In this work, we propose an abductive framework for biosignal interpretation, based on the concept of Temporal Abstraction Patterns. A temporal abstraction pattern defines an abstraction relation between an observation hypothesis and a set of observations constituting its evidence support. New observations are generated abductively from any subset of the evidence of a pattern, building an abstraction hierarchy of observations in which higher levels contain those observations with greater interpretative value of the physiological processes underlying a given signal. Non-monotonic reasoning techniques have been applied to this model in order to find the best interpretation of a set of initial observations, permitting even to correct these observations by removing, adding or modifying them in order to make them consistent with the available domain knowledge. Some preliminary experiments have been conducted to apply this framework to a well known and bounded problem: the QRS detection on ECG signals. The objective is not to provide a new better QRS detector, but to test the validity of an abductive paradigm. These experiments show that a knowledge base comprising just a few very simple rhythm abstraction patterns can enhance the results of a state of the art algorithm by significantly improving its detection F1-score, besides proving the ability of the abductive framework to correct both sensitivity and specificity failures.

The present study is a continuation work of my previous work in the art:" Algebraic Net Class Rewriting Systems, Syntax and Semantics for Knowledge Representation and Aut omated Problem Solving" in Tirri SI (2013), and preliminaries as well as related notations are to be found there. Lots of studies have been driven to clarify routes between nodes e.g. in process algebra, important topics setting ground to game theories as well as overall in halting problems. On the other hand in more complex dimensional cases ordering definitions in sets of subgraphs have been under vigorous investigations mainly concentrated in tree structures. An amazingly minute portion of studies on gr aphs concentrates to relations between graphs and abstraction of them and one explanation for this might be that transformations on conceptual levels lead joints to a succinct model proper to syntax as well as to semantic domain requiring combining algebra ic structures to loop structured graphs and realizations of them, this requiring symbiosis of abstract syntax and real case sides. The most remarkable study of human abstraction mechanism yielding a concrete result especially within mathematics in the for m of analytical tools has been manifested by French philosopher, mathematician and physicist Ren é Descartes in the 17th century in his work " Regulae ad directionem ingenii, Règles utiles et claires pour la direction de l'Esprit en la recherche de la Vérité (1628)", freely outlining: "… a t first we must organize the things which are the most essential ones in conc entrating to do that by simplifying from phase to phase the vague, indefinite original pro b lem. Then we try to understand the relations between tho se simplified parts and then compare the propositions to be proved i.e. wise versa try to see the connections between the reached relations and the original problem.