Karlen Walter, Gan Heng, Chiu Michelle, Dunsmuir Dustin, Zhou Guohai, Dumont Guy A, Ansermino J Mark
Department of Electrical & Computer Engineering, The University of British Columbia, Vancouver, Canada.
Department of Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, Vancouver, Canada.
PLoS One. 2014 Jun 11;9(6):e99266. doi: 10.1371/journal.pone.0099266. eCollection 2014.
The recommended method for measuring respiratory rate (RR) is counting breaths for 60 s using a timer. This method is not efficient in a busy clinical setting. There is an urgent need for a robust, low-cost method that can help front-line health care workers to measure RR quickly and accurately. Our aim was to develop a more efficient RR assessment method. RR was estimated by measuring the median time interval between breaths obtained from tapping on the touch screen of a mobile device. The estimation was continuously validated by measuring consistency (% deviation from the median) of each interval. Data from 30 subjects estimating RR from 10 standard videos with a mobile phone application were collected. A sensitivity analysis and an optimization experiment were performed to verify that a RR could be obtained in less than 60 s; that the accuracy improves when more taps are included into the calculation; and that accuracy improves when inconsistent taps are excluded. The sensitivity analysis showed that excluding inconsistent tapping and increasing the number of tap intervals improved the RR estimation. Efficiency (time to complete measurement) was significantly improved compared to traditional methods that require counting for 60 s. There was a trade-off between accuracy and efficiency. The most balanced optimization result provided a mean efficiency of 9.9 s and a normalized root mean square error of 5.6%, corresponding to 2.2 breaths/min at a respiratory rate of 40 breaths/min. The obtained 6-fold increase in mean efficiency combined with a clinically acceptable error makes this approach a viable solution for further clinical testing. The sensitivity analysis illustrating the trade-off between accuracy and efficiency will be a useful tool to define a target product profile for any novel RR estimation device.
测量呼吸频率(RR)的推荐方法是使用计时器计数60秒内的呼吸次数。在繁忙的临床环境中,这种方法效率不高。迫切需要一种可靠、低成本的方法,以帮助一线医护人员快速准确地测量RR。我们的目标是开发一种更有效的RR评估方法。通过测量在移动设备触摸屏上点击获得的呼吸之间的中位时间间隔来估计RR。通过测量每个间隔的一致性(与中位数的%偏差)来持续验证估计值。收集了30名受试者使用手机应用程序从10个标准视频中估计RR的数据。进行了敏感性分析和优化实验,以验证可以在不到60秒的时间内获得RR;计算中纳入更多点击时准确性会提高;排除不一致的点击时准确性会提高。敏感性分析表明,排除不一致的点击并增加点击间隔的数量可改善RR估计。与需要计数60秒的传统方法相比,效率(完成测量的时间)显著提高。准确性和效率之间存在权衡。最平衡的优化结果提供了平均效率9.9秒和归一化均方根误差5.6%,在呼吸频率为40次/分钟时相当于2.2次/分钟。平均效率提高了6倍,同时误差在临床上可接受,这使得该方法成为进一步临床测试的可行解决方案。说明准确性和效率之间权衡的敏感性分析将是为任何新型RR估计设备定义目标产品概况的有用工具。