Respiratory frequency is an important physiological feature commonly used to assess health. However, the current measurements involve dedicated devices which not only increase the medical cost but also make health monitoring inconvenient. Earlier studies have shown that respiratory frequency could be extracted from electrocardiography (ECG) signal, but little was done to assess the possibility of extracting respiratory frequency from oscillometric cuff pressure pulses (OscP) or Korotkoff sounds (KorS), which are normally used for measuring blood pressure and more easily accessible than the ECG signal. This study presented a method to extract respiratory frequency from OscP and KorS during clinical blood pressure measurement. The method was evaluated with clinical data collected from 15 healthy participants, and its measurement accuracy was compared with a reference respiratory rate obtained with a magnetometer. Experimental results showed small non-significant mean absolute bias (0.019 Hz for OscP and 0.024 Hz for KorS) and high correlation (0.7 for both OscP and KorS) between the reference respiratory frequency and respiratory frequency extracted from OscP or KorS, indicating the high reliability of extracting respiratory frequency from OscP and KorS during normal blood pressure measurement.
|Title of host publication||Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS|
|Publication status||Published - 18 Oct 2016|
|Event||38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Orlando, United States|
Duration: 16 Aug 2016 → 20 Aug 2016
|Conference||38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society|
|Period||16/08/16 → 20/08/16|
Chen, D., Chen, F., Murray, A., & Zheng, D. (2016). A method for extracting respiratory frequency during blood pressure measurement, from oscillometric cuff pressure pulses and Korotkoff sounds recorded during the measurement. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS IEEE. https://doi.org/10.1109/EMBC.2016.7591670