Using a neural network in a first-aid single point sensor system to analyze and determine cardiopulmonary functions of a casualty in an emergency

In the paper algorithms are presented that are necessary to analyze cardiovascular and cardiopulmonary parameters which are provided by a first-aid sensor system. The parameters detected at a single point of the patient's neck are combined and interpreted by a neural network. The algorithms will be integrated into a pocket sized sensor system which thereby provides first aiders with the means to easily and quickly assess the status of the vitality parameters of an unconscious casualty. The initially detected parameters, i.e. electrocardiogram, mechanical pulse wave and respiration, are analyzed in time and frequency domains and put into correlation. The data is then routed to a neural network. All the data received will now be reduced to a simple statement of "cardiopulmonary resuscitation yes or no" which will then be transmitted to the first aider.