Accurate assessment of sleep-wake patterns is important for sleep researchers and clinicians. Actigraphs are low-cost, non-intrusive, wrist-worn activity detectors used to estimate sleep-wake patterns in a natural environment for several nights. Although actigraphy shows good sensitivity (sleep detection), it has consistently demonstrated poor specificity (wakefulness detection while lying in bed relatively motionless). Because insomnia is characterized by wakefulness in bed, actigraphy may not be a valid objective measure of wakefulness for this group. It is possible that refinement of actigraphy software settings for sleep/wake algorithms might improve specificity. The current studies investigated this hypothesis by comparing wake parameters from 48 combinations of actigraphy settings to determine which sleep/wake algorithms best inform insomnia diagnosis and treatment. In the first study, none of the 48 actigraphy setting combinations consistently discriminated between adults with insomnia (n = 69) and non-insomnia (n = 80) on all three wake parameters, and no setting clearly discriminated between groups for the composite variable, total wake time. Similarly, in the second study, no setting combinations consistently discriminated between adults treated for insomnia (n = 18) and controls with untreated insomnia (n = 26) on all three wake parameters. Although two setting combinations discriminated between groups for the composite variable, total wake time, the values were extreme which raises validity concerns. Therefore, no actigraphy setting recommendations can be made based on the current findings. This research offers insights about the effects of actigraphy software settings on actigraphy specificity as it pertains to the diagnosis and treatment of insomnia.