Fig. 4 | Scientific Reports

Fig. 4

From: Automatic detection of persistent physiological changes after COVID infection via wearable devices with potential for long COVID management

Fig. 4

Long term individualized-baseline z-scored trend of two sample physiological parameters from 60 days before the testing day to 200 days after the testing day. Panels (a) and (b) show the normalized trajectories for users with detected persistent physiological change (orange), other COVID positive cases (red), and COVID negative individuals (blue). The vertical dashed red line indicates the testing day. Panels (c), (d), and (e), display the number of unique users contributing data each day: (c) COVID negative users, (d) COVID positive users, and (e) COVID positive users with detected persistent physiological change. There are N = 2,513 COVID negative users and N = 663 COVID positive users, within which N = 33 users with detected persistent physiological change are identified. The shaded areas in (a) and (b) reflect the standard deviation across individuals; note that the widening of the shaded region over time, particularly for users with detected persistent physiological change, reflects increased variability due to participant attrition.

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