Premium
A zero phase adaptive fuzzy Kalman filter for physiological tremor suppression in robotically assisted minimally invasive surgery
Author(s) -
Sang Hongqiang,
Yang Chenghao,
Liu Fen,
Yun Jintian,
Jin Guoguang,
Chen Fa
Publication year - 2016
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1741
Subject(s) - kalman filter , computer science , signal (programming language) , control theory (sociology) , compensation (psychology) , vibration , filter (signal processing) , adaptive filter , artificial intelligence , acoustics , physics , computer vision , algorithm , psychology , control (management) , psychoanalysis , programming language
Background Hand physiological tremor of surgeons can cause vibration at the surgical instrument tip, which may make it difficult for the surgeon to perform fine manipulations of tissue, needles, and sutures. Methods A zero phase adaptive fuzzy Kalman filter (ZPAFKF) is proposed to suppress hand tremor and vibration of a robotic surgical system. The involuntary motion can be reduced by adding a compensating signal that has the same magnitude and frequency but opposite phase with the tremor signal. Results Simulations and experiments using different filters were performed. Results show that the proposed filter can avoid the loss of useful motion information and time delay, and better suppress minor and varying tremor. Conclusions The ZPAFKF can provide less error, preferred accuracy, better tremor estimation, and more desirable compensation performance, to suppress hand tremor and decrease vibration at the surgical instrument tip. Copyright © 2016 John Wiley & Sons, Ltd.