  Epilepsy is a chronic neurological disorder characterized by recurrent
seizures. One method for analyzing seizure activity is to compute the
correlation dimension of time-series electroencephalographic signals. The
Grasserberg and Proccacia algorithm is commonly used to compute this
correlation dimension. The algorithm uses the Heaviside function to determine
the correlation integral by counting the number of distances between vectors
(d_ij) that are greater than a threshold. However, information about the
chaotic nature of the signal is not completely retained by this function. In
this work, instead of using the Heaviside function, we calculated the
correlation integral by using an exponential function of d_ij. Greater
sensitivity to the interictal and ictal signals using this modified algorithm
was verified using three datasets. Comparing heatmaps of d_ij obtained using
the original and modified methods showed additional information that was
retained with the new algorithm.
