A Middleware Framework for Ambiguous Context Mediation in Smart Healthcare Application.
ABSTRACT Ubiquitous healthcare applications envision future computing and networking environments as being filled with sensors that can determine various types of contexts of its inhabitants, such as location, activity and vital signs. While such information is useful in providing context-sensitive services to the inhabitants to promote intelligent independent living, however in reality, both sensed and interpreted contexts may often be ambiguous. Thus, a challenge facing the development of realistic and deployable context-aware services is the ability to handle ambiguous contexts to prevent hazardous situations. In this paper, we propose a framework which supports efficient context-aware data fusion for healthcare applications that assume contexts could be ambiguous. Our framework provides a systematic approach to derive context fragments, and deal with context ambiguity in a probabilistic manner. We also incorporate the ability to represent contexts within the applications, and the ability to easily compose rules to mediate ambiguous contexts. Through simulation and analysis, we demonstrate the effectiveness of our proposed framework for monitoring elderly people in the smart home environment.
SourceAvailable from: Zubair Khalid
Dataset: UTM Paper
[Show abstract] [Hide abstract]
ABSTRACT: In this paper, a patient mobile monitoring enabling framework is presented. To this end, biometric devices (e.g. glucometers, blood pressure meters) are used to send data to the mobile phone via technologies such as NFC or Bluetooth among others. These data are complete by the doctor for the patient control. An ontological architecture has been built up to allow the cataloguing of the framework elements. An ontological classification of the patient profile and modules definition are presented. Moreover, as study case, these ontologies are implemented for chronic diseases, based on the monitoring and control of the convalescent person. Also, we present a predictive model to allow the control of the patient history based on analysis of past situation that allow predicting situation in a certain moment (variation on vital signs). In general, MoMo (Mobile Monitoring) Framework provides a solution to patients" mobile monitoring based on mobile and biometrics devices.
Conference Paper: Context aware biomedical robotic platform for elderly health care[Show abstract] [Hide abstract]
ABSTRACT: Health professionals, nursing and care staff are in short supply to cater to all the needs of the growing, global elderly population. This paper presents the design and implementation of a low cost and low power context aware robotic system to assist the elderly due to a desire to develop accessible technology for all countries and considering the poverty of many elderly. The system is furnished with 4 wheels for indoor navigation. It is equipped with 'environmental parameter monitoring' sensors and the system can be controlled by the user through voice commands. The system interprets the environmental contexts and makes context aware decisions based on the sensed information. On the basis of the previous medical history from the database server and the newly interpreted data, the decision making unit makes efficient decisions and gives feedback to the device control unit. The system improves the health of the elderly by regularly monitoring the environmental conditions of people.Computer Science & Education (ICCSE), 2013 8th International Conference on; 01/2013