—There has been compelling evidence that
outpatients, especially those who are elderly or taking multiple
complexly scheduled drugs, are not taking their medicines as
complications, functional disabilities, lower quality of life, and
even mortality. Existing technologies for monitoring and
improving drug adherence are either costly or too complicated
for general patients to use. In this paper, we introduce the
detailed design and the complete prototype of a marketable
Radio-Frequency Identification (RFID)-based Medication
Adherence Intelligence System (RMAIS) that can be
conveniently used at a residential home by ordinary patients.
RMAIS is designed to maintain patients' independence and
enable them to take multiple daily medicine dosages of the right
amount at the right time. The system is patient-centered and
user-friendly by reminding a patient of the prescribed time for
medication and dispensing it in a fully automatic and fool-proof
way. This is achieved mainly due to its novel design of a
motorized rotation platform and the smooth integration of a
scale, an RFID reader, and the rotation platform. In addition,
this system has an Internet-based notification function that is
used to alert the patient when it is time to take medicine as well
as report deviations from the prescribed schedule to the
primary care physicians or pharmacists.
According to the national council report , “In the
United States and around the world, there is compelling
evidence that patients are not taking their medicines as
Medication noncompliance can result in unnecessary disease
progression, complications, lower quality of life, and even
mortality. As medical science has made possible new
therapies and medicines to effectively treat more chronic or
fatal diseases, medication schedules and conflicts between
medicines have become more complicated and difficult for
general patients to grasp. This problem is even worse for
elderly patients who are forgetful or have dementia.
The growing need for in-home healthcare devices is best
described in  as the population growth of retirement-age
Americans is projected to overload the current healthcare
system and inevitably cause it to fail in less than ten years.
Manuscript received April 1, 2010. This work was supported in part by
the National Science Foundation under Grant CNS-0627318.
Corey McCall, Branden Maynes and Cliff C. Zou are with the School of
Electrical Engineering and Computer Science, University of Central
Florida, 4000 Central Florida Blvd., Orlando, FL 32816 USA (phone: 407-
823-5015; fax: 407-823-5835; e-mail: email@example.com).
Ning J. Zhang is with College of Health and Public Affairs, University