  We propose an estimator of the kernel-based conditional mean dependence
measure obtained from an appropriate modification of a naive estimator based on
usual empirical estimators. We then get asymptotic normality of this estimator
both under conditional mean independence hypothesis and under the alternative
hypothesis. A new test for conditional mean independence of random variables
valued into Hilbert spaces is then introduced.
