**5. Conclusions**

Reliable non-contact cardiovascular parameters monitoring can be difficult because many factors can contaminate the pulse signal, e.g. a subject movement and illumination changes. In this article we examined the accuracy of HR estimation for various human activities during typical HCI scenarios (sitting still, reading text, typing text and playing game). We tested three different heart rate estimation algorithms and four signal extraction methods. The results show that the proposed signal extraction method (ExG) provides acceptable results (65% *sRate* for PSD), while being much faster to calculate that the ICA method. We have found that, depending on the scenario being studied, a different combination of signal extraction methods and pulse estimation algorithm ensures optimal heart rate detection results. We also noticed that the choice of signal representation has a greater impact on accuracy than the choice of estimation algorithm.

**Funding:** This research was funded by the AGH University of Science and Technology in year 2019 from the subvention granted by the Polish Ministry of Science and Higher Education.

**Conflicts of Interest:** The authors declare no conflict of interest.
