Triangle Simplex Plots for Representing and Classifying Heart Rate Variability

Simplex plots afford barycentric mapping and visualisation of the ratio of three variables as positions in an equilateral triangle (2-simplex); for instance, time distribution in three-interval musical rhythms. We propose a novel use of simplex plots to visualise and analyse the balance of autonomic variables in a music condition. RR interval series were collected from a musical trio (pianist, violinist, cellist) during baseline (5 min) and music performance, Schubert's Trio Op. 100, Andante con moto t> 1 0 min), in nine rehearsal sessions. The power spectrum components, very low (VLF), low (LF), and high (HF), were calculated from RR intervals in 30 s windows (hop size 15 s), then normalised to 1 and visualised in tri-angle simplex plots. Spectral clustering was used to group data points between baseline and music period. A strong negative correlation in clustering accuracy and number of performance was observed for the violinist $(r=-0.80, p\leq$ .01, accuracy range: [0.64, 0.94]) andpianist $(r=-0.62, p=.073, [0.64,0.80])$, suggesting adaptation of their car-diac response in time; a non-significant correlation was observedfor the cellist $(r=-0.23, p=,55,\ [0,50,0,61])$. Using simplex plots, we can effectively represent VLF, LF and HF components and track changes in autonomic response over a series of music rehearsals to observe au-tonomic states and changes over time.