A Robust Method for Estimating Respiration Rate Using Wi-Fi in Noisy Environments

Respiration rate is a critical parameter for assessing the physiological well-being of patients. Traditional methods typically rely on contact-based and visual devices, which pose challenges for long-term monitoring due to issues of comfort and privacy. This paper proposes a non-contact method for acquiring respiration rates using Wi-Fi Radio Frequency (RF) electromagnetic waves. We address the challenge of accurately estimating respiration rates by presenting a robust approach that leverages receiver antenna diversity to enhance the signal-to-noise ratio (SNR), thereby significantly improving estimation accuracy. Our method employs the maximal ratio combining technique to integrate the received signals effectively. Experimental results demonstrate that the proposed method achieves the overall Mean Absolute Error (MAE) of 0.7 bpm across all trials, compared to ground truth wearable respiration belts, indicating reliable respiration estimation using Wi-Fi system.