An online censoring (OC) based weighted-frequency Fourier linear combiner (OC-WFLC) adaptive filtering structure is proposed to reduce data processing costs in the estimation of pathological hand tremor (PHT) measurements. The proposed OC-WFLC is combined with the Fourier linear combiner (FLC) to effectively separate the PHT and voluntary movement from the hand tremor signal. The OC-WFLC is shown to adaptively extract the most informative frequency information, that is readily employed within the FLC to adaptively decompose the measurement signal into its PHT and voluntary movement components. The utilization of the OC strategy in the proposed framework is shown to significantly reduce data processing costs without adverse effects on the performance. Simulation results on real-world PHT data demonstrate the ability of the proposed OC-WFLC to yield a dramatic reduction of the processing time, a prerequisite for real-time rehabilitative, wearable, and assistive technology designed for PHT patients.