The use of two-channel electro-oculography in automatic detection of unintentional sleep onset.

@article{citeulike:2948806, abstract = {An automatic method was developed for detecting unintentional sleep onset. The automatic method is based on a two-channel electro-oculography (EOG) with left mastoid (M1) as reference. An automatic estimation of slow eye movements (SEM) was developed and used as the main criterion to separate sleep stage 1 (S1) from wakefulness. Additionally synchronous electroencephalographic (EEG) activity of sleep stages 1 and 2 was detected by calculating cross-correlation and amplitude difference in the 1.5-6 Hz theta band between the two EOG channels. Alpha power 8-12 Hz and beta power 18-30 Hz were used to determine wakefulness. Unintentional sleep onsets were studied using data from four separate maintenance of wakefulness test (MWT) sessions of 228 subjects. The automatic scoring of 30s sleep onset epochs using only EOG was compared to standard visual sleep stage scoring. The optimal detection thresholds were derived using data from 114 subjects and then applied to the data from different 114 subjects. Cohen's Kappa between the visual and the new automatic scoring system in separating wakefulness and sleep was substantial (0.67) with epoch by epoch agreement of 98\%. The sleep epoch detection sensitivity was 70\% and specificity 99\%. The results are provided with a 1s delay for each 30s epoch. The developed method has to be tested in field applications. The advantage of the automatic method is that it could be applied during online recordings using only four disposable self-adhesive self-applicable electrodes.}, address = {Brain Work Research Center, Finnish Institute of Occupational Health, Helsinki, Finland. jussi.virkkala@ttl.fi}, author = {Virkkala, J. and Hasan, J. and V\"{a}rri, A. and Himanen, S. L. and H\"{a}rm\"{a}, M. }, citeulike-article-id = {2948806}, doi = {http://dx.doi.org/10.1016/j.jneumeth.2007.02.001}, issn = {0165-0270}, journal = {Journal of neuroscience methods}, keywords = {eog, sleep}, month = {June}, number = {1}, pages = {137--144}, posted-at = {2008-07-01 17:13:42}, priority = {2}, title = {The use of two-channel electro-oculography in automatic detection of unintentional sleep onset.}, url = {http://dx.doi.org/10.1016/j.jneumeth.2007.02.001}, volume = {163}, year = {2007} }

TY - JOUR ID - citeulike:2948806 L3 - citeulike-article-id:2948806 TI - The use of two-channel electro-oculography in automatic detection of unintentional sleep onset. JF - Journal of neuroscience methods VL - 163 IS - 1 SP - 137 EP - 144 AD - Brain Work Research Center, Finnish Institute of Occupational Health, Helsinki, Finland. jussi.virkkala@ttl.fi SN - 0165-0270 N2 - An automatic method was developed for detecting unintentional sleep onset. The automatic method is based on a two-channel electro-oculography (EOG) with left mastoid (M1) as reference. An automatic estimation of slow eye movements (SEM) was developed and used as the main criterion to separate sleep stage 1 (S1) from wakefulness. Additionally synchronous electroencephalographic (EEG) activity of sleep stages 1 and 2 was detected by calculating cross-correlation and amplitude difference in the 1.5-6 Hz theta band between the two EOG channels. Alpha power 8-12 Hz and beta power 18-30 Hz were used to determine wakefulness. Unintentional sleep onsets were studied using data from four separate maintenance of wakefulness test (MWT) sessions of 228 subjects. The automatic scoring of 30s sleep onset epochs using only EOG was compared to standard visual sleep stage scoring. The optimal detection thresholds were derived using data from 114 subjects and then applied to the data from different 114 subjects. Cohen's Kappa between the visual and the new automatic scoring system in separating wakefulness and sleep was substantial (0.67) with epoch by epoch agreement of 98%. The sleep epoch detection sensitivity was 70% and specificity 99%. The results are provided with a 1s delay for each 30s epoch. The developed method has to be tested in field applications. The advantage of the automatic method is that it could be applied during online recordings using only four disposable self-adhesive self-applicable electrodes. KW - eog KW - sleep AU - Virkkala, J AU - Hasan, J AU - Värri, A AU - Himanen, SL AU - Härmä, M PY - 2007/06/15/ UR - http://dx.doi.org/10.1016/j.jneumeth.2007.02.001 ER -