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Multistep prediction of physiological tremor for surgical robotics applications

  • Kyungpook National University
  • Nanyang Technological University

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

Abstract

Accurate canceling of physiological tremor is extremely important in robotics-assisted surgical instruments/procedures. The performance of robotics-based hand-held surgical devices degrades in real time due to the presence of phase delay in sensors (hardware) and filtering (software) processes. Effective tremor compensation requires zero-phase lag in filtering process so that the filtered tremor signal can be used to regenerate an opposing motion in real time. Delay as small as 20 ms degrades the performance of human-machine interference. To overcome this phase delay, we employ multistep prediction in this paper. Combined with the existing tremor estimation methods, the procedure improves the overall accuracy by 60% for tremor estimation compared to single-step prediction methods in the presence of phase delay. Experimental results with developed methods for 1-DOF tremor estimation highlight the improvement.

Original languageEnglish
Article number6530703
Pages (from-to)3074-3082
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Volume60
Issue number11
DOIs
StatePublished - 2013

Keywords

  • Autoregressive (AR)
  • band limited multiple linear Fourier combiner (BMFLC)
  • inertial sensors
  • Kalman filter
  • multistep prediction
  • physiological motion
  • tremor

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