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University of Groningen Ambulatory assessment of human circadian phase and related sleep disorders from heart rate variability and other non-invasive physiological measurements Gil Ponce, Enrique

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University of Groningen

Ambulatory assessment of human circadian phase and related sleep disorders from heart

rate variability and other non-invasive physiological measurements

Gil Ponce, Enrique

IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.

Document Version

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Publication date: 2017

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):

Gil Ponce, E. (2017). Ambulatory assessment of human circadian phase and related sleep disorders from heart rate variability and other non-invasive physiological measurements. University of Groningen.

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Stellingen

Behorende bij het proefschrift:

Ambulatory assessment of human circadian phase

and related sleep disorders from heart rate variability

and other non-invasive physiological measurements

1. Heart rate and heart rate variability contain valuable timing information which can be used to estimate circadian phase in humans. 2. Beyond overnight sleep lab recordings, 24-hour recordings of circadian signals, such as heart rate variability, can support the diagnosing of circadian sleep disorders.

3. The shiny exterior of modern wrist-worn sensors allude to a high level of trustworthiness and quality of the data collected. However, in many cases, the scientific/validity of the on-board algorithms still require substantial improvement.

4. The pervasiveness of heart rate sensors and accelerometers is the beginning of the adoption of continuous health monitoring in the consumer market.

5. Sleep laboratory procedures can lead to biased results due to the scheduling of the sleep timing of participants based on staff working hours. 6. Mathematical models require that structure and parameter values are transparent, which makes them indispensable for understanding complex processes.

Enrique A. Gil Groningen, 28 april 2017

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