The complex evaluation of thermo-physiological comfort for a particular garment is still challenging, as it depends on the different structural parameters and individual properties of textiles. Measurement of relevant fabric characteristics requires very specific laboratory equipment, such as an M 290 moisture management tester (SDL ATLAS) or similar. For this reason, it is obvious that there is a great demand to predict the overall moisture management capability ( OMMC) based on the individual properties that are responsible for clothing comfort and testing according to different standards rather than OMMC-specific calculation using the M 290 tester. Therefore, in this research, linear regression analysis was performed using MATLAB software to predict the OMMC for cotton–polyester fabrics knitted in two patterns, namely 1 × 1 rib and half-Milano rib, using four percentages of fibers. Water vapor permeability, water vapor resistance, water absorption capacity, water absorption time, and air permeability were used as input variables for linear regression analysis to predict the OMMC of fabrics. The performed analysis has shown that the OMMC is directly dependent on the relative water vapor permeability and air permeability, and the linear regression equation suggested in this research can predict the suitability of a textile for a particular garment concerning its moisture management behavior.

中文翻译：

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棉涤针织物吸湿排汗相关性能的线性回归分析

对特定服装的热生理舒适度的复杂评估仍然具有挑战性，因为它取决于纺织品的不同结构参数和个体特性。相关织物特性的测量需要非常特殊的实验室设备，例如 M 290 水分管理测试仪 (SDL ATLAS) 或类似设备。因此，显然非常需要根据负责服装舒适度的各个属性来预测整体水分管理能力 (OMMC)，并根据不同标准进行测试，而不是使用 M 290 进行 OMMC 特定计算测试员。因此，在本研究中，使用 MATLAB 软件进行线性回归分析，以预测使用四种纤维百分比编织两种模式（即 1 × 1 罗纹和半米兰罗纹）的棉涤织物的 OMMC。以水蒸气渗透率、水蒸气阻力、吸水能力、吸水时间和透气度作为线性回归分析的输入变量来预测织物的OMMC。进行的分析表明，OMMC 直接取决于相对水蒸气渗透率和透气率，并且本研究中提出的线性回归方程可以预测纺织品对于特定服装的水分管理行为的适用性。