assessment of sleep physiology, but the methodology presently used is costly, intrusive
to participants, and laborious in application. There is a recognized need to develop more
easily applicable yet reliable EEG systems that allow unobtrusive long-term recording
of sleep-wake EEG ideally away from the laboratory setting. cEEGrid is a recently
developed flex-printed around-the-ear electrode array, which holds great potential for
sleep-wake monitoring research. It is comfortable to wear, simple to apply, and minimally
intrusive during sleep. Moreover, it can be combined with a smartphone-controlled
miniaturized amplifier and is fully portable. Evaluation of cEEGrid as a motion-tolerant
device is ongoing, but initial findings clearly indicate that it is very well suited for cognitive
research. The present study aimed to explore the suitability of cEEGrid for sleep
research, by testing whether cEEGrid data affords the signal quality and characteristics
necessary for sleep stage scoring. In an accredited sleep laboratory, sleep data from
cEEGrid and a standard PSG system were acquired simultaneously. Twenty participants
were recorded for one extended nocturnal sleep opportunity. Fifteen data sets were
scored manually. Sleep parameters relating to sleep maintenance and sleep architecture
were then extracted and statistically assessed for signal quality and concordance. The
findings suggest that the cEEGrid system is a viable and robust recording tool to capture
sleep and wake EEG. Further research is needed to fully determine the suitability of
cEEGrid for basic and applied research as well as sleep medicine.
Mikkelsen K.B, Ebajemito, J.K., Bonmati-Carrion, M.A., Santhi, N., Revell, V.L., Atzori, G., della Monica, C., Debener, S., Dijk, D-J., Sterr, A., de Vos, M. (2018). Machine learning derived sleep-wake staging from around-the-ear EEG outperforms manual scoring and actigraphy. Journal of Sleep Research. Nov 13:e12786. DOI: 10.1111/jsr.12786.
Sterr A., Ebajemito, J.K., Mikkelsen K.B, Bonmati-Carrion, M.A., Santhi, N., Atzori, G., della Monica, C., Grainger, L., Revell, V.L., Debener, S., Dijk, D-J., de Vos, M. Sleep EEG derived from behind-the-ear electrodes (cEEGrid) compared to standard polysomnography: A proof of concept study. Frontiers Human Neurosci. 2018 Nov 26;12:452. DOI: 10.3389/fnhum.2018.00452.
della Monica, C., Dijk, D-J. (2018). What makes a good night’s sleep? The external and internal factors that influence a good night’s sleep. Physiology News. Winter 2018, Issue 113, p36-39.
della Monica, C., Johnsen, S., Atzori, G., Groeger, J. A., Dijk, D-J. (2018). Rapid-Eye-Movement Sleep, Sleep Continuity and Slow Wave Sleep as Predictors of Cognition, Mood and Subjective Sleep Quality in Healthy Men and Women, Aged 20-84 Years. Frontiers in Psychiatry. Jun 22;9:255. DOI: 10.3389/fpsyt.2018.00255.
Cerasuolo, M., Giganti, F., Conte, F., Costanzo, L. M., della Monica, C., Arzilli, A., Marchesano, R., Perrella, A. & Ficca, G. (2016). Schooltime subjective sleepiness and performance in Italian primary school children. Chronobiology International. DOI: 10.1080/07420528.2016.1178274.
della Monica, C., Atzori, G., Dijk, D-J. (2015). Effects of lunar phase on sleep in men and women in Surrey. Journal of Sleep Research. DOI: 10.1111/jsr.12312.
Marcone, R., della Monica, C., Caputo, A. (2015). Friendship competence in kindergarten and primary school children. European Journal of Developmental Psychology. DOI:10.1080/17405629.2015.1031215.
Barbato, G., Costanzo, A., della Monica, C., D'Onofrio, P., Cerrato, F., De Padova, V. (2013) Effects of prolonged wakefulness: The role of PERIOD3 genotypes and personality traits. Psychological Reports; 113(2):540-551.
Barbato, G., della Monica, C., Costanzo, A., De Padova, V. (2012) Dopamine activation in Neuroticism as measured by spontaneous eye blink rate. Physiology and Behavior. 105:332-336.
Di Lorenzo, D., Barbato, G., Conte, F., Costanzo, A., della Monica, C., Serio, M., Ficca, G. (2011) Leptin and mood disorders. Italian Journal of Psychopathology, 17:183-192.