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Looking to the medical environment of the 21st Century, this paper describes the use of the signal interchange format (SIGIF) standard to integrate the data collected by biological signal monitoring systems with systems from other parts of a hospital or research facility. This paper covers three parts of this process. The first is the signal archive and communications system (SACS) which collects the data directly from a patient, the second part covers the signal interchange format standard which is used to communicate data from the SACS to a picture archive and communications system (PACS), and the last part covers the changes to a PACS. The concept of a signal archive and communications system was presented at the 1993 IEEE Engineering in Medicine and Biology Conference as part of a paper by Joao Paulo Cunha. This paper attempts to define a specific architecture for a SACS and describe changes to published descriptions of a PACS required to complete the PACS/SACS interface. For over 15 years the use of computerized signal collections systems have been commonly accepted as part of hospital and research environments. Each manufacture has devised a unique, and usually proprietary, method of storing that information. During that time, very little has been done to provide a common standard so this information could be communicated to another computer. This has resulted in millions of miles of hard copy printouts being stored in patient records. The radiology departments have had the same problem; however, they solved the problem with the ACR/NEMA DICOM standard. The SIGIF standard is being presented as an equivalent standard to solve the communications problem for biological signal data. This paper presents a new step in the integration of bio-signal collection systems with other hospital data processing systems. The concept being presented for the first time in this paper is to convent signal information into the DICOM image format. Each pixel of the image will represent one data point from a biological signal. A twelve lead EKG would result in twelve images representing approximately 30 minutes of collected data. Each image would take up less than 2 MBytes of information based on an 8 bit, 1024 samples per second, A/D converter. Once this conversion has been performed the signal data can be integrated into the PACS environment without requiring any additional software. It can be processed, filtered, displayed, and stored using the same algorithms as would be used for an MRI image. The concepts presented in this paper open up the use of the hospitals computational resources to signal data; that, at the present time, are reserved for the processing, display, and storage of radiology department images.
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