Robust beat detection under noisy conditions is required in order to obtain a correct clinical interpretation of the ECG in ambulatory settings. This paper describes the evaluation and optimization of a beat detection algorithm that is robust against high levels of noise. An evaluation protocol is defined in order to study four different characteristics of the algorithm: non-rhythmic patterns, different levels of SNR, exact peak detection and different levels of physical activity. This protocol is based on the MIT/BIH arrhythmia database and additional ECG recordings obtained under different levels of physical activity measured by 2-axis accelerometers. The optimized algorithm obtained a Se=99.65% and +P=99.79% on the MIT/BIH arrhythmia database while keeping a good performance on ECGs with high levels of activity (overall of Se=99.86%, +P=99.91%). In addition, this method was optimized to work in real time, for future implementation in a Wireless ECG sensor based on a microprocessor.