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Content Provider | IEEE Xplore Digital Library |
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Author | Müller, M. Loijens, P. Schilberg, D. Jeschke, S. |
Copyright Year | 2010 |
Description | Author affiliation: Institute of Information Management in Mechanical Engineering of RWTH Aachen University, Germany (Müller, M.; Loijens, P.; Schilberg, D.; Jeschke, S.) |
Abstract | In developed countries many of the main causes of death such as heart attack and stroke usually strike outside of hospitals. Therefore patient outcome depends to a large extent on the quality of preclinical care. In order to improve it, Telematic Rescue Assistance Systems (TRAS) are being developed. They transmit vital signs, audio and sometimes video data from the rescue team to an emergency physician at a remote site, thus enabling this specialist to assist in diagnosis and treatment. Not only is specialist expertise brought to the emergency site, but also time to definite treatment is reduced, as specialists are involved earlier and hospitals are informed in advance about incoming patients. Due to their use in emergencies, risks to the proper functioning of TRAS hardware have to be kept as low as possible. Adequate methods for risk assessment have to be chosen, since the use of an inadequate method can result in a cumbersome resource-intensive process, while at the same time major risks are being overlooked. This paper proposes a methodology for reducing hardware risks in the development of TRAS. |
Starting Page | 2163 |
Ending Page | 2166 |
File Size | 756890 |
Page Count | 4 |
File Format | |
ISBN | 9781424441235 |
ISSN | 1557170X |
DOI | 10.1109/IEMBS.2010.5626405 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-08-31 |
Publisher Place | Argentina |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Medical services Hardware Analytical models Risk management Reliability Brain modeling Hazards |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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