A Novel Health Monitoring System using Patient Trajectory Analysis: Challenges and Opportunities

Continued advances and cost reduction in mobile devices such as smart phones made them widely used in our daily- life practices such as en route navigation and vehicle tracking. Health applications utilizing these battery-powered devices con- tinue to grow, and so does the demand for effective modeling and analysis tools to support data collected by these devices. Health monitoring applications in particular became very popular these days. However, researchers must overcome many challenges, such as data acquisition, data scales and data uncertainty, in order to develop such applications. In this paper, we propose a novel health monitoring system that can interact with the patient and analyze the patient's moving trajectories combined with data of environmental conditions. We present a system architecture, and discuss ideas and challenges in developing the health monitoring system for asthma patients. This system can provide a better understanding of the effect of environmental factors on triggering health attacks and hence support individual-based health care. Index Terms—health monitoring, uncertain trajectories, envi- ronmental factors, asthma, road networks I. INTRODUCTION Relations between negative health effects like asthma and lung cancer and elevated levels of the environmental factors, such as air pollution, tobacco smoke and humidity, have been detected in several large scale exposure studies (8). Thus, public health care and service systems often require the ability to track, monitor, and analyze patients' trajectories and their relationships with several environmental factors in order to derive conclusions that will help in preventing and treating diseases. Health applications dealing with large volume of continuously moving data objects, such as humans and ve- hicles continue to grow. However, these applications present significant challenges in terms of data size, data scales, com- plex structures and relationships, uncertainty, and space and time constraints. Tracking moving objects has been a hot issue recently due to the large number of applications that depend heavily on it. However, individual monitoring of exposure to environmental conditions did not follow the same pace despite its great impact on public health; the general effect on earth has more been the concern. Limited research has been done on techniques for retrieving, storing and analyzing real-time data of patients along with the environmental conditions patients are exposed to. The main objective of this research is to improve public health care through proposing ideas and directions to develop an effective and efficient real-time health monitoring system that can report potential health threats (e.g., asthma attacks) associated with environmental conditions, support individual's long-term health care management, reduce the cost, effort and time spent in traditional health visits to hospitals, and provide intelligent information that might be useful for improving public health care plans and strategies. Although we are targeting asthma in this paper as it is well known that asthma is highly affected by surrounding environmental conditions (2), (13), our proposed system can be used in improving the general well-being as well as targeting other diseases that are affected by the environment. This paper focuses on the two main components in develop- ing our proposed system that takes into account the correlation between the time and location of a patient and the level and time of exposure to negative environmental factors; these are patient trajectory tracking and environmental exposure measurement. The first component can be obtained by location tracking devices such as the GPS. The second component not only includes air pollution level but also other measurements, such as humidity and temperature levels, that can be normal to healthy people but not to asthma patients. Finally, we discuss challenges and opportunities to develop the proposed system and conclude the paper.