MedRem: An Interactive Medication Reminder and Tracking System on Wrist Devices

Md Abu Sayeed Mondol1, Ifat Afrin Emi1, John Stankovic1

  • 1University of Virginia

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Contributed Papers (Oral)

Sessions

14:00 - 15:00 | Wed 26 Oct | Main Auditorium | WeCT1

Technical Session 3: Innovations in Tools for Health Care

Abstract

Medication adherence is pivotal for effective health outcomes. One of the main reasons behind poor medication adherence is forgetfulness, and reminder systems are often used in addressing the problem. This paper presents MedRem, a novel medication reminder and tracking system on wearable wrist devices. The system is handy and interactive, and it is enriched with several useful features. To address the limitations of the tiny display size of the wrist devices, MedRem incorporates speech recognition and text-to-speech features along with clever interface design. Users interact with the system using voice commands as well as using the display available on the device. A dictionary based training approach is used on top of the state of the art speech recognition systems to reduce the errors in recognizing the commands from the users. The system is evaluated for both native and non-native English speakers. The error rates for recognizing voice commands are 6.43% and 20.9% for the native and the non-native speakers, respectively, when a off-the-shelf speech recognition system is used. MedRem reduces the error to nearly zero for both types of users through a dictionary based training approach. On average, only 1.25 and 15 training commands are required to achieve this performance for the native and the non-native speakers, respectively.

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