  Let $X_1,X_2, \ldots$ be independent and identically distributed random
elements taking values in a separable Hilbert space $\mathbb{H}$. With
applications for functional data in mind, $\mathbb{H}$ may be regarded as a
space of square-integrable functions, defined on a compact interval. We propose
and study a novel test of the hypothesis $H_0$ that $X_1$ has some unspecified
non-degenerate Gaussian distribution. The test statistic
$T_n=T_n(X_1,\ldots,X_n)$ is based on a measure of deviation between the
empirical characteristic functional of $X_1,\ldots,X_n$ and the characteristic
functional of a suitable Gaussian random element of $\mathbb{H}$. We derive the
asymptotic distribution of $T_n$ as $n \to \infty$ under $H_0$ and provide a
consistent bootstrap approximation thereof. Moreover, we obtain an almost sure
limit of $T_n$ as well as a normal limit distribution of $T_n$ under
alternatives to Gaussianity. Simulations show that the new test is competitive
with respect to the hitherto few competitors available.
