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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]