Riviere and A. Thakral and I. I. Iordachita and G. Mitroi and D. Stoianovici",
   title = "Predicting respiratory motion for active canceling during percutaneous needle insertion",
   booktitle = "Proc. 23rd Annual Intl. Conf. IEEE Engineering in Medicine and Biology Society",
   pages = "3477-3480",
   month = "October",
   year = "2001",
}

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