amsys 17(16): e3

Research Article

Medication Adherence using Non-intrusive Wearable Sensors

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  • @ARTICLE{10.4108/eai.19-12-2017.153484,
        author={T. H.  Lim and A. H.  Abdullah},
        title={Medication Adherence using Non-intrusive Wearable Sensors},
        journal={EAI Endorsed Transactions on Ambient Systems},
        volume={4},
        number={16},
        publisher={EAI},
        journal_a={AMSYS},
        year={2017},
        month={12},
        keywords={Medication Adherence, Body Sensor Networks, Activities Recognition, Hand Gesture},
        doi={10.4108/eai.19-12-2017.153484}
    }
    
  • T. H. Lim
    A. H. Abdullah
    Year: 2017
    Medication Adherence using Non-intrusive Wearable Sensors
    AMSYS
    EAI
    DOI: 10.4108/eai.19-12-2017.153484
T. H. Lim1,*, A. H. Abdullah1
  • 1: Universiti Teknologi Brunei, Tungku Highway, Gadong, Brunei Darussalam.
*Contact email: lim.tiong.hoo@utb.edu.bn

Abstract

Activity recognition approaches have been applied in home ambient systems to monitor the status and well- being of occupant especially for home care systems. With the advancement of embedded wireless sensing devices, various applications have been proposed to monitor user´s activities and maintain a healthy lifestyle. In this paper, we propose and evaluate a Smart Medication Alert and Treatment Electronic Systems (SmartMATES) using a non-intrusive wearable activity recognition sensing system to monitor and alert an user for missing medication prescription. Two sensors are used to collect data from the accelerometer and radio transceiver. Based on the data collected, SmartMATES processes the data and generate a model for the various actions including taking medication. We have evaluated the SmartMATES on 9 participants. The results show that the SmartMATES can identify and prevent missing dosage in a less intrusive way than existing mobile application and traditional approaches.