In biomedical applications, the similarity between a signal measured from an injured subject and a reference signal measured from a normal subject can be used to quantify the injury severity. This paper proposes a generalization of the adaptive signed correlation index (ASCI) to account for specific signal features of interest and extend the trichotomization of conventional ASCI to an arbitrary number of levels. In the context of spinal cord injury assessment, a computational example is presented to illustrate the enhanced resolution of the proposed measure and its ability to offer a more refined measure of the level of injury.
@article{arxiv.1610.06640,
title = {A Generalized Correlation Index for Quantifying Signal Morphological Similarity},
author = {A. Olenko and K. T. Wong and H. Mir and H. Al-Nashash},
journal= {arXiv preprint arXiv:1610.06640},
year = {2016}
}