Sleep insights from the finger tip: How photoplethysmography can help quantify sleep
Shuli Eyal,Anda Baharav +1 more
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TLDR
This study aimed to validate a new automated sleep analysis which is simply based on the inter-beat-interval series obtained from PPG, and that uses features of heart rate variability, and was tested against gold standard scoring of whole night state-of-the-art sleep studies.Abstract:
Sleep is essential for a healthy and productive life, yet its importance is largely overlooked, allowing populations to sleep less and to develop sleep disturbances. This trend results into an epidemic of poor quality and insufficient sleep that is turn jeopardizes health, performance, mood, memory, social relationships and productivity. A first step to overcome this epidemic relies on uncovering it at the individual and societal levels. The availability of different wearable devices that can track physiological signals represents a great opportunity to define and quantify the problem. Many such devices incorporate a photoplethysmography (PPG) sensor. This triggers interest in studies aiming to get insight into human sleep structure based on information obtained from PPG sensors. This study aimed to validate a new automated sleep analysis which is simply based on the inter-beat-interval series obtained from PPG, and that uses features of heart rate variability. The candidate algorithm was tested against gold standard scoring of whole night state-of-the-art sleep studies. The PPG-based sleep scoring performs very well in differentiating sleep stages, however, the sleep/wake separation is not sufficient and requires improvement. This last task is facilitated by the fact that the majority of devices with PPG capabilities, are equipped with accelerometers providing additional information for better separation. Combining accelerometers and PPG signals from wearable devices in a sleep analyser is likely to provide a reliable and accurate automated detection of sleep and wakefulness, including sleep macro- and micro-architecture.read more
Citations
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Journal ArticleDOI
Transfer learning from ECG to PPG for improved sleep staging from wrist-worn wearables.
Qiao Li,Qichen Li,Ayse S. Cakmak,Giulia Da Poian,Donald L. Bliwise,Viola Vaccarino,Amit J. Shah,Gari D. Clifford +7 more
TL;DR: In this paper, a sleep staging method from wrist-worn accelerometry and the photoplethysmogram (PPG) was developed by leveraging transfer learning from a large electrocardiogram (ECG) database.
Journal ArticleDOI
An unbiased, efficient sleep–wake detection algorithm for a population with sleep disorders: change point decoder
Ayse S. Cakmak,Giulia Da Poian,Adam Willats,Ammer Haffar,Rami Abdulbaki,Yi-An Ko,Amit J. Shah,Viola Vaccarino,Donald L. Bliwise,Christopher J. Rozell,Gari D. Clifford,Gari D. Clifford +11 more
TL;DR: A novel and unbiased data-driven method for detection of sleep-wake and compared its performance to the well-established Oakley algorithm relative to polysomnography in elderly men with disordered sleep achieved balanced performance and higher AUC, despite underestimating sleep/wake transitions.
Journal ArticleDOI
Photoplethysmographic-based automated sleep-wake classification using a support vector machine.
TL;DR: This work aims to design an automated approach for sleep-wake classification using wearable fingertip photoplethysmographic (PPG) signal, which would help in continuous, non-invasive monitoring of sleep quality.
Dissertation
Photoplethysmogram Derived Cardio-Respiratory Biomarkers for Sleep Monitoring
TL;DR: This thesis has implemented algorithms that are capable of extracting HR and RR from the short length photoplethysmogram (PPG) signal and investigated the statistical and surrogate cardio-respiratory biomarkers to classify sleep stages using supervised machine learning techniques.
References
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Journal ArticleDOI
A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects.
TL;DR: Techniques of recording, scoring, and doubtful records are carefully considered, and Recommendations for abbreviations, types of pictorial representation, order of polygraphic tracings are suggested.
Journal ArticleDOI
Behavioral and physiological consequences of sleep restriction
Siobhan Banks,David F. Dinges +1 more
TL;DR: Recent experiments reveal that following days of chronic restriction of sleep duration below 7 hours per night, significant daytime cognitive dysfunction accumulates to levels comparable to that found after severe acute total sleep deprivation.
Journal ArticleDOI
Comparison of detrended fluctuation analysis and spectral analysis for heart rate variability in sleep and sleep apnea
TL;DR: Investigation of the effect of sleep stages and sleep apnea on autonomic activity by analyzing heart rate variability concludes that changes in HRV are better quantified by scaling analysis than by spectral analysis.
Journal ArticleDOI
Photoplethysmography pulse rate variability as a surrogate measurement of heart rate variability during non-stationary conditions
Eduardo Gil,Michele Orini,Michele Orini,Raquel Bailon,Jose Maria Vergara,Luca Mainardi,Pablo Laguna +6 more
TL;DR: Although some differences in the time-varying spectral indices extracted from HRV and PRV exist, mainly in the HF band associated with respiration, PRV could be used as a surrogate of HRV during non-stationary conditions, at least during the tilt table test.
Peer Review
Validation of a
TL;DR: The validation process attests to the scientific rigor with which the scenario and ckecklist were elaborated and can, therefore, be used safely in undergraduate nursing education.