Combining behavioral and physiologic measures depicts gradual process of falling asleep, may help diagnose sleep disorders
Massachusetts General Hospital (MGH) investigators have developed a system to accurately track the dynamic process of falling asleep, something has not been possible with existing techniques. In their report in a recent issue of the open-access journal PLOS Computational Biology, the research team describes how combining key physiologic measurements with a behavioral task that does not interfere with sleep onset gives a better picture of the gradual process of falling asleep. In addition to being a powerful tool for future research, the system could provide valuable insight into diagnosing and understanding sleep disorders.
Sleep study participants are asked to squeeze a small ball with their hand in time with their breathing, and the force and timing of their motions are measured by the glove and by electrodes on a forearm muscle. By combining EEG brainwave data with information from the way squeezes decrease in frequency and strength as a participant falls asleep, investigators can now track the dynamic changes in brain and body during the sleep onset process.
Credit: Michael Prerau, PhD, MGH Department of Anesthesia, Critical Care and Pain Management
Prerau is an instructor of Anæsthesia, and Purdon is an assistant professor of Anæsthesia at Harvard Medical School. Additional co-authors are Katie Hartnack, Gabriel Obregon-Henao and Aaron Sampson, MGH Anesthesia; Margaret Merlino, Karen Gannon and Matt Bianchi, MD, PhD, MGH Department of Neurology; and Jeffrey M. Ellenbogen, MD, Johns Hopkins University. The study was supported by National Institutes of Health New Innovator Award DP2-OD006454.
Tracking the Sleep Onset Process: An Empirical Model of Behavioral and Physiological Dynamics. Published: October 02, 2014 DOI: 10.1371/journal.pcbi.1003866