Automatic Detection of Seizures with Applications

There are an estimated two million people with epilepsy in the United States. Many of these people do not respond to anti-epileptic drug therapy. Two devices can be developed to assist in the treatment of epilepsy. The first is a microcomputer-based system designed to process massive amounts of electroencephalogram (EEG) data collected during long-term monitoring of patients for the purpose of diagnosing seizures, assessing the effectiveness of medical therapy, or selecting patients for epilepsy surgery. Such a device would select and display important EEG events. Currently many such events are missed. A second device could be implanted and would detect seizures and initiate therapy. Both of these devices require a reliable seizure detection algorithm. A new algorithm is described. It is believed to represent an improvement over existing seizure detection algorithms because better signal features were selected and better standardization methods were used

Enskog and van der Waals play hockey

We consider the mean free path of a hockey puck in a system of other pucks on an air table, and show how the simple low-density kinetic-theory value for this mean free path can be extended to higher densities. This approach is connected both with the Enskog theory of the transport properties of dense gases and with the van der Waals theory of the equation of state of dense gases. We derive several simple approximations for the high-density mean free path, and compare the results with each other, with accurate computer-simulation results, and with experimental results obtained in the freshman physics laboratory of the University of Maryland. We present the arguments in both simplified and more elaborate forms