In recent years frame approximation, in particular sparse approximation received a lot of attention, mostly due to the advent of compressed sensing. While there is how already a huge amount of literature dealing with the 1D- and 2D-case little is done in higher dimension. In this talk we will show how Clifford analysis can help studying (sparse) approximation in higher dimensions and give some examples.