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Tremor Estimation and Removal in Robot‐Assisted Surgery Using Improved Enhanced Band‐Limited Multiple Fourier Linear Combiner

Wenjie Wang, Boqiang Jia, Jianwei Ma, Xiaohua Wang, Huajian Song

Year
2024
Citations
5

Abstract

BACKGROUND: During a robot-assisted minimally invasive surgery, hand tremors in a surgeon's manipulation of the master manipulator can cause vibrations of the slave surgical instruments. METHODS: This letter addresses this problem by proposing an improved Enhanced Band-Limited Multiple Linear Fourier Combiner (E-BMFLC) algorithm for filtering the physiological tremor signals of a surgeon's hand. The proposed method uses the amplitude of the input signal to adapt the learning rate and a dense division of the combiner bands for the higher amplitude bands of the tremor signals. RESULTS: By using the proposed improved E-BMFLC algorithm, the compensation accuracy can be improved by 4.5%-8.9%, as well as a spatial position error of less than 1 mm. CONCLUSION: The results show that among all filtering methods, the improved E-BMFLC filtering method has the highest number of successful experiments and the lowest experimental time.

Keywords

Computer scienceCompensation (psychology)SIGNAL (programming language)AmplitudeFourier transformPosition (finance)Artificial intelligenceComputer visionRobotAlgorithm

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