Respiratory impedance measured by the forced oscillation technique (FOT) can be contaminated by artifacts such as coughing, vocalization, swallowing or leaks at the mouthpiece. We present a novel technique to detect these artifacts using multilevel discrete wavelet transforms. FOT was performed with artifacts introduced during separate 60 s recordings at known times in 10 healthy subjects. Brief glottal closures were generated phonetically and confirmed by nasopharyngoscopic imaging of the glottis. Artifacts were detected using Daubechies wavelets by applying a threshold to squared detail coefficients from the wavelet transforms of both pressure and flow signals. Sensitivity and specificity were compared over a range of thresholds for different level squared detail coefficients. Coughs could be identified using 1st level detail (cd1) coefficients of pressure achieving 96% sensitivity and 100% specificity while swallowing could be identified using cd2 thresholds of pressure with 95% sensitivity and 97% specificity. Male vocalizations could be identified using cd1 coefficients with 88% sensitivity and 100% specificity. For leaks at the mouthpiece, cd3 thresholds of flow could identify these events with 98% sensitivity and 99% specificity. Thus, this method provided an accurate, easy, and automated technique for detecting and removing artifacts from measurements of respiratory impedance using FOT.