Autoregressive model with Kalman filter for estimation of physiological tremor in surgical robotic applications
作者： K. C. Veluvolu , W. T. Ang , Sivanagaraja Tatinati
DOI:
关键词: Control theory 、 Autoregressive model 、 Adaptive filter 、 Kalman filter 、 Inertial measurement unit 、 Compensation (engineering) 、 Computational complexity theory 、 Filter design 、 Computer science 、 Process (computing)
摘要: In real-time implementation computational complexity plays vital role. This paper focuses on adaptive signal processing of physiological hand tremor for cancellation in robotic devices. The is modelled with AR(3) process that has less compared to other model based existing methods. this paper, filter coefficients are updated Kalman improve the performance. method AR-LMS and improved AR-Kalman implemented compensation. A comparative study conducted algorithms data from microsurgeons novice subjects. Experimental results shows proposed AR improves accuracy by at least 10% LMS.
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