Complexity of physiological responses decreases in high-stress musical performance

Abstract

For musicians, performing in front of an audience can cause considerable apprehension; indeed, performance anxiety is felt throughout the profession, with wide ranging symptoms arising irrespective of age, skill level and amount of practice. A key indicator of stress is frequency-specific fluctuations in the dynamics of heart rate known as heart rate variability (HRV). Recent developments in sensor technology have made possible the measurement of physiological parameters reflecting HRV non-invasively and outside of the laboratory, opening research avenues for real-time performer feedback to help improve stress management. However, the study of stress using standard algorithms has led to conflicting and inconsistent results. Here, we present an innovative and rigorous approach which combines: (i) a controlled and repeatable experiment in which the physiological response of an expert musician was evaluated in a low-stress performance and a high-stress recital for an audience of 400 people, (ii) a piece of music with varying physical and cognitive demands, and (iii) dynamic stress level assessment with standard and state-of-the-art HRV analysis algorithms such as those within the domain of complexity science which account for higher order stress signatures. We show that this offers new scope for interpreting the autonomic nervous system response to stress in real-world scenarios, with the evolution of stress levels being consistent with the difficulty of the music being played, superimposed on the stress caused by performing in front of an audience. For an emerging class of algorithms that can analyse HRV independent of absolute data scaling, it is shown that complexity science performs a more accurate assessment of average stress levels, thus providing greater insight into the degree of physiological change experienced by musicians when performing in public.

Simulating and stimulating performance: introducing distributed simulation to enhance musical learning and performance

“…The relative LF/HF power ratio, although the subject of recent debate as to whether it actually reflects the sympatho-vagal balance (Billman, 2013) and about its accuracy for dynamic stress level assessment (Williamon et al, 2013), has been widely used in the study of stress in performance (Nakahara et al, 2009; for a review, see Billman, 2013). …”

“…While the simplest measures of HRV are the mean of the RR time series and the standard deviation about its mean, both of these statistics are based on the absolute magnitude of the RR interval. However, in many applications, relative measures such as the power ratio of the low- and high-frequency components of HRV allow for more reliable comparisons between participants (for further information, see “Data treatment and analysis” and Williamon et al, 2013). Finally, the existing studies test the hypothesis that performance exposure using virtual environments can ameliorate psychological and physiological symptoms of performance anxiety; while this seems plausible on the surface, the inter- and intra-individual variability in how people experience and interpret such symptoms can be extremely large (Williamon, 2004).…”

A Pilot Study Evaluating the Physiological Parameters of Performance-Induced Stress in Undergraduate Music Students

“…According to Williamon et al [12], the high-frequency component of the HRV reflects parasympathetic nervous system activity, whereas the low-frequency component reflects a balance between orthosympathetic and parasympathetic nervous system activity. Stress incudes changes in the balance between the parasympathetic and the sympathetic nervous system in favor of sympathetic activity.…”

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

“…To this end, the analysis of HRV is performed by sample entropy (SampEn), as it is designed to operate on real-world nonlinear and non-stationary data [2], low frequency (LF HRV ) and high frequency (HF HRV ) power of the HRV frequency spectrum and their ratio (LF/HF). While a low SampEn designates a high regularity and may be linked to high levels of stress [3], an increased SampEn corresponds to an increase in randomness in the data, suggesting a physically relaxed state (baseline) [4]. Although not without controversy, the LF HRV band in HRV, 0.04-0.15 Hz, is thought to reflect the activity of the sympathetic nervous system (SNS; high stress) and the baroreflex (blood pressure), while the HF HRV band, 0.15-0.4 Hz, is believed to correspond to the activity of the parasympathetic nervous system (PNS; relaxed state) and respiratory sinus arrhythmia (RSA), naturally occurring heart rate modulations due to breathing [5,6].…”