Using state-of-the-art sleep analysis techniques, including EEG, sophisticated wireless motion sensors, monitors, digital videography, new computer software and mathematical algorithms refined at UMaine and MIHGH, Hayes and colleagues analyze spontaneous movement during stages of infant sleep.
Hayes and her collaborators, including EMMC neonatologist Dr. Ramesh Krishnan and Ph.D. student Marcia Troese, have analyzed data on two fronts: the microstructure of sleep movements in high-risk infants, and the EEG signal in auditory neurocognitive performance.
The process of isolating and studying the comparatively weak infant brain waves presented a signal-to-noise problem. Conflicting signal noise can mask an infant’s brain activity. With a NASA grant, UMaine electrical and computer engineer Ali Abedi, engineering physics graduate student Timothy Falkner and mathematician Andre Khalil addressed the issue by developing software to better isolate brain signals and enable in-depth assessments.
In addition, to improve the fidelity of sleep movement measurement, Hayes, Abedi and postdoctoral student Muhammad Arsalan developed a sensor system that more precisely measures sleep movement and arousal.
Ph.D. biomedical sciences graduate student Jonathan Paul is credited with helping advance development of the neonatal EEG assessment method to measure an infant’s capacity to habituate to repeated stimuli, and differentiate between novel and repeated sounds. With the methods he developed, Paul found that maternal addiction patterns prenatally and sleep deprivation postnatally both impair task performance in the first month of life.
“No one has yet described spontaneous movements during sleep as having any specific function,” Hayes says. “We have established that they may be important to general cardiorespiratory integrity because high-risk infants, infants with apnea and other groups, like alcohol- and opiate-exposed groups, have increased sleep fragmentation associated with the suppression of sleep movement.
“We believe that the integrity of the (autonomic) sleep movements pattern generator is damped by sleep deprivation and may represent a primitive arousal system,” Hayes says. “Functional impairment in the vigor or intensity of movement bursts may increase SIDS risk.”
