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Mobile phones are becoming a communication tool commonly used by people all over the world; and they are started to be adopted in psychosocial therapies involving vulnerable people. We are herein presenting the results of an academic literature review. We identified scientific papers published between 2006 and 2015 resorting to academic databases available on the Internet, applying a systematic selection method based on quality criteria. Secondly, we analysed contents, highlighting the scarcity of research involving vulnerable people. The available literature specialized in psychosocial therapies offers investigation results which involve mobile phones and patients in general, focusing particularly on the clinical psychology field and, to a lesser extent, on the social work field. Particularly significant are the investigation works developed in the United States. In the present paper we introduce a first 'state of the art', identifying opportunities and also the limitations surrounding the use of mobile phones in psychosocial therapies targeting the vulnerable. Issues concerning privacy and data confidentiality, and the access of vulnerable people to mobile phones and how they use them, pose significant challenges; but they offer the opportunity to reach isolated or impoverished populations, or even to facilitate access to social and healthcare services. We close this paper formulating possible orientations, hypotheses and goals to design new investigation works involving vulnerable populations. [ABSTRACT FROM AUTHOR]

In mobile health care monitoring, compression is an essential tool for solving storage and transmission problems. The important issue is able to recover the original signal from the compressed signal. The main purpose of this paper is compressing the ECG signal with no loss of essential data and also encrypting the signal to keep it confidential from everyone, except for physicians. In this paper, mobile processors are used and there is no need for any computers to serve this purpose. After initial preprocessing such as removal of the baseline noise, Gaussian noise, peak detection and determination of heart rate, the ECG signal is compressed. In compression stage, after 3 steps of wavelet transform (db04), thresholding techniques are used. Then, Huffman coding with chaos for compression and encryption of the ECG signal are used. The compression rates of proposed algorithm is 97.72 %. Then, the ECG signals are sent to a telemedicine center to acquire specialist diagnosis by TCP/IP protocol. [ABSTRACT FROM AUTHOR]

In this paper we have discussed the application of artificial intelligence in telemedicine using mobile device. The main goal of our research is to develop methods and systems to collect, analyze, distribute and use medical diagnostics information from multiple knowledge sources and areas of expertise. Physicians may collect and analyze information obtained from experts worldwide with the help of a medical decision support system. In this information retrieval system, modern communication tools such as computers and mobile phones can be used efficiently. In this work we propose a medical decision support system using the general packet radio service (GPRS). GPRS, a data extension of the mobile telephony standard Global system for mobile communications (GSM) is emerging as the first true packet-switched architecture to allow mobile subscribers to benefit from high-speed transmission rates and run JAVA based applications from their mobile terminals. An academic prototype of a medical decision support system using mobile device was implemented. The results reveal that the system could find acceptance from the medical community and it could be an effective means of providing quality health care in developing countries. [ABSTRACT FROM AUTHOR]