Algorithm 2 Multivariate EMD.
1:	Choose a suitable point set for sampling a (p − 1)-sphere;
2:	Calculate a projection, denoted by qθv(t), of the input signal s(t) along the direction vector xθv, for all v (the whole set of direction vectors), giving $q_{{\mathrm{\theta }}_v}{\left(t\right)}_{v=1}^V$ as the set of projections;
3:	Find the time instants ${\left\{t_{{\mathrm{\theta }}_v}^i\right\}}_{v=1}^V$ corresponding to the maxima of the set of projected signals $q_{{\mathrm{\theta }}_v}{\left(t\right)}_{v=1}^V$;
4:	Interpolate [ $t_{{\mathrm{\theta }}_v}^i$, $\mathbf{\text{s}}\left(t_{{\mathrm{\theta }}_v}^i\right)$] to obtain multivariate envelope curves ${\mathbf{\text{e}}}_{{\mathrm{\theta }}_v}{\left(t\right)}_{v=1}^V$;
5:	For a set of V direction vectors, the mean m(t) of the envelope curves is calculated as: $$\mathbf{\text{m}}\left(t\right)=\frac{1}{V}\sum _{v=1}^V{\mathbf{\text{e}}}_{{\theta }_v}\left(t\right)$$ (2)
6:	Extract ‘detail’ d(t) using d(t) = s(t) − m(t). If d(t) fulfils the stoppage criterion [33] for a multivariate IMF, apply the above procedure to s(t) − d(t); otherwise, apply it to d(t).