Methodology based on linguistic protoforms for activity detection in patients with type 2 diabetes mellitus
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Date
2024-01-03
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1764
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Abstract
Nowadays, activity recognition systems are a very hot topic with a high applicability in almost any field. These types of systems are capable of detecting human activities using Internet of Things devices that incorporate a set of sensors that allow us to collect events associated with such activities. This study presents a general methodology based on linguistic protoforms for human activity detection. This methodology approaches one of the main challenges of this type of systems, multi-occupancy, and for this purpose it incorporates an indoor localisation system. Furthermore, this methodology is applied in a real environment in patients affected by type 2 diabetes mellitus with the aim of enabling health care professionals to check the degree of compliance with the therapeutic contract. Finally, an analysis is conducted of the alignment of the Sustainable Development Goals with this research.
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Soft Computing: Theory Innovations and Problem-Solving Benefits, diabetes, human activity recognition, linguistic protoforms
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10 pages
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Proceedings of the 57th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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