Manual Electrode Array Insertion Through a Robot-assisted Minimal Invasive Cochleostomy: Feasibility and Comparison of Two Different Electrode Array Subtypes.

HYPOTHESIS To evaluate the feasibility and the results of insertion of two types of electrode arrays in a robotically assisted surgical approach. BACKGROUND Recent publications demonstrated that robot-assisted surgery allows the implantation of free-fitting electrode arrays through a cochleostomy drilled via a narrow bony tunnel (DCA). We investigated if electrode arrays from different manufacturers could be used with this approach. METHODS Cone-beam CT imaging was performed on fivecadaveric heads after placement of fiducial screws. Relevant anatomical structures were segmented and the DCA trajectory, including the position of the cochleostomy, was defined to target the center of the scala tympani while reducing the risk of lesions to the facial nerve. Med-El Flex 28 and Cochlear CI422 electrodes were implanted on both sides, and their position was verified by cone-beam CT. Finally, temporal bones were dissected to assess the occurrence of damage to anatomical structures during DCA drilling. RESULTS The cochleostomy site was directed in the scala tympani in 9 of 10 cases. The insertion of electrode arrays was successful in 19 of 20 attempts. No facial nerve damage was observed. The average difference between the planned and the postoperative trajectory was 0.17 ± 0.19 mm at the level of the facial nerve. The average depth of insertion was 305.5 ± 55.2 and 243 ± 32.1 degrees with Med-El and Cochlear arrays, respectively. CONCLUSIONS Robot-assisted surgery is a reliable tool to allow cochlear implantation through a cochleostomy. Technical solutions must be developed to improve the electrode array insertion using this approach.

A Tutorial of the Mobile Multimedia Wireless Sensor Network (M3WSN) OMNeT++ Framework

In this work, we will give a detailed tutorial instruction about how to use the Mobile Multi-Media Wireless Sensor Networks (M3WSN) simulation framework. The M3WSN framework has been published as a scientific paper in the 6th International Workshop on OMNeT++ (2013) [1]. M3WSN framework enables the multimedia transmission of real video se- quence. Therefore, a set of multimedia algorithms, protocols, and services can be evaluated by using QoE metrics. Moreover, key video-related information, such as frame types, GoP length and intra-frame dependency can be used for creating new assessment and optimization solutions. To support mobility, M3WSN utilizes different mobility traces to enable the understanding of how the network behaves under mobile situations. This tutorial will cover how to install and configure the M3WSN framework, setting and running the experiments, creating mobility and video traces, and how to evaluate the performance of different protocols. The tutorial will be given in an environment of Ubuntu 12.04 LTS and OMNeT++ 4.2.

Trends in Human-Centric Multimedia Networking Scenarios

The evolution of wireless access technologies and mobile devices, together with the constant demand for video services, has created new Human-Centric Multimedia Networking (HCMN) scenarios. However, HCMN poses several challenges for content creators and network providers to deliver multimedia data with an acceptable quality level based on the user experience. Moreover, human experience and context, as well as network information play an important role in adapting and optimizing video dissemination. In this paper, we discuss trends to provide video dissemination with Quality of Experience (QoE) support by integrating HCMN with cloud computing approaches. We identified five trends coming from such integration, namely Participatory Sensor Networks, Mobile Cloud Computing formation, QoE assessment, QoE management, and video or network adaptation.