Motion artifact resulting from electrode and patient movement is a significant source of noise in ECG, EEG, EMG, and impedance pneumography recording. Noise resulting from motion is particularly troublesome in ambulatory ECG recordings, such as those made during Holter monitoring or stress tests, because the bandwidth of the motion artifact overlaps with the ECG signal bandwidth. The authors investigated the effect of an adaptive motion-artifact removal algorithm on the performance of a standard QRS detector. They made four ECG recordings on each of the three subjects while manually generating artifact. Adaptive noise removal was applied to the ECG signal using a skin-stretch signal as the noise reference. Adaptive noise removal reduced the number of false QRS detections in the records from 380 to 104, for an average reduction in false detections of 72.6%. False-detection reductions for individual records ranged from 12% to 93%.