Near Infrared Spectroscopy (NIRS) is an optical method used for monitoring local tissue oxygenation and hemodynamics. This method is becoming increasingly popular in clinical and research applications. One important shortcoming of NIRS is an extreme sensitivity to motion artifacts. In this paper, we propose a new algorithm for removing movement artifacts from NIRS signals. We applied wavelet transform and then used the signal representation in the wavelet domain to isolate the artifacts and remove them using statistical testing. We tested this method on both simulated and experimental NIRS data acquired in a leg fracture operation and compared the results with those of median filtering, FIR filtering and wavelet SURE threshold estimation methods. The results show that the method significantly reduces the artifacts without distorting the signal in artifact free regions and outperforms other artifact removal methods.
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