Seppanen Tiina M, Kananen Janne, Alho Olli-Pekka, Seppanen Tapio
Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:7857-60. doi: 10.1109/EMBC.2015.7320213.
Respiratory disorders are a very common and growing health problem. Signal waveforms of respiratory airflow and volume may indicate pathological signs of several diseases and, thus, it would be important to measure them accurately. Currently, devices used in respiration measurements are mostly obtrusive in nature interfering with the natural respiration patterns. We used a depth camera for the continuous measurement of respiratory function without contact on a subject. We propose a novel calibration method which enables accurate estimates of the respiratory airflow waveforms from the depth camera data. Eight subjects were measured with the depth camera and spirometer at the same time using different breathing styles. Results show that not only the respiratory volume and respiratory rate (RR) can be computed precisely from the estimated respiratory airflow, but also the respiratory airflow waveforms are very accurate. This offers interesting opportunities, e.g. in pulmonary and critical care medicine, when objective measurements are required.
呼吸系统疾病是一个非常常见且日益严重的健康问题。呼吸气流和容积的信号波形可能表明多种疾病的病理迹象，因此，准确测量这些波形非常重要。目前，用于呼吸测量的设备大多本质上具有侵入性，会干扰自然呼吸模式。我们使用深度相机在不接触受试者的情况下连续测量呼吸功能。我们提出了一种新颖的校准方法，能够根据深度相机数据准确估计呼吸气流波形。八名受试者使用不同呼吸方式，同时用深度相机和肺活量计进行测量。结果表明，不仅可以根据估计的呼吸气流精确计算呼吸容积和呼吸频率（RR），而且呼吸气流波形也非常准确。这提供了有趣的机会，例如在需要进行客观测量的肺病和重症监护医学领域。
