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Date
2023Type
- Conference Paper
ETH Bibliography
yes
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Abstract
Wearable electroencephalography (EEG) enables real-time interactions with the sleeping brain in real-life settings. An important parameter to monitor during these interactions are sleep arousals, i.e. temporary increases in EEG frequency, that compose sleep dynamics, but are challenging to detect without delay. We describe the development of an EEG- and accelerometer(ACC)-based sensing approach to detect arousals in real-time. We investigated the ability of these sensing modalities to timely and accurately detect arousals. When evaluated on 6 nights of mobile recordings, ACC had a median real-time delay of 2 s and was therefore better suited for an early detection of arousals than EEG (4.7 s). The detection performance was independent of sleep stages, but worked better on longer arousals. Our results demonstrate that a head-mounted ACC might be a cost-effective and easy-to-integrate solution for arousal detection where short delays are important or EEG signals are not available. Show more
Publication status
publishedExternal links
Book title
2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)Pages / Article No.
Publisher
IEEEEvent
Subject
Accelerometers; Sleep; Electroencephalography; Real-time systems; Biology; Delays; SensorsOrganisational unit
01225 - D-ITET Zentr. f. projektbasiertes Lernen / D-ITET Center for Project-Based Learning
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ETH Bibliography
yes
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