Athlete monitoring is a major field of interest for professional and recreational runners as well as for coaches to improve performance and reduce injury risk. The development of inertial sensors in recent years offers the opportunity to improve the number of monitored training sessions significantly. This research used a self-developed inertial sensor in conjunction with a motion tracking system and four smart bands to record the runner`s movement and extract parameters such as step numbers and frequencies. The data recorded were calibrated before it was high-pass filtered to remove gravity components from the signal. A peak detection algorithm was developed to find the number of steps, which have been further used to compare the different systems (IMU, motion capture, smart bands) and find their agreement. The results showed a very strong correlation between the IMU and the motion tracking system of r2 = 0.998, and an r2 = 0.996 between the IMU and one smart band
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