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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Validation of Photoplethysmography-Based Sleep Staging Compared With Polysomnography in Healthy Middle-Aged Adults
Pedro Fonseca, Tim Weysen, Maaike Goelema, et al.
SLEEP (2017) Vol. 40, Iss. 7
Open Access | Times Cited: 128

Showing 1-25 of 128 citing articles:

Wearable Sleep Technology in Clinical and Research Settings
Massimiliano de Zambotti, Nicola Cellini, Aimée Goldstone, et al.
Medicine & Science in Sports & Exercise (2019) Vol. 51, Iss. 7, pp. 1538-1557
Open Access | Times Cited: 369
Sleep stage prediction with raw acceleration and photoplethysmography heart rate data derived from a consumer wearable device
Olivia Walch, Yitong Huang, Daniel B. Forger, et al.
SLEEP (2019) Vol. 42, Iss. 12
Open Access | Times Cited: 186
The Promise of Sleep: A Multi-Sensor Approach for Accurate Sleep Stage Detection Using the Oura Ring
Marco Altini, Hannu Kinnunen
Sensors (2021) Vol. 21, Iss. 13, pp. 4302-4302
Open Access | Times Cited: 127
A Systematic Review of Sensing Technologies for Wearable Sleep Staging
Syed Anas Imtiaz
Sensors (2021) Vol. 21, Iss. 5, pp. 1562-1562
Open Access | Times Cited: 125
State of the science and recommendations for using wearable technology in sleep and circadian research
Massimiliano de Zambotti, Cathy Goldstein, Jesse D. Cook, et al.
SLEEP (2023) Vol. 47, Iss. 4
Closed Access | Times Cited: 51
The convergence of traditional and digital biomarkers through AI-assisted biosensing: A new era in translational diagnostics?
Sagar S. Arya, Sofia B. Dias, Herbert F. Jelinek, et al.
Biosensors and Bioelectronics (2023) Vol. 235, pp. 115387-115387
Open Access | Times Cited: 47
The 2023 wearable photoplethysmography roadmap
Peter Charlton, John Allen, Raquel Bailón, et al.
Physiological Measurement (2023) Vol. 44, Iss. 11, pp. 111001-111001
Open Access | Times Cited: 42
Face2PPG: An Unsupervised Pipeline for Blood Volume Pulse Extraction From Faces
Constantino Álvarez Casado, Miguel Bordallo López
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 11, pp. 5530-5541
Open Access | Times Cited: 42
Validity and reliability of the Oura Ring Generation 3 (Gen3) with Oura sleep staging algorithm 2.0 (OSSA 2.0) when compared to multi-night ambulatory polysomnography: A validation study of 96 participants and 421,045 epochs
Thomas Svensson, Kaushalya Madhawa, Hoang Nt, et al.
Sleep Medicine (2024) Vol. 115, pp. 251-263
Open Access | Times Cited: 16
Agreement between actigraphic and polysomnographic measures of sleep in adults with and without chronic conditions: A systematic review and meta-analysis
Samantha Conley, Andrea Knies, Janene Batten, et al.
Sleep Medicine Reviews (2019) Vol. 46, pp. 151-160
Open Access | Times Cited: 118
A systematic review of the accuracy of sleep wearable devices for estimating sleep onset
Hannah Scott, Leon Lack, Nicole Lovato
Sleep Medicine Reviews (2019) Vol. 49, pp. 101227-101227
Closed Access | Times Cited: 113
Limiting racial disparities and bias for wearable devices in health science research
Peter J. Colvonen, Pamela N. DeYoung, Naa-Oye A Bosompra, et al.
SLEEP (2020) Vol. 43, Iss. 10
Open Access | Times Cited: 112
Pulse rate variability in cardiovascular health: a review on its applications and relationship with heart rate variability
Elisa Mejía‐Mejía, James M. May, Róbinson Torres, et al.
Physiological Measurement (2020) Vol. 41, Iss. 7, pp. 07TR01-07TR01
Open Access | Times Cited: 110
Validation of Fitbit Charge 2 and Fitbit Alta HR Against Polysomnography for Assessing Sleep in Adults With Obstructive Sleep Apnea
Fernando Moreno-Pino, Alejandro Porras‐Segovia, Pilar López-Esteban, et al.
Journal of Clinical Sleep Medicine (2019) Vol. 15, Iss. 11, pp. 1645-1653
Open Access | Times Cited: 94
Deep learning enables sleep staging from photoplethysmogram for patients with suspected sleep apnea
Henri Korkalainen, Juhani Aakko, Brett Duce, et al.
SLEEP (2020) Vol. 43, Iss. 11
Open Access | Times Cited: 93
Wearables in cardiology: Here to stay
Lilas Dagher, Hanyuan Shi, Yan Zhao, et al.
Heart Rhythm (2020) Vol. 17, Iss. 5, pp. 889-895
Closed Access | Times Cited: 92
Artificial intelligence in sleep medicine: background and implications for clinicians
Cathy Goldstein, Richard B. Berry, David T. Kent, et al.
Journal of Clinical Sleep Medicine (2020) Vol. 16, Iss. 4, pp. 609-618
Open Access | Times Cited: 91
A deep transfer learning approach for wearable sleep stage classification with photoplethysmography
Mustafa Radha, Pedro Fonseca, Arnaud Moreau, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 85
A Review of Approaches for Sleep Quality Analysis
Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado‐Dias, et al.
IEEE Access (2019) Vol. 7, pp. 24527-24546
Open Access | Times Cited: 84
Automating sleep stage classification using wireless, wearable sensors
Alexander J. Boe, Lori L. McGee Koch, Megan K. O’Brien, et al.
npj Digital Medicine (2019) Vol. 2, Iss. 1
Open Access | Times Cited: 84
Sensors Capabilities, Performance, and Use of Consumer Sleep Technology
Massimiliano de Zambotti, Nicola Cellini, Luca Menghini, et al.
Sleep Medicine Clinics (2020) Vol. 15, Iss. 1, pp. 1-30
Open Access | Times Cited: 76
Wearable monitoring of sleep-disordered breathing: estimation of the apnea–hypopnea index using wrist-worn reflective photoplethysmography
Gabriele B. Papini, Pedro Fonseca, Merel M. van Gilst, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 70
Past, Present, and Future of Multisensory Wearable Technology to Monitor Sleep and Circadian Rhythms
Matthew R. Lujan, Ignacio Perez-Pozuelo, Michael A. Grandner
Frontiers in Digital Health (2021) Vol. 3
Open Access | Times Cited: 66
At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch
Nathan Zavanelli, Hojoong Kim, Jong-Su Kim, et al.
Science Advances (2021) Vol. 7, Iss. 52
Open Access | Times Cited: 57
Technologies for sleep monitoring at home: wearables and nearables
Heenam Yoon, Sang Ho Choi
Biomedical Engineering Letters (2023) Vol. 13, Iss. 3, pp. 313-327
Closed Access | Times Cited: 24
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