Bigdata Oriented Multimedia Mobile Health Applications

Abstract

In this paper, two mHealth applications are introduced, which can be employed as the terminals of bigdata based health service to collect information for electronic medical records (EMRs). The first one is a hybrid system for improving the user experience in the hyperbaric oxygen chamber by 3D stereoscopic virtual reality glasses and immersive perception. Several HMDs have been tested and compared. The second application is a voice interactive serious game as a likely solution for providing assistive rehabilitation tool for therapists. The recorder of the voice of patients could be analysed to evaluate the long-time rehabilitation results and further to predict the rehabilitation process.

Symbian OS for Developing Mobile Multimedia Software Platform for Gymnastics

“…At this moment, the information media play an important role, and the emergence of mobile multimedia brings great convenience to the modern society [2]. Mobile multimedia are the portable mobile devices which are the integration of the computer and video technique to realize the information communication and transmission between human and computer on two or above media [3]. Simply, a mobile phone that people use is a carrier of mobile multimedia, whose functions contain network, music, films, information, pictures, etc.…”

Multi dimension query of sports video for cloud service environment

“…The classification of sports video mainly includes features extraction, divider design and other key contents; at present, there are sports video extraction methods of mainly static features, movement features and integration of these two etc [3][4][5]; single static features or movement static features can only describe part and clip information of sports video category and misclassification phenomenon happen easily, therefore, multi-feature has become the main sports video classification method [5]. Compared with single features, multiple features method can describe sports video category information from various perspectives and the accuracy rate of sports video classification has been improved accordingly, however, traditional features combination algorithm merely combines several features together in a simple way but not realize effective integration, which has caused high complexity of feature space and high dimension of divider input but the accuracy, timeliness and stability of sports video classification is still very low.…”

A Fast Image Retrieval Method Designed for Network Big Data

“…when the size of the image database increases to a certain extent, manual labeling for each image will become impossible to achieve. At the same time, due to the humans' understanding to image content often has a strong subjectivity, the description for the same image will be different in manual annotation [15]- [17].…”