ADAPTIVE EPSILON-TUBE FILTER FOR BLUNT NOISE REMOVAL

摘要

Techniques for motion artifact (MA) reduction in impedance plethysmography (IP) and other physiological signals are provided. The techniques limit the amplitude of MA filtered signals by imposing an “ε-tube.” The techniques may include the introduction of a regularization term to ensure that the pattern of a filtered signal is similar to the pattern of the primary component of the original, unfiltered signal by maximizing the regularity of the filtered signal. The techniques may be integrated into a portable monitoring device, such as an armband, to remove MA from various diagnostic signals and to extract primary signal components for producing enhanced device performance.

主权项

1. A computer-implemented method of adaptively filtering a signal, comprising:
sampling, by one or more processors, a signal over a plurality of successive sliding time windows, the signal including a primary signal component having an amplitude that varies over time but is substantially constant within each of the plurality of successive sliding time windows; receiving, by one or more processors, a plurality of movement signals over a first sliding time window from among the plurality of successive sliding time windows, the plurality of movement signals being indicative of a blunt noise component that may be included in the signal within the first sliding time window; calculating, by one or more processors, a prototype signal that models dominant frequency components of the signal from a second sliding time window that chronologically precedes the first sliding time window; calculating, by one or more processors, a set of filter coefficients utilizing the plurality of movement signals within the first sliding time window such that an objective function is minimized and a constraint is satisfied; and filtering, by one or more processors, the signal within the first sliding time window in accordance with the set of filter coefficients to retain the primary signal component while removing the blunt noise, wherein the constraint is satisfied when the filtered signal amplitude within the first sliding time window is limited between a threshold value based upon the primary signal component amplitude within the second sliding time window, and wherein the objective function is minimized when the error between frequency components of the filtered signal within the first sliding time window and the frequency components of the prototype signal are minimized.