Graduation Semester and Year
2010
Language
English
Document Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Computer Science and Engineering
First Advisor
Fillia Makedon
Abstract
One of the issues in healthcare systems or medical information systems is the reduction of medical errors to ensure patient safety. Our approach is to develop a cyber physical system which applies different RFID tags to monitor medicine consumption and its impact in an assistive environment. This approach talks about detecting the medication intake pattern in an assistive environment and implements an application oriented experimental research which tracks the drug consumption pattern using RFID readers and tags, motion sensors, a wireless sensor mote and a weight sensor. In this approach, an energy efficient technique by using multiple sensor devices which aims in efficient information flow to achieve significant extension of the system lifetime is implemented.In our approach, we use wireless sensor network environment to gather a person's behavior of daily pill usage in an apartment. Most people especially elderly are likely to have a sudden behavioral change due to their aging or existing health problems. Therefore, it is necessary to have an autonomous system that can monitor their activities in order to prevent emergent situation in advance. Our approach presents a sensor network environment that can recognize normal behavioral patterns of the patients who live in an apartment without assistance. We use a Web Based Caregiver Module to make the process of monitoring the medicine consumption simpler and easier.
Disciplines
Computer Sciences | Physical Sciences and Mathematics
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Vinjumur, Jyothi K., "Detecting Medication Consumption Patterns In Assistive Environments" (2010). Computer Science and Engineering Theses. 29.
https://mavmatrix.uta.edu/cse_theses/29
Comments
Degree granted by The University of Texas at Arlington