Adaptive canceling of physiological tremor for improved precision in microsurgery

Area of Science:

• Biomedical Engineering
• Robotics
• Control Systems

Background:

• Physiological hand tremor is a significant challenge in microsurgery, limiting precision and increasing risks.
• Existing methods for tremor reduction are often insufficient for real-time compensation during delicate procedures.

Purpose of the Study:

• To develop and validate a novel adaptive algorithm for tremor estimation.
• To introduce a new technique for active, real-time cancellation of physiological hand tremor in microsurgery.

Main Methods:

• Utilized the weighted-frequency Fourier linear combiner (WFLC) to model tremor as a modulating sinusoid, tracking its frequency, amplitude, and phase.
• Employed piezoelectric actuators to move the surgical instrument tip in opposition to tremor motion, effectively canceling it.
• Demonstrated the technique in a one-dimensional cantilever apparatus simulating surgical instrument dynamics, using prerecorded hand motion data.

Main Results:

• The WFLC tremor compensation reduced root-mean-square (rms) tip motion in the 6-16 Hz tremor band by 67%.
• Reduced the rms error relative to voluntary motion estimates by 30%.
• The system showed effectiveness in a benchtop simulation of microsurgical conditions.

Conclusions:

• The presented adaptive algorithm and active cancellation technique offer a promising solution for mitigating physiological hand tremor in microsurgery.
• The technology is suitable for implementation in hand-held microsurgical instruments, potentially enhancing surgical outcomes.
• This approach represents a significant advancement in improving the stability and precision of microsurgical interventions.