Sleep inertia is the condition that a person experiences upon awakening, which can vary depending on the sleep stage at the time of awakening. It is characterized by reduced alertness, drowsiness, and difficulties in cognitive and motor functions. This can pose risks in professions that require immediate high levels of attention after awakening. This study presents the Anti Sleep Inertia System (ASIS). The ASIS aims to determine the best time to wake up using an alarm clock within a specified time window. This is done using a system composed of two machine learning (ML) models that classify and predict each segment of the electroencephalogram (EEG) signal recorded during sleep. Despite the complexity of the field, the model has shown its efficacy reaching an overall accuracy of 0.73, despite its lightweight architecture

ASIS: A Smart Alarm Clock Based on Deep Learning for the Safety of Night Workers

Daniele Lozzi
Conceptualization
;
Alessandro Di Matteo;Enrico Mattei;Alessia Cipriani;Pasquale Caianiello;Filippo Mignosi;Giuseppe Placidi
2024-01-01

Abstract

Sleep inertia is the condition that a person experiences upon awakening, which can vary depending on the sleep stage at the time of awakening. It is characterized by reduced alertness, drowsiness, and difficulties in cognitive and motor functions. This can pose risks in professions that require immediate high levels of attention after awakening. This study presents the Anti Sleep Inertia System (ASIS). The ASIS aims to determine the best time to wake up using an alarm clock within a specified time window. This is done using a system composed of two machine learning (ML) models that classify and predict each segment of the electroencephalogram (EEG) signal recorded during sleep. Despite the complexity of the field, the model has shown its efficacy reaching an overall accuracy of 0.73, despite its lightweight architecture
2024
979-8-3503-7800-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/251839
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