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Assisted Medication Management in Elderly Care Using Miniaturised Near-Infrared Spectroscopy

Published:05 July 2018Publication History
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Abstract

Near-infrared spectroscopy (NIRS) measures the light reflected from objects to infer highly detailed information about their molecular composition. Traditionally, NIRS has been an instrument reserved for laboratory usage, but recently affordable and smaller devices for NIRS have proliferated. Pairing this technology with the ubiquitous smartphone opens up a plethora of new use cases. In this paper, we explore one such use case, namely medication management in a nursing home/elderly care centre. First, we conducted a qualitative user study with nurses working in an elderly care centre to examine the protocols and workflows involved in administering medication, and the nurses' perceptions on using this technology. Based on our findings, we identify the main impact areas that would benefit from introducing miniaturised NIRS. Finally, we demonstrate via a user study in a realistic scenario that miniaturised NIRS can be effectively used for medication management when leveraging appropriate machine learning techniques. Specifically, we assess the performance of multiple pre-processing and classification algorithms for a selected set of pharmaceuticals. In addition, we compare our solution with currently used methods for pharmaceutical identification in a local care centre. We hope that our reflection on the multiple aspects associated with the introduction of this device in an elderly care setting can help both academics and practitioners working on related problems.

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        cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
        Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 2, Issue 2
        June 2018
        741 pages
        EISSN:2474-9567
        DOI:10.1145/3236498
        Issue’s Table of Contents

        Copyright © 2018 ACM

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        Publication History

        • Published: 5 July 2018
        • Accepted: 1 April 2018
        • Revised: 1 February 2018
        • Received: 1 November 2017
        Published in imwut Volume 2, Issue 2

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