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Title: Methods for assessing sleep and sleepiness in healthy adults and patients with respiratory sleep disorders
Author: Alqurashi, Yousef Dhefullah
ISNI:       0000 0004 9350 8910
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2019
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Scalp electroencephalography (scalp EEG) is an accurate method for measuring sleep. However, this procedure is cumbersome, costly, and cannot be conducted over an extended period. Recently, wearable pieces of equipment to monitor sleep have been developed, one of which is the in-ear EEG. Therefore, the first two aims of this thesis were to investigate whether a novel in-ear EEG could measure sleep accurately during daytime naps, and then during overnight sleep. Clinically, excessive daytime sleepiness (EDS) is usually measured subjectively by use of the Epworth sleepiness scale (ESS). However, patients sometimes make errors and require assistance when they complete the ESS. A visual analogue scale (VAS) is a simple method that is used to measure subjective feelings such as pain, mood and breathlessness; we hypothesised that it could also measure sleepiness. Therefore, the third aim of this thesis was to investigate whether the VAS could be used as an accurate method to measure sleepiness in patients with respiratory sleep disorders, and in healthy adults. In the first study, the in-ear EEG detected sleep onset and the results offered substantial agreement with the findings of scalp EEG, in healthy adults during daytime naps. In the second study, the in-ear EEG detected slow-wave sleep at a substantial level of agreement compared with scalp EEG, in healthy adults during overnight sleep. In the third study, the VAS detected sleepiness in healthy adults and patients with respiratory sleep disorders, before and after one month of continuous positive airway pressure (CPAP) treatment. In summary, this thesis has shown that the in-ear EEG and VAS offer accurate and simple methods for the measurement of sleep and sleepiness, in both patients and healthy participants. In future, it is speculated that these two methods could be integrated into smart phones to offer simple, fast and accurate measurement of sleep and sleepiness.
Supervisor: Morrell, Mary ; Moss, James ; Polkey, Michael Iain Sponsor: Safārah (UK)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral