By occupying nearly a third of human lifespan, sleep constitutes the main activity of the human brain. Numerous recent theories on the function of sleep confirm its beneficial role at multiple physiological levels. Together with physical activity and nutrition, sleep is a corner stone of healthy living. However, latest trends show that our society has been progressively curtailing sleep in benefit of other activities. Numerous portable (consumer or medical type) devices have recently emerged that monitor signals that can provide information about sleep that is relevant for patients, physicians, or consumers. The types of signals acquired with portable devices and can provide sleep relevant information are of a large variety including: movement (actigraphy), muscle activity (electromyography), ocular activity (electrooculography), cardio-respiratory activity (electrocardiogram, breathing effort), electroencephalography, and photopletismography. Signal processing plays an important role in the analysis and interpretation of these signals in the context of sleep. Sleep research poses interesting signal processing challenges. In offline processing, the challenge is the inherent long duration of recordings and the relatively high sampling frequency necessary to capture important microevents to understand the restorative function of sleep. In online processing, the challenge is to locally identify sleep states (REM or NREM stages) in real-time and with short latency.
In this tutorial lecture, the main theories on the function of sleep are presented first followed by a general introduction on sleep science, the types of sleep, sleep architecture, and polysomnography. In the second part of the tutorial, the focus is on signal processing methods. The analysis of the sleep macro-structure in terms of sleep stages is first presented followed by the analysis of sleep microstructure in terms of events such as spindles and slow-waves. Sleep models (sleep dissipation, circadian model, and sleep inertia) are also presented. Finally current trends in sleep research and the relevance of signal processing are presented.
List of Speakers (tentative)
Gary Garcia-Molina, Philips Research North America and University of Wisconsin-Madison, email@example.com
Presentation Title: Signal processing methods in Sleep Research
Bio: Dr. Gary Garcia Molina has worked in neuroscience research for more than a decade. In 2004, he obtained his doctoral degree from the Swiss Federal Institute of Technology Lausanne, Switzerland (EPFL). His thesis entitled “Direct Brain- Computer Communication through Scalp Recorded EEG Signals” was nominated for the Swiss best thesis award. In January 2005, Dr. Garcia joined Philips Research Europe laboratories (Eindhoven, The Netherlands)where he led research activities in the areas of EEG based Brain-Computer Interfaces (BCI) and sleep. In 2007, Gary Garcia led several work packages in the EU project BRAIN which developed light stimulation based BCI systems. In 2012, Gary Garcia joined Philips Research North America as a clinical scientist cooperating with the University of Wisconsin-Madison (UW). Dr. Garcia has an honorary fellow appointment at the UW. He is based in Madison-Wisconsin US and works at the world renowned center of Sleep and consciousness where he conducts research in the domain of closed-loop based systems for the enhancement of sleep restoration. Gary Garcia published numerous (50+) papers, book chapters, and (20+) patent applications on signal processing, BCI, and sleep. In addition he gave several (10+) tutorial lectures on BCI and Sleep at various conference events.
Organizer I: Gary Garcia-Molina, Proposer-IEEE Member
Bio: Gary Garcia is a senior clinical scientist at Philips Research North America and has an honorary fellow appointment at the University of Wisconsin-Madison. He works at the world renowned center of Sleep and consciousness where he conducts research in the domain of closed-loop based systems for the enhancement of sleep restoration.