The progress of computer science has brought with it additional demands for the integration of various technologies onto the portable personal computer (PC) and at the same time has given raise to many novel applications. In the application presented here, the minimized potable PhysioCord is used with a standardized interface connecting the amplifier for ECG and other signals, DECT and as option GSM function modules. 

The structure for the portable which is introduced can provide lower profile, better performance and less power consumption. 

The portable is realized by its external connection abilities and interface with external devices. 

The recognition is realized by using the following methods:

- Neural networks for feature extraction,

- Fuzzy-logic for pattern recognition,

- Evolutionary algorithms for classification,

- Dynamic lists for internal management of signal description in real-time,

- Database systems for external management of signal description and clinical data.  

- Knowledge management systems for the acquisition of knowledge of clinical experts.

However, the real-time recognition of ECG-signals in the time-domain used on the patented method and the application of new information and communication technologies employed gives a high quality for recognition of risk situation.

The progress of computer science has brought with it additional demands for the integration of various technologies onto the portable personal computer (PC) and at the same time has given raise to many novel applications. In the application presented here, the minimized portable PC is used with a standardized interface connecting the amplifier for ECG and other signals, GSM and as option GPS function modules. The structure for the portable which is introduced can provide lower profile, better performance and less power consumption. The proposed portable PC is realized by its external connection abilities and interface with external devices. 

For optimal application of the portable the physician uses a two or multi step strategy:

In 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 graphical user interface. 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.

These 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 management with direct access. The physician can evaluate the received signals in context with the course of the illness and the stored signals in the database. He can decide with high accuracy in minimum time duration. The optimization of this decision process is the key process in this step. This creates a high chance for saving risk patients in optimal time.

Publication PhysioCord                     PatiMon                    CARiMan                        Herz                        EKGNLD