## 2 Related Work
Experimental trials with deep learning solutions [17] appear to be promising. The tradeoff is the computational costs and the amount of data required to create a proper learning model that classify correctly the rough movements of a patience. Streaming multimedia content in healthcare systems over Internet/Intranet [18] has also been a key component in the last decade. A theoretical framework proposed by [19] to have distributor system that delivers the multimedia contents in the healthcare system to doctors and professionals involves a number of different features; however, social schedule and a reliable communication system are not fully functional. There is no monitoring module either, and still lack of many concepts to build a monitoring system as the one presented here. Furthermore, the use of social media apps was not been fully exploited in any of the related projects. The use of a social network integrated in the social agenda is not present in the telehealth care systems. According to the World Health Organization, falls are the second most common cause of accidental or unintentional injury deaths worldwide. And a staggering 37.3 million falls are severe enough to require medical attention each year. A wide range of factors contributes to fall risks, such as environmental hazards, illness, neurological, mental conditions, muscle weakness, poor vision, and medication [10; 20; 21; 22; 23]. While there is no such thing as a 100% effective fall detection or prevention solution, most experts agree that a combination of available sensor technology can greatly increase system reliability. And there is a growing acceptance by seniors as monitoring is a means to extend their independent living opportunities [21; 23]. There is a system created and funded by European Agency: Ministry of industry, tourism and commerce, Spain. This project gets different users connected via smartphones and shares contents of TV programs that are currently on [24]. This is a way of sharing TV contents that are on and also of filtering the commercials based on the profile of the user. This system was not intended to be applied to telehealth care, although the technology and the idea can be used in the communication between the professional and the user to build a social agenda. Another application in telehealth care granted by the Ministry of industry, Energy and Tourism is introduced in Castellanos [25]. The system still requires a lot of improvements such as computer vision, multiple user interaction, and a complete social schedule. These three ideas can contribute with a major change in traditional tele treatment approaches. These three are in the top of the emerging and promising technologies and can improve dramatically the monitoring and the living quality of these minorities during the rehab process. Moreover, it is a small project, used as a demo in hospitals in different regions intended to monitor a small number of patients. This paper targets a bigger number of monitored patients by updating the resources of the communication servers. This is essential not only to increase the number of end users but also to keep technologies such as machine learning algorithms and computer vision running efficiently. A novel algorithm for biomedical image segmentations is introduced together with an algorithm for biomedical image feature selection in [PERSON] and [PERSON] [26]. Biomedical image segmentations and feature selection are foundations to detect and predict diseases. Discovering biomedical knowledge from medical text documents is a critical means for advancing medical practice and clinical outcomes in patients. A novel domain specific methodology is built to identify the word meanings in medical documents characterized by different domains [27]. This methodology uses a domain fusion algorithm to narrow domain concepts from different domain knowledge and avoids unknown domain problem; it can be effectively used for both biomedical information retrieval and text mining.