ABSTRACT
We have designed and fabricated an interoperable system for medication adherence. The system is composed of a pillbox that wirelessly communicates with a computer application and a custom-made wristband. The system receives the information of taking specific medication from the user or caregiver, reminds the user to take the medication, monitors the user's hand gesture during the medication intake and monitors the compartments of the pillbox for refilling purpose. The performance of the developed system was examined in various bench-top scenarios. The system has the potential to improve the existing systems by reminding the user to take the medication through the wristband, automatically collecting user's hand gestures during the medication intake, and providing detailed information about the exisexistencetence of medication in the compartments of the pillbox.
Subject(s)
Medication Adherence , Tablets , Hand , Humans , SoftwareABSTRACT
Two tri-axial accelerometers were placed on the wrists (one on each hand) of the patients with Parkinson's disease (PD) and a non-PD control group. Subjects were asked to perform three of the upper extremity motor function tasks from the Unified Parkinson's Disease Rating Scale (UPDRS) test. The tasks were: 1) finger tapping, 2) opening and closing of palms, and 3) pronation-supination movements of the forearms. The inertia signals were wirelessly received and stored on a computer for further off-line analysis. Various features such as range, standard deviation, entropy, time to accomplish the task, and maximum frequency present in the signal were extracted and compared. The results showed that among the studied population, "standard deviation", "range", "entropy", "time" and "max frequency" are the best to worst features, respectively, to distinguish between the non-PD and PD subjects. Furthermore, using the mentioned features, it is more probable to distinguish between the non-PD and PD subjects from tasks 2 and 3 as opposed to task 1.