Deciphering the Link: Correlating REM Sleep Patterns with Depressive Symptoms via Consumer Wearable Technology

Author:

Crișan Cătălina Angela1,Stretea Roland2ORCID,Bonea Maria1ORCID,Fîntînari Vadim3,Țața Ioan Marian4,Stan Alexandru5,Micluția Ioana Valentina1,Cherecheș Răzvan Mircea6,Milhem Zaki1ORCID

Affiliation:

1. Department of Neurosciences, Psychiatry and Pediatric Psychiatry, Faculty of Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania

2. Clinical Hospital of Infectious Diseases, 400348 Cluj-Napoca, Romania

3. SC STEEPSOFT AI SRL, 505600 Sacele, Romania

4. Automatics and Computers Doctoral School, Politehnica University of Bucharest, 060042 Bucharest, Romania

5. Clinical Emergency Hospital for Children, 400370 Cluj-Napoca, Romania

6. Department of Public Health, College of Political, Administrative and Communication Sciences, Babeș-Bolyai University, 400294 Cluj-Napoca, Romania

Abstract

This study investigates the correlation between REM sleep patterns, as measured by the Apple Watch, and depressive symptoms in an undiagnosed population. Employing the Apple Watch for data collection, REM sleep duration and frequency were monitored over a specified period. Concurrently, participants’ depressive symptoms were evaluated using standardized questionnaires. The analysis, primarily using Spearman’s correlation, revealed noteworthy findings. A significant correlation was observed between an increased REM sleep proportion and higher depressive symptom scores, with a correlation coefficient of 0.702, suggesting a robust relationship. These results highlight the potential of using wearable technology, such as the Apple Watch, in early detection and intervention for depressive symptoms, suggesting that alterations in REM sleep could serve as preliminary indicators of depressive tendencies. This approach offers a non-invasive and accessible means to monitor and potentially preempt the progression of depressive disorders. This study’s implications extend to the broader context of mental health, emphasizing the importance of sleep assessment in routine health evaluations, particularly for individuals exhibiting early signs of depressive symptoms.

Funder

EIT Health

Publisher

MDPI AG

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