Wearable accelerometry provides easily portable systems that supply real-time data adequate for gait analysis. When they do not provide direct measurement of a spatio-temporal parameter of interest, such as step length, it has to be estimated with a mathematical model from indirect sensor measurements. In this work we are concerned with the accelerometry-based estimation of the step length in straight line human walking. We compare five step length estimators. Measurements were taken from a group of four adult men, adding up a total of 800 m per individual of walking data. Also modifications to these estimators are proposed, based on biomechanical considerations. Results show that this modifications lead to improvements of interest over previous methods.