A custom-built single-channel in-ear electroencephalography sensor for sleep phase detection: an interdependent solution for at-home sleep studies

• Published in: Journal of sleep research 2024-10, p.e14368
• Main Authors: Borges, Daniel Filipe, Soares, Joana Isabel, Silva, Heloísa, Felgueiras, João, Batista, Carla, Ferreira, Simão, Rocha, Nuno Barbosa, Leal, Alberto
• Format: Article
• Language: English
• ISSN: 0962-1105; 1365-2869; 1365-2869
• DOI: 10.1111/jsr.14368

Sleep is vital for health. It has regenerative and protective functions. Its disruption reduces the quality of life and increases susceptibility to disease. During sleep, there is a cyclicity of distinct phases that are studied for clinical purposes using polysomnography (PSG), a costly and technically demanding method that compromises the quality of natural sleep. The search for simpler devices for recording biological signals at home addresses some of these issues. We have reworked a single-channel in-ear electroencephalography (EEG) sensor grounded to a commercially available memory foam earplug with conductive tape. A total of 14 healthy volunteers underwent a full night of simultaneous PSG, in-ear EEG and actigraphy recordings. We analysed the performance of the methods in terms of sleep metrics and staging. In another group of 14 patients evaluated for sleep-related pathologies, PSG and in-ear EEG were recorded simultaneously, the latter in two different configurations (with and without a contralateral reference on the scalp). In both groups, the in-ear EEG sensor showed a strong correlation, agreement and reliability with the 'gold standard' of PSG and thus supported accurate sleep classification, which is not feasible with actigraphy. Single-channel in-ear EEG offers compelling prospects for simplifying sleep parameterisation in both healthy individuals and clinical patients and paves the way for reliable assessments in a broader range of clinical situations, namely by integrating Level 3 polysomnography devices. In addition, addressing the recognised overestimation of the apnea-hypopnea index, due to the lack of an EEG signal, and the sparse information on sleep metrics could prove fundamental for optimised clinical decision making.