Certainty Modeling of a Decision Support System for Mobile Monitoring of Exercise induced Respiratory Conditions

Mobile health systems in recent times, have notably improved the healthcare\nsector by empowering patients to actively participate in their health, and by\nfacilitating access to healthcare professionals. Effective operation of these\nmobile systems nonetheless, requires high level of intelligence and expertise\nimplemented in the form of decision support systems (DSS). However, common\nchallenges in the implementation include generalization and reliability, due to\nthe dynamics and incompleteness of information presented to the inference\nmodels. In this paper, we advance the use of ad hoc mobile decision support\nsystem to monitor and detect triggers and early symptoms of respiratory\ndistress provoked by strenuous physical exertion. The focus is on the\napplication of certainty theory to model inexact reasoning by the mobile\nmonitoring system. The aim is to develop a mobile tool to assist patients in\nmanaging their conditions, and to provide objective clinical data to aid\nphysicians in the screening, diagnosis, and treatment of the respiratory\nailments. We present the proposed model architecture and then describe an\napplication scenario in a clinical setting. We also show implementation of an\naspect of the system that enables patients in the self-management of their\nconditions.\n