Estimation of pathological tremor by using adaptive shifting BMFLC base d on RLS algorithm

Pathological tremor is an involuntary, rhythmic oscillatory movement and impacts individual living activities. Tremor amplitude and frequency as significant features are important for tremor suppression by biomechanical loading. In this context, an adaptive shifting bandlimited multiple Fourier linear combiner (ASBMFLC) based on recursive least square (RLS) is proposed to estimate the modulated signals with shifting frequency band and zero-phase lag. This method includes digital filter, modified Weighted-Frequency Fourier Linear Combiner (WFLC), modulation of frequency band and Bandlimited Multiple Fourier Linear Combiner (BMFLC). In WFLC, RLS algorithm instead of least mean square (LMS) is employed to decrease the transit period and accelerate the estimation of dominant frequency. Based on the simulation signals, WFLC, BMFLC and ASBMFLC with RLS algorithm are evaluated, respectively. The results demonstrate that the proposed algorithm can adapt to unknown dominant frequency without prior information. Using the proposed algorithm, the voluntary motion/drift is also successfully separated from the tremor portion.