Abstract: To ensure the occupational safety and health of firefighters, improve their physical fitness and training effectiveness, research is being conducted on the fusion technology of multi sign sensor information for firefighters. In response to the problem that vital sign monitoring equipment is susceptible to harsh environments during firefighting training, significant work movements of firefighters, and interference from personal protective equipment of firefighters, resulting in reduced accuracy of data collection and ineffective or missing data collection, this article adopts the design of multi-mode sensor cross collection to monitor firefighter physical sign indicators. Multi-mode sensors are used to monitor firefighter's electrocardiogram and pulse waves from different positions, and the collected signals are denoised using wavelet threshold contraction method and fast sliding mean filtering. Then, feature recognition and fusion are carried out based on the discrete and continuous types of data. After integration, tests were conducted in several scenarios such as power bicycles, heavy rain environments, firefighter tire rolling, and drag dummy training, indicating a significant improvement in the monitoring accuracy and fault tolerance of the multi-mode vital sign monitoring unit.

Key words: firefighters occupational safety and health, multi-sensor information fusion, firefighter vital signs, signs monitoring