Modelling stress in public speaking: Evolution of stress levels during conference presentations

Theerasak Chanwimalueang, Lisa Aufegger, Wilhelm von Rosenberg, Danilo P. Mandic
<span title="">2016</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="" style="color: black;">2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</a> </i> &nbsp;
The Electrocardiogram (ECG) collected in real-life scenarios is often noisy and contaminated with motion artefacts. This study proposes a new framework to analyse the heart rate variability (HRV) in mobile scenarios by introducing novel R-peak detection and HRV detrending algorithms. The R-peak detection combines matched filtering and Hilbert transform, while detrending the HRV is performed using empirical mode decomposition with novel physically meaningful stopping criteria. Next, four
more &raquo; ... tive metricssample entropy, LF HRV , HF HRV and LF/HF ratio -are used to estimate stress levels in two public speaking events: (i) a presentation in front of an audience and (ii) an interactive poster presentation, both at ICASSP 2015. We show that the proposed framework makes it possible to detect distinctive 'stress-patterns' in the structural complexity of the HRV, thus verifying the complexity-loss hypothesis in physiological research.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1109/icassp.2016.7471788</a> <a target="_blank" rel="external noopener" href="">dblp:conf/icassp/ChanwimalueangA16</a> <a target="_blank" rel="external noopener" href="">fatcat:ng4l62zdpzczpoiissid3grxg4</a> </span>
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