Assisted medication management in elderly care using miniaturised near-infrared spectroscopy
Klakegg, Simon; Goncalves, Jorge; Luo, Chu; Visuri, Aku; Popov, Alexey; van Berkel, Niels; Sarsenbayeva, Zhanna; Kostakos, Vassilis; Hosio, Simo; Savage, Scott; Bykov, Alexander; Meglinski, Igor; Ferreira, Denzil (2018-06-01)
Simon Klakegg, Jorge Goncalves, Chu Luo, Aku Visuri, Alexey Popov, Niels van Berkel, Zhanna Sarsenbayeva, Vassilis Kostakos, Simo Hosio, Scott Savage, Alexander Bykov, Igor Meglinski, and Denzil Ferreira. 2018. Assisted Medication Management in Elderly Care Using Miniaturised Near-Infrared Spectroscopy. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 2, Article 69 (July 2018), 24 pages. DOI: https://doi.org/10.1145/3214272
© Copyright is held by the owner/author(s). | ACM 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of ACM on interactive, mobile, wearable and ubiquitous technologies, http://dx.doi.org/10.1145/3214272.
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https://urn.fi/URN:NBN:fi-fe201902205812
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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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