Studying the Effect of Long COVID-19 Infection on Sleep Quality Using Wearable Health Devices: Observational Study

Abstract

Background: Patients with COVID-19 have increased sleep disturbances and decreased sleep quality during and after the infection. The current published literature focuses mainly on qualitative analyses based on surveys and subjective measurements rather than quantitative data.

Objective: In this paper, we assessed the long-term effects of COVID-19 through sleep patterns from continuous signals collected via wearable wristbands.

Methods: Patients with a history of COVID-19 were compared to a control arm of individuals who never had COVID-19. Baseline demographics were collected for each subject. Linear correlations among the mean duration of each sleep phase and the mean daily biometrics were performed. The average duration for each subject's total sleep time and sleep phases per night was calculated and compared between the 2 groups.

Results: This study includes 122 patients with COVID-19 and 588 controls (N=710). Total sleep time was positively correlated with respiratory rate (RR) and oxygen saturation (SpO₂). Increased awake sleep phase was correlated with increased heart rate, decreased RR, heart rate variability (HRV), and SpO₂. Increased light sleep time was correlated with increased RR and SpO₂ in the group with COVID-19. Deep sleep duration was correlated with decreased heart rate as well as increased RR and SpO₂. When comparing different sleep phases, patients with long COVID-19 had decreased light sleep (244, SD 67 vs 258, SD 67; P=.003) and decreased deep sleep time (123, SD 66 vs 128, SD 58; P=.02).

Conclusions: Regardless of the demographic background and symptom levels, patients with a history of COVID-19 infection demonstrated altered sleep architecture when compared to matched controls. The sleep of patients with COVID-19 was characterized by decreased total sleep and deep sleep.

Keywords: COVID-19; biometric; demographic; digital health; health data; health monitoring; long COVID-19; patient data; sleep; sleep architecture; wearable device; wearables.