Artefact cancellation in motor-sensory evoked potentials: two approaches using adaptive filtration and exponential approximation.

Adaptive filtering for artefact cancellation in motor-sensory evoked potentials using signals obtained by subtraction methods (double-stimulus, off-nerve and subthreshold) is proposed. This is advantageous as inherent non-linear distortions can be overcome in an easier way by adaptive filtering. Efficiency is assessed with reference signals synthesised by varying the shape and reducing the amplitude of a 'pure' evoked potential in the range from 10% to 50%. The experiments show virtually identical shapes of the 'pure' and the filtered signal. The time shift between them is insignificant if a causal filter and small number of Widrow coefficients, e.g. N = 8, are used. Further, two-exponential artefact approximation is applied with subsequent direct subtraction from the contaminated signal by a specially designed PC-controlled system for data acquisition and processing. For a fast procedure convergence, one-parametric optimisation of the time-constant tau is used, starting with tau = 0.5 ms. The results obtained with artefact-corrupted evoked potentials from several subjects prove the efficiency of the approach. It has the substantial advantage of avoiding the need for reference signals. Both methods have advantages compared with other known software techniques.