ICS Dr. G. Roscher GmbH
Real-time Recognition of ECG
Recognition of ECG
a new Strategy for Risk Management in Heart-Circulation Diseases
optimal application of the portable
PhysioCord the physician uses a two or multi step strategy:
the first step, the recognition procedure runs on the stationary system with
high performance and visual evaluation by a qualified expert, a cardiologist.
The common recognition system recognizes the ECG and builds classes
automatically. The experienced physician evaluates the ECG and the classes,
marks significant and interesting signal structures in the ECG and in the
classes as well as using a powerful station with graphical user interface by
using the HeartScope. This process
generates the formal description of the signal in detail, ECG-substructures (P,
Q, R, S, T) up to heart beats and classes. The
critical pattern may be failing to identify proper ECG’s, e.g. by cardiac
arrest, appearance of iterative ECG’s with an elevated S-T, P-Q segments, e.g.
acute myocardial infarction (AMI), or grouped ECG’s with desperate elements,
e.g. torsade de points. All of these critical patterns can be adapted
individually to properly fit the properties of the individual patients. A
permanent monitoring of patients at risks, e.g. after an AMI or at the
beginning, during changes or respective dosage adaptation of a specific drug
treatment (anti-arrhythmica) gives new insight in these processes. Each of these
patterns with its descriptive details is stored in a data base permitting
further analysis. If a pattern does not match with previously described patterns
a new class of pattern will be opened. In this way several classes of patterns
of usually occurring ECG’s arise and can be offered for matching. Note that
patterns indicating harmful situation or being critical for surviving can be
introduced in this pattern recognition program by the physician.
patterns which characterize the ECG and the risk situations are the basis for
the next step: The portable recognition system with low power technology is
taught by templates for marked details, ECG-substructures, heart beats and class
descriptions of the same patient with the same electrode positions. The
recognition rate using this strategy is asymptotic near 100%.
In this way, the system can recognize risk situations in real-time with highest accuracy, while connecting the rescue organization by handy-function and transmit relevant data for evaluation and decision making by the physician. The receiver has a powerful Database & Knowledge Management System with direct access. The physician can evaluate the received signals in context with the course of the illness and the stored signals. He can decide with high accuracy in minimum time duration. The optimisation of this decision process is the key process in this step. This creates a high chance for saving risk patients in optimal time.