Let $H_k$ be the $k$th Hankel matrix of the sequence.
For the forward direction of the equivalence, we use the fact that positive definiteness of each $H_k$ individually implies positive determinant of $H_k$.
In more detail:
Akhiezer defines a positive sequence as one in which every quadratic (Hankel) form is positive definite. This translates to $c^T H_k c > 0$ for all nonzero $c$. For example in the case $k=2$, the quadratic form is $s_0c_0^2 + 2s_1c_0c_1 + s_2c_1^2 = c^T H_2 c$.
Now let $c$ be any eigenvector of $H_k$ with eigenvalue $\lambda$ ($c$ is nonzero by definition of eigenvector). Then $0 < c^T H_k c = c^T \lambda c = \lambda |c|^2,$ which shows $\lambda > 0.$ so all eigenvalues of $H_k$ are greater than 0, and the determinant of $H_k$, which is the product of its eigenvalues, is positive. Note that this argument is not specific to Hankel or even symmetric matrices, in general, positive definiteness implies positive determinant.
The other direction follows immediately from Sylvester's Criterion (https://en.wikipedia.org/wiki/Sylvester%27s_criterion)
, which characterizes positive definite matrices as having all their leading minors positive (necessarily and sufficiently).
For $n \geq k$ we find $H_k$ embedded in $H_n$ as the $k$th leading minor of $H_n$. Assuming that $H_i$ for $i \leq n$ has positive determinant, Sylvester's Criterion implies that $H_n$ is positive definite.
Since $H_k$ by assumption has positive determinant for all $k$, this shows that all Hankel matrices of the sequence are positive-definite.