This research paper presents an in-depth validation of a developed inertial tracking system for human motion analysis. The system integrates gyroscopes, accelerometers, and magnetometers, and is controlled via Wi-Fi. The validation process involved two key experiments. The first experiment aimed to determine the time points involved between the collection of signals by the developed inertial tracker and their reception by an effector system. This was achieved by varying the payload formation time and the number of sensors. The second experiment aimed to determine the reliability of the data over time, according to constant linear variations to which an inertial sensor was subjected. The sensor was fixed on a shaker, and the frequency of the generated wave changed proportionally over time. The results revealed a maximum average time lag of approximately 12 ms in information transmission latency, which is well within acceptable limits for real-time applications. Also, it is shown that the system maintained data reliability even under dynamic conditions. Therefore, these findings underscore the system’s robustness and its potential impact on fields such as medical diagnostics, rehabilitation, and human-computer interaction. The paper concludes with a discussion on the challenges faced in ensuring data reliability and network latency, and future directions for this research.