Adaptive human-machine interface for persons with tremor

Abstract
A new adaptive filter has been developed to model pathological tremor during human-machine interaction. Operating online, the system suppresses tremor to improve precision in human-machine control. Offline, the system processes recorded data to quantify tremor for clinical use. The filter estimates tremor frequency as well as amplitude, adapting the reference input frequency to follow frequency modulation of tremor. The algorithm is computationally inexpensive and simple to implement in many human-machine interface applications. Experimental results are presented.

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