The main goal of the experimental work is to see how well the algorithm performs in handling artifacts from IBI signal while calculating the HRV features. For evaluation
ten visually inspected ‘No artifacts’ and three ‘With artifacts’ measurements as discussed in the ‘Data collection and HRV features’ section are considered.
Now, from these three ‘With artifacts’ measurements 30 corrupted measurements are generated by introducing three random sets of artifacts and randomly placing them with each ‘No artifacts’ measurements. Then the time and frequency domain features are calculated for these 30 ‘With artifacts’ measurements. The intention is to see how the features values are deviated for the ‘With artifacts’measurements compare to ‘No artifacts’ measurements using the algorithm. The performance of the proposed algorithm is investigated both in detecting and interpolating artifacts. Another algorithm i.e., the
hierarchical algorithm is introduced for detecting the outlier and results are compared with the proposed algorithm. Third party software [19] which has applied cubic spline interpolation is considered to evaluate the performance of the proposed algorithm.