Predicting Respiratory Motion for Active Canceling During Percutaneous Needle Insertion

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.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA410283

Entities

People

  • A. Thakral
  • C. N. Riviere
  • D. Stoianovici
  • G. Mitroi
  • I. I. Iordachita

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Counter WMD

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Algorithms
  • Amplitude
  • Anesthesia
  • Cartesian Coordinates
  • Compensation
  • Displacement
  • Errors
  • Fourier Series
  • Frequency
  • Health Services
  • Medical Personnel
  • Physicians
  • Respiration
  • Three Dimensional
  • X Rays

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Robotics and Automation.
  • Trauma Surgery or Emergency Medicine.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Autonomy