Analysis of Heart Rate Variability (HRV) is an active area of research in the engineering and the medical communities. Current studies use medical-grade ECG signals, from a limited number of available databases. On the other hand, the trend for physiological measurements is towards less obtrusive, wearable devices. It is therefore of interest to apply HRV analysis to signals from such wearable sensors, whose outputs could exhibit varying levels of noise caused by motion artifacts. The main contribution of this paper is the quantification of the impact of imperfect HRV measurements due to motion artifacts on classifiers which use standard time domain and spectral HRV features. The analysis could potentially lead to development of more robust features and classifiers for use in wearable and non-controlled environments.

Additional Metadata
Keywords classification, Heart Rate Variability (HRV), motion artifacts
Persistent URL dx.doi.org/10.1109/MeMeA.2013.6549726
Conference IEEE International Symposium on Medical Measurements and Applications, MeMeA 2013
Citation
Nikolic-Popovic, J. (Jelena), & Goubran, R. (2013). Impact of motion artifacts on Heart Rate Variability measurements and classification performance. Presented at the IEEE International Symposium on Medical Measurements and Applications, MeMeA 2013. doi:10.1109/MeMeA.2013.6549726