A zero phase adaptive fuzzy Kalman filter for physiological tremor suppression in robotically assisted minimally...

Area of Science:

• Robotics
• Surgical Technology
• Control Systems

Background:

• Surgeon hand tremor introduces vibrations at the surgical instrument tip.
• These vibrations impede precise manipulation of tissues, needles, and sutures during surgery.

Purpose of the Study:

• To propose a zero phase adaptive fuzzy Kalman filter (ZPAFKF) for suppressing hand tremor in robotic surgical systems.
• To reduce involuntary motion by introducing a compensating signal with opposite phase to the tremor.

Main Methods:

• Developed and implemented a zero phase adaptive fuzzy Kalman filter (ZPAFKF).
• Utilized simulations and experimental setups to evaluate filter performance against other methods.
• Compared tremor suppression capabilities, information loss, and time delay.

Main Results:

• The ZPAFKF effectively suppressed minor and varying tremors.
• The filter successfully avoided the loss of useful motion information.
• No significant time delay was introduced by the ZPAFKF.

Conclusions:

• The ZPAFKF demonstrated superior tremor estimation and compensation performance.
• The filter achieved reduced error and improved accuracy in robotic surgery simulations and experiments.
• The ZPAFKF is a valuable tool for suppressing hand tremor and decreasing surgical instrument tip vibration.