Massaroni Carlo, Senesi Guglielmo, Schena Emiliano, Silvestri Sergio
a Unit of Measurements and Biomedical Instrumentation, Departmental Faculty of Engineering , Università Campus Bio-Medico di Roma , Rome , Italy.
Comput Methods Biomech Biomed Engin. 2017 Dec;20(16):1678-1689. doi: 10.1080/10255842.2017.1406081. Epub 2017 Nov 22.
Breathing parameters can be measured by motion capture systems by placing photo-reflective markers on the chest wall. A computational model is mandatory to compute the breathing volume and to calculate temporal and kinematical features by the gathered markers trajectories. Despite different methods based on different geometrical approaches can be adopted to compute volumes, no information about their differences in the respiratory evaluation are available. This study investigated the performances of four methods (conventional, prism-based, convex hull with boundary condition, based on Delaunay triangulation) using an optoelectronic motion capture system, on twelve healthy participants during 30 s of breathing. Temporal trends of volume traces, tidal volume values, and breathing durations were compared between methods and spirometry (used as reference instrument). Additionally, thoraco-abdominal motion patterns were compared between methods by analysing the compartmental contributions and their variability. Results shows comparable similarities between the volume traces obtained using spirometry, prism-based and conventional methods. Prism-based and convex hull with boundary condition methods show lower bias in tidal volumes estimation up to 0.06 L, compared to the conventional and Delaunay triangulation methods. Prism-based method shows maximum differences of 30 mL in the comparison of compartmental contributions to the total volume, by resulting in a maximum deviation of 1.6% in the percentage contribution analysis. In conclusion, our finding demonstrated the accuracy of the non-invasive MoCap-based breathing analysis with the prism-based method tested. Data provided in this study will lead researchers and clinicians in the computational method choice for temporal and volumetric breathing analysis.
通过在胸壁上放置光反射标记,运动捕捉系统可以测量呼吸参数。必须使用计算模型来计算呼吸量,并根据收集到的标记轨迹计算时间和运动学特征。尽管可以采用基于不同几何方法的不同方法来计算体积,但关于它们在呼吸评估中的差异尚无可用信息。本研究使用光电运动捕捉系统,对12名健康参与者在30秒呼吸过程中,研究了四种方法(传统方法、基于棱柱的方法、带边界条件的凸包法、基于德劳内三角剖分的方法)的性能。比较了各方法与肺活量计(用作参考仪器)之间的体积曲线时间趋势、潮气量值和呼吸持续时间。此外,通过分析各部分的贡献及其变异性,比较了各方法之间的胸腹运动模式。结果表明,使用肺活量计、基于棱柱的方法和传统方法获得的体积曲线具有可比的相似性。与传统方法和德劳内三角剖分方法相比,基于棱柱的方法和带边界条件的凸包法在潮气量估计中的偏差更低,可达0.06升。在比较各部分对总体积的贡献时,基于棱柱的方法显示出最大差异为30毫升,在百分比贡献分析中导致最大偏差为1.6%。总之,我们的研究结果证明了基于非侵入性运动捕捉的呼吸分析与经测试的基于棱柱的方法的准确性。本研究提供的数据将引导研究人员和临床医生在选择用于时间和体积呼吸分析的计算方法时做出决策。