Validation of an automated sleep detection algorithm using data from multiple accelerometer brands-Reference-Cited by-同舟云学术

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Validation of an automated sleep detection algorithm using data from multiple accelerometer brands

Published:2022-10-31 Issue: Volume: Page:
ISSN:0962-1105
Container-title:Journal of Sleep Research
language:en
Short-container-title:Journal of Sleep Research

Author:

Plekhanova Tatiana¹²^ORCID,Rowlands Alex V.¹²,Davies Melanie J.¹²,Hall Andrew P.³⁴,Yates Tom¹²,Edwardson Charlotte L.¹²

Affiliation:

1. Diabetes Research Centre University of Leicester Leicester UK

2. NIHR Leicester Biomedical Research Centre University of Leicester Leicester UK

3. University Hospitals of Leicester NHS Trust Leicester UK

4. Department of Health Sciences University of Leicester Leicester UK

Funder

NIHR Leicester Biomedical Research Centre

Publisher

Wiley

Subject

Behavioral Neuroscience,Cognitive Neuroscience,General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jsr.13760

Reference31 articles.

1. The Current State of Physical Activity Assessment Tools

2. STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT

3. Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies

4. Automatic Sleep/Wake Identification From Wrist Activity

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3. Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality;npj Digital Medicine;2024-06-30

4. A Machine Learning Model for Predicting Sleep and Wakefulness Based on Accelerometry, Skin Temperature and Contextual Information;Nature and Science of Sleep;2024-06

5. Objectively assessed sleep quality parameters in Multiple Sclerosis at home: Association to disease, disease severity and physical activity;Sleep Medicine;2024-06

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