A real-time hyperventilation trend monitoring algorithm in-flight

Hyperventilation will cause vertigo, spasm, loss of consciousness etc., which seriously affects flight safety. For pilots, it is not easy to distinguish between hyperventilation and hypoxia. In this paper, a real-time hyperventilation trend monitoring algorithm in-flight is proposed to help pilot judge and prevent hyperventilation. Firstly, we propose RP pressure to instead of mask pressure to de-noise, and respiratory rate validity to eliminate breathing state with very low signal-to-noise ratio. Then, based on RP pressure and respiratory rate validity, we propose optimized respiratory rate detection method. The accuracy of optimized respiratory rate detection method was verified on flight data. Finally, based on accurate respiratory rate, a real-time hyperventilation trend monitoring algorithm is proposed, which was applied to 200 hours of flight data and ground system testing data including multiple flight conditions. The results are consistent with actual data and feedback of pilots.