Deep Neural Networks for Automatic Classification of Anesthetic-Induced Unconsciousness

rid. The apparent equivalency of thesetime chunksmask the affective experiences and emotional intensities of lived temporality

. Notably, this lack of predictability had large social, rather than individual, implications—a finding that strongly echoes prior CSCW research [1, 4, 13, 15, 20, 22, 34, 35, 36, 38, 45, 46, 59]

In alignmentwith Reddy and Dourish’s concept of temporal trajectory [45], spectral time suggests that temporal experience is more than a grid of accountable blocks; multiple temporalities create flowsthat often defy both logical renderingand seamless manipulation

Our data reveal that not every temporal experience is easily articulated, planned for, measurable orable to be renderedinto a schedule.We call these temporal experiences spectral time,to capture howtime trailsor ghostsin ways that cannot always be expected, planned, or accounted for.Spectral time referencesmoments that do not lend themselves to scheduling(i.e. chunking), either because the act seems toomundane to justify articulation (i.e., getting dressed), because it is difficult to assess (i.e., travel time) or simply because it cannot be anticipated (i.e., creative phases).