Estimation and filtering of physiological tremor for real-time compensation in surgical robotics applications

Physiological tremor is the main cause of imprecision in microsurgical procedures/robotics applications. Existing methods, such as weighted-frequency Fourier linear combiner (WFLC), rely on estimating the tremor under the assumption that it has a single dominant frequency. This paper focuses on developing a new algorithm for accurate tremor filtering in real time.

A study conducted on several novice subjects and microsurgeons showed the tremor to contain several dominant frequencies in a band, rather than a single dominant frequency. Based on the tremor characteristics, a new algorithm band-limited multiple Fourier linear combiner (BMFLC) has been developed to estimate a band of signals with multiple dominant frequencies. A separation procedure to separate the intended motion/drift from the tremor portion is also discussed.

A simulation study was first conducted to validate the theoretical development on recorded tremor data. The experimental set-up was designed to study the real-time performance of the proposed algorithm. Tremor sensing using accelerometers is also discussed, with the proposed algorithm. Our experiments showed that the developed BMFLC algorithm had an average tremor compensation of 64% compared to 43% for the WFLC algorithm in real-time for one degree of freedom (1-DOF) cancellation of tremor.

The BMFLC algorithm can be applied for the three axes separately and 3-DOF cancellation of tremor can be achieved. Further research is required to deal with complex gestures involved during microsurgery.