Most illnesses are best managed by taking prompt actions (e.g., making adjustments to medications or changing the pacing of a heart) in response to changes in the state of the patient. What is needed is a closed-loop approach in which 1) the state of the patient is monitored continually, 2) The data is automatically analyzed to detect developing problems, and 3) action is taken. The action can be either a direct intervention or alerting potential caregivers about the change in state. Over the last several years we have been developing tools and techniques that apply this paradigm to help patients who suffer from epilepsy. Epilepsy, a serious disorder of the central nervous system that predisposes those affected to recurrent seizures, is the third most common neurological disorder in the United States, behind Alzheimer’s disease and stroke. Its incidence is roughly equal to the sum of the incidence of cerebral palsy, multiple sclerosis and Parkinson’s disease. Approximately 1% of the world’s population exhibits symptoms of epilepsy. The mortality rate among people with epilepsy is two to three times higher than the general population and the risk of sudden death is 24 times greater. We are developing a wearable system that will automatically couple the real-time detection of the electrographic onset of a seizure in the EEG of ambulatory patients to either the initiation of a neural stimulator, an audible warning, or notification of a caregiver by cell phone. This talk will present our algorithmic work on building patient specific seizure detectors, an evaluation of our detectors against other state-of-the-art techniques, and our current work on translating these resu;ts into clinical applications.
From January of 1999 through August of 2004, Professor Guttag served as Head of MIT’s Electrical Engineering and Computer Science Department. He served as Associate Department Head from Computer Science from 1993 to 1998. EECS, with approximately 1800 students and 125 faculty members, is the largest department at MIT. Professor Guttag currently co-heads the Computer Science and Artificial Intelligence Laboratory’s Networks and Mobile Systems Group. This group studies issues related to computer networks, applications of networked and mobile systems, and advanced software-based medical instrumentation and decision systems.
Professor Guttag has also done research, published, and lectured in the areas of software engineering, mechanical theorem proving, hardware verification, compilation, and software radios. In addition to his academic activities, Professor Guttag has had long-term consulting relationships with a number of industrial research and advanced development organizations. He has also worked for many years as a consultant specializing in the analysis of information systems related business opportunities and risks. He currently serves on the technical advisory boards of Vanu, Inc. and IMLogic, on the Board of Directors of Empirix, Inc. and Avid Technology, Inc., and on the Board of Trustees of the MGH Institute of Health Professions. He is also a member of the American Academy of Arts and Sciences.
Prof. Guttag earned an A.B. in English and an M.S. in Applied Mathematics from Brown University, and a Ph.D. in Computer Science from the University of Toronto..