Takamoto Hiroki, Nishine Hiroki, Sato Shohei, Sun Guanghao, Watanabe Sadao, Seokjin Kim, Asai Masahito, Mineshita Masamichi, Matsui Takemi
Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan.
Department of Respiratory Medicine, St. Marianna University School of Medicine, Kanagawa, Japan.
Front Physiol. 2020 Sep 11;11:552942. doi: 10.3389/fphys.2020.552942. eCollection 2020.
Obstructive pulmonary diseases, such as diffuse panbronchiolitis (DPB), asthma, chronic obstructive pulmonary disease (COPD), and asthma COPD overlap syndrome (ACOS) trigger a severe reaction at some situations. Detecting early airflow limitation caused by diseases above is critical to stop the progression. Thus, there is a need for tools to enable self-screening of early airflow limitation at home. Here, we developed a novel non-contact early airflow limitation screening system (EAFL-SS) that does not require calibration to the individual by a spirometer. The system is based on an infrared time-of-flight (ToF) depth image sensor, which is integrated into several smartphones for photography focusing or augmented reality. The EAFL-SS comprised an 850 nm infrared ToF depth image sensor (224 × 171 pixels) and custom-built data processing algorithms to visualize anterior-thorax three-dimensional motions in real-time. Multiple linear regression analysis was used to determine the amount of air compulsorily exhaled after maximal inspiration (referred to as the forced vital capacity, FVC ) from the ToF-derived anterior-thorax forced vital capacity (FVC), height, and body mass index as explanatory variables and spirometer-derived FVC as the objective variable. The non-contact measurement is automatically started when an examinee is sitting 35 cm away from the EAFL-SS. A clinical test was conducted with 32 COPD patients (27/5 M/F, 67-93 years) as typical airflow limitation cases recruited at St. Marianna University Hospital and 21 healthy volunteers (10/11 M/F, 23-79 years). The EAFL-SS was used to monitor the respiration of examinees during forced exhalation while sitting still, and a spirometer was used simultaneously as a reference. The forced expiratory volume in 1 s (FEV1% ) was evaluated as a percentage of the FVC , where values less than 70% indicated suspected airflow limitation. Leave-one-out cross-validation analysis revealed that this system provided 81% sensitivity and 90% specificity. Further, the FEV1 values were closely correlated with that measured using a spirometer ( = 0.85, < 0.0001). Hence, EAFL-SS appears promising for early airflow limitation screening at home.
阻塞性肺疾病，如弥漫性泛细支气管炎（DPB）、哮喘、慢性阻塞性肺疾病（COPD）和哮喘-COPD重叠综合征（ACOS），在某些情况下会引发严重反应。检测由上述疾病引起的早期气流受限对于阻止疾病进展至关重要。因此，需要能够在家中进行早期气流受限自我筛查的工具。在此，我们开发了一种新型非接触式早期气流受限筛查系统（EAFL-SS），该系统无需通过肺活量计针对个体进行校准。该系统基于红外飞行时间（ToF）深度图像传感器，该传感器已集成到多款用于拍照对焦或增强现实的智能手机中。EAFL-SS由一个850纳米红外ToF深度图像传感器（224×171像素）和定制的数据处理算法组成，以实时可视化前胸三维运动。多元线性回归分析用于根据ToF衍生的前胸用力肺活量（FVC）、身高和体重指数作为解释变量，以及肺活量计衍生的FVC作为目标变量，来确定最大吸气后强制呼出的空气量（称为用力肺活量，FVC）。当受检者坐在距离EAFL-SS 35厘米处时，非接触测量自动开始。在圣玛丽安娜大学医院招募了32例COPD患者（27例男性/5例女性，67 - 93岁）作为典型气流受限病例，并选取21名健康志愿者（10例男性/11例女性，23 - 79岁）进行了一项临床试验。使用EAFL-SS在受检者静息状态下进行用力呼气时监测其呼吸情况，同时使用肺活量计作为参考。将1秒用力呼气量（FEV1%）评估为FVC的百分比，其中值小于70%表示疑似气流受限。留一法交叉验证分析表明，该系统的灵敏度为81%，特异性为90%。此外，FEV1值与使用肺活量计测量的值密切相关（= 0.85，< 0.0001）。因此，EAFL-SS在家中进行早期气流受限筛查方面似乎很有前景。
