This paper presents a K-NN based algorithm that handles artifacts by detecting and interpolating it with nearby existing data for heart rate variability (HRV) analysis.The
approach proposed here is an attempt to remove artifacts from inter beat interval (IBI) signal, produced by spurious distortions such as muscle movement, sneezing, etching, and shaking of the part of the body that is connected to the electrodes of the ECG sensor while collecting the signal. The experimental work shows a promising performance in handling artifacts from IBI signals.