Sensors and Game Synchronization for Data Analysis in eSports eSports industry has greatly progressed within the last decade in terms of audience and fund rising, broadcasting, networking and hardware. Since the number and quality of professional team has evolved too, there is a reasonable need in improving skills and training process of professional eSports athletes. In this work, we demonstrate a system able to collect heterogeneous data (physiological, environmental, video, telemetry) and guarantying synchronization with 10 ms accuracy. In particular, we demonstrate how to synchronize various sensors and ensure post synchronization, i.e. logged video, a socalled demo file, with the sensors data. Our experimental results achieved on the CS:GO game discipline show up to 3 ms accuracy of the time synchronization of the gaming computer.

IEEE 1588Based General and Precise Time Synchronization Method for Multiple Sensors * An increasing number of robotic systems contain multiple sensors, and the accurate timestamps of sensors are crucial for fusing multiple sensors information in robot applications. However, the accuracy and stability of traditional timestamp synchronization algorithms are degraded when synchronizing the timestamps of multiple sensors, due to the clock inconsistency, asynchronous trigger delay, and variable transmission delay. This paper presents a general and precise time synchronization method for multiple sensors with respect to a local clock (i.e. typically a computerxe2x80x99s internal clock). First, to reduce the software scheduling delay, an IEEE 1588based method, which combines hardware and software to obtain timestamps, is formulated to modify the masterslave timestamp acquisition location. Second, a hardware synchronization trigger method is proposed to reduce the runtime of trigger threads in the software, by introducing the microprocessor to trigger multiple sensors synchronously. Finally, a timestamp matching method is proposed to reduce the unreliability of variable communication delays by matching the trigger timestamp and the timestamp of data reception. To the best of our knowledge, this approach is the first synchronization method to combine hardware and software to obtain the timestamps of multiple sensors. Results show that the ability of our method can estimate time offset to microsecond accuracy.