Automatic identification of solid-phase medication intake using wireless wearable accelerometers

Abstract

We have proposed a novel solution to a fundamental problem encountered in implementing non-ingestion based medical adherence monitoring systems, namely, how to reliably identify pill medication intake. We show how wireless wearable devices with tri-axial accelerometer can be used to detect and classify hand gestures of users during solid-phase medication intake. Two devices were worn on the wrists of each user. Users were asked to perform two activities in the way that is natural and most comfortable to them: (1) taking empty gelatin capsules with water, and (2) drinking water and wiping mouth. 25 users participated in this study. The signals obtained from the devices were filtered and the patterns were identified using dynamic time warping algorithm. Using hand gesture signals, we achieved 84.17 percent true positive rate and 13.33 percent false alarm rate, thus demonstrating that the hand gestures could be used to effectively identify pill taking activity.

Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease

“…This indirect method was chosen because it is easily applicable to large cohorts, but it requires reliable interactions with the smartwatch which may be difficult to achieve for individuals with advanced PD and may be susceptible to active deception (i.e., participant choosing not to consume the medication whilst acknowledging its intake) (15). In the future to reduce this risk, our system could be associated with medication specific upper arm movement detection algorithms, such as those developed by other authors (51)(52)(53).…”

Artificial intelligence in the field of pharmacy practice: A literature review

“…The addition of a fluorophore to the medication, which can be detected in the bloodstream with a monitoring device on the patient's wrist. 70 , 71 …”

“…EE/drospirenoneFlex was well tolerated, with 80% of women satisfied with the treatment. Wang R, 2014 70 USA To assess how wireless wearable devices equipped with a tri-axial accelerometer can be used to detect and classify user hand gestures during solid-phase medication administration. Prospective observational study Twenty-five subjects, aged 21 years and older Using hand gesture signals, the true positive rate was 84.17% and the false alarm rate was 13.33%, demonstrating that hand gestures could be used to effectively identify pill taking activity.…”

E-Textiles for Healthy Ageing

“…Example technologies that can support patient compliance include smartphone-based medication adherence applications providing scheduled reminders [32]. Other approaches aim to detect when medicines have been taken by, for example, incorporating sensors into medicine packaging [33] and activity recognition techniques detecting the motion associated with the twisting of a cap and the hand to mouth movement [34]. Inertial based sensors in clothing can also be used to detect the act of taking medicines and textile-based actuators/sounders can be used to provide a prompt for users to follow the prescription.…”