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Sleep Monitoring in Adults Using Wearables and Unobtrusive Technology

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Wearable/Personal Monitoring Devices Present to Future

Abstract

Sleep is a complex physiological process that plays a fundamental role in maintaining homeostasis and overall health. It has an internal structure characterized by sleep stages, which is often affected by either the high demands of the current 24-h society or by different sleep disorders such as sleep apnea. These disturbances to the regular sleep structure have been strongly associated with reductions in cognitive and behavioral performance, attention deficit, depression, nocturia, memory loss, snoring, and cardiovascular diseases. Therefore, it is crucial to identify sleep problems in an early stage before the overall health is compromised in an irreversible way. Currently, sleep disorders are diagnosed using polysomnography (PSG), which is the gold-standard sleep test usually recorded in a sleep laboratory. This test is often associated with elevated costs and reduced comfort. With this in mind, many studies have focused on the development of wearables and unobtrusive technologies that can be used at home and that can monitor sleep during more than one single night. This chapter discusses unobtrusive state-of-the-art sensors and algorithms for sleep monitoring in adults, with a special focus on heart rate, respiration, and blood oxygenation monitoring.

M. Deviaene–D. Huysmans—These authors have equal contributions to the work.

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Notes

  1. 1.

    The EEG captures the electrical activity from the brain, commonly obtained from the scalp using surface electrodes.

  2. 2.

    The EOG records the electrical signal caused due to the opposite polarity between the front and back of the eye, which acts as a dipole.

  3. 3.

    The EMG records the electrical activity of the muscles.

  4. 4.

    The ECG records the electrical activity of the heart.

  5. 5.

    Tidal volume corresponds to the volume of air inspired/expired with each breathing cycle.

  6. 6.

    Time differences between consecutive R-peaks in the ECG.

  7. 7.

    During obstructive apneas, the respiratory effort signals from the thoracic and abdominal belts are often out of phase, and this phenomenon is called the thoracoabdominal paradox.

  8. 8.

    PALM is an acronym for the measured parameters for each of the four studied traits: Pcrit, arousal threshold, loop gain, and muscle responsiveness.

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Acknowledgements

This research received funding from Agentschap Innoveren en Ondernemen (VLAIO) 150466 OSA+, imec sbo funds Wearablehealth, and the Flemish Government (AI Research Program). SVH, CV, DH, and MD are affiliated to Leuven.AI - KU Leuven institute for AI, B-3000, Leuven, Belgium. KU Leuven Stadius acknowledges the financial support of imec.

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  1. KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, Leuven, Belgium

    Margot Deviaene, Dorien Huysmans, Sabine Van Huffel & Carolina Varon

  2. IMEC-Leuven, Circuits and Systems for Health, Leuven, Belgium

    Ivan D. Castro

  3. UZ Leuven, Department of Pneumology, Leuven University Centre for Sleep and Wake Disorders, Leuven, Belgium

    Pascal Borzée, Dries Testelmans & Bertien Buyse

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    Gaetano D. Gargiulo

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    Ganesh R. Naik

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Deviaene, M. et al. (2022). Sleep Monitoring in Adults Using Wearables and Unobtrusive Technology. In: Gargiulo, G.D., Naik, G.R. (eds) Wearable/Personal Monitoring Devices Present to Future. Springer, Singapore. https://doi.org/10.1007/978-981-16-5324-7_8

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