---
title: "Temporal Event Recognition: An Application to Left Ventricular Performance"
authors:
  - "John K. Tsotsos"
doi: ""
url: "https://ijcai.org/proceedings/1981/171"
pdf: "https://ijcai.org/proceedings/1981/0171.pdf"
venue: "Proceedings of the Seventh International Joint Conference on Artificial Intelligence"
year: 1981
pages: "900-906"
track: "Medical Application"
keywords:
---

# Temporal Event Recognition: An Application to Left Ventricular Performance

John K. Tsotsos

*Proceedings of the Seventh International Joint Conference on Artificial Intelligence*, pages 900-906.

## Abstract

The problem of recognition of time-varying events, particularly molion concepts, is discussed and a framework for the abstraction of such concepts is briefly presented. We have de~igned 11nd implemented a knowledge-based expert system for motion understanding that incorporates several novel features. A frame-based representation , which includes exception handling via similarity links and the organizational primitives IS-A and PART-OF is used to construct a knowledge base of temporal concepts. This knowledge base drives the recognition process that integrates the paradigms of hypothesize-andtP.qt l'lnrl r.nmpP.t.itinn i'lnd en-operation among conceptually adjacent hypotheses . The recognition stra · tegy also includes a hypothesis rating scheme that. is amenable to empirical performance analysis . This framework has been applied to the problem of human left ventricular performance evaluation from image sequences, and thus the knowledge base also contains much uf lht: cUl'rent understanding of left ventricular dynamics . This paper describes some aspects of this application in detail and presents a complet~> analy~iof a typical image sequence, emphasizing comparisons between human and computer analysis . Additional justification of the adequacy of the framework has been obtained using empirical studies of the hypothesis rating scheme.