The present work aims to develop an embedded system for data acquisition and transmission of dynamic parameters from a bicycle and biomedical data of the cyclist during the physical activity. The acquired data can be used to verify and validate parameters regarding the longitudinal dynamic model of the bycicle, allowing comparisons with simulated data. In addition, the monitoring of biomedical parameters allows an analysis of the functioning of respiratory and cardiovascular systems throughout physical activity, quantifying the influence of the cyclist effort during exercise and its impacts on the body. The correlation between the dynamic parameters and the biomedical data can present a performance measurement for the cyclist, establishing standards and limits that the cyclist can endure without any health harm. It is also developed an remote station to visualize some of the acquired data in real time, to allow constant monitoring of the physical activity. Based on the acquired data, two algorithms are implemented in order to allow the extraction of more information of the activity. The first one is a trajectory reconstruction algorithm based on inertial data that allows a kinematic analysis of the bycicle movement. And the second is a QRS detection algorithm on the cyclist s ECG, which is the basis algorithm for digital processing of electrocardiograms.