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In this paper, the application of individual scenario-based traffic models in identifying the traffic carrying needs of networks in patient monitoring environments is presented. Since the total number of traffic sources is small for a central limit theorem-like approximation, a simple traffic matrix for each scenario can be used to identify the capacity needed for carrying data. The data traffic is classified into three categories; constant bit rate (CBR), On-Off, and Impulsive. In digital communications, the Impulsive traffic is considered a limiting case of the On-Off traffic. Lack of standard mechanisms for digitization of the patient monitoring data offers a unique challenge for traffic modeling. Sample traffic characteristics in a certain scenario are used to demonstrate that the network does not have to be designed for a very high bit rate even if some sources occasionally generate high data rates. This is due to the fact that a source generating high data rate could do so only for a small fraction of time, which results in smoothing out the data over longer periods of time.