Pulmonary electrical impedance tomography (EIT) is a functional imaging technique which allows real-time monitoring of ventilation distribution. Ventilation heterogeneity (VH) is a characteristic feature of chronic obstructive pulmonary disease (COPD), and has previously been quantified using amplitude-based features derived from tidal variations in the amplitude of the EIT signal. However, VH may be better described by time-based metrics, the measurement of which is made possible by the high temporal resolution of EIT. We aimed to 1) quantify VH using novel time-based EIT metrics, and 2) determine the physiological relevance of these metrics by exploring their relationships with complex lung mechanics measured by the forced oscillation technique (FOT).We performed FOT, spirometry, and tidal-breathing EIT measurements in 11 healthy and 9 COPD volunteers. Through offline signal processing, we derived 3 features from the impedance-time (Z-t) curve for each image pixel: (1) t, mean expiratory time; (2) PHASE, mean time difference between pixel and global Z-t curves; and (3) AMP, mean amplitude of Z-t curve tidal variation. Distribution was quantified by the coefficient of variation (CV) and the heterogeneity index (HI).Both CV and HI of the tand PHASE features were significantly increased in COPD compared to controls, and both related to spirometry and FOT resistance and reactance measurements. In contrast, distribution of the AMP feature showed no relationships with lung mechanics.These novel time-based EIT metrics of VH reflect complex lung mechanics in COPD, and have the potential to allow real-time visualization of pulmonary physiology in spontaneously-breathing subjects.