Rajesh M. Hegde, B.S. Manoj, Bashkar D. Rao, & Ramesh R. Rao. (2006). Emotion detection from speech signals and its applications in supporting enhanced QoS in emergency response. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 82–91). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Networking in the event of disasters requires new hybrid wireless architectures such as Wireless Mesh Networks (WMNs). Provisioning Quality of Service (QoS) in such networks which are quickly deployed during emergencies demand radical solutions. In this paper, we provide a new QoS approach for voice calls over a wireless mesh networks during emergency situations. According to our scheme, the contention and back-off parameters are modified based on the emotion content in the voice streams. This paper also looks at methods for detecting emotion from an incoming voice call using the speech signal. The issues of interest in such situations are whether the caller is in a state of extreme panic, moderate panic, or in a normal state of behavior. The communication network behavior should be modified to provide differentiated QoS for calls based on the degree of emotion. We use several features extracted from the speech signal like the range of pitch variation, energy in the critical bark band, range of the first three formant variations, and speaking rate among others to discriminate between the three emotional states. At the back end the Gaussian mixture modeling techniques is used to model the three emotional states of the speaker. Since a large number of features increase the computational complexity and time, a feature selection technique is employed based on the Bhattacharya distance, to select the set of features that give maximum discrimination between the classes. These set of features are employed to simulate an emotion recognition system. The results indicate a promising emotion detection rate for the three emotions. We also present the early results on detecting the emotion content in the speech and using this in the MAC layer differentiated QoS provisioning scheme. Our scheme provides an end-to-end delay performance improvement for panicked calls as high as 60% compared to normal calls.
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Kai Kamphenkel, Markus Blank, Jens Bauer, & Georg Carle. (2007). Secure transmission of pre-clinical ultrasound video data at the scene of a mass casualty incident. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 377–383). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The use of portable ultrasound devices enables a better and immediate diagnostics at the scene of a mass casualty incident. The detection of free fluid in abdomen and thorax is an important indicator for the further treatment. The gained information affects the triage of casualties, the pre-clinical medical attendance and the patient management. The presented article describes an innovative approach to transmit sonographic video streams over wireless networks to a remote hospital, where the medical data is used for diagnostics. For the secure transmission of data a new network unit is designed, which gathers information with regard to the network status and the character of transported data. This “Intelligent Network” is located in the transport layer of the OSI reference model and enables a dynamic interconnection between network and application, provides an interface for functional transparency and the disclosure of parameters and establishes the basis for an universal security system.
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