The approximate entropy (ApEn) is a measure of systems complexity. The implementation of the method is computationally expensive and requires execution time analogous to the square of the size of the input signal. We propose here a fast algorithm which speeds up the computation of approximate entropy by detecting early some vectors that are not similar and by excluding them from the similarity test. Experimental analysis with various biomedical signals revealed a significant improvement in execution times.