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.