In this paper a new algorithm is proposed for QRS onset and offset detection in single lead electrocardiogram (ECG) records. In a first step, the R peak is detected in order to use it as reference to roughly limit the research of the QRS onset and offset. Then, an auxiliary signal is defined from the envelope of the ECG signal. Finally, a statistical hypothesis testing is applied to the auxiliary signal in order to detect mean changes. The performances of the algorithm have been evaluated using the PhysioNet QT database. The mean and standard deviation of the differences between onsets and offsets manually marked by cardiologists and those detected by the proposed algorithm are computed. The standard deviations obtained in this work are around the tolerances accepted by expert physicians, and slightly outperform the results obtained by the other known algorithms evaluated with the same database.