Exploration Of Lossy Posture Classification Model Using In-Bed Flexible Pressure Sensors

Moon, Aekyeung; Son, Seung Woo; Kim, Minjun; Chang, Seyun; Park, Hyeji

doi:10.1109/fleps57599.2023.10220219

2023 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS) 2023

DOI: 10.1109/fleps57599.2023.10220219

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Exploration Of Lossy Posture Classification Model Using In-Bed Flexible Pressure Sensors

Aekyeung Moon,

Seung Woo Son,

Minjun Kim

et al.

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2024

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Cited by 2 publications

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Effective Posture Classification Using Statistically Significant Data From Flexible Pressure Sensors

Yoon,

Moon,

Son

2024

IEEE Flex. Electron.

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Effective Posture Classification Using Statistically Significant Data From Flexible Pressure Sensors

Yoon,

Moon,

Son

2024

IEEE Flex. Electron.

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In-Bed Monitoring: A Systematic Review of the Evaluation of In-Bed Movements Through Bed Sensors

Ocagli,

Lanera,

Borghini

et al. 2024

Informatics

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The growing popularity of smart beds and devices for remote healthcare monitoring is based on advances in artificial intelligence (AI) applications. This systematic review aims to evaluate and synthesize the growing literature on the use of machine learning (ML) techniques to characterize patient in-bed movements and bedsore development. This review is conducted according to the principles of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and is registered in the International Prospective Register of Systematic Reviews (PROSPERO CRD42022314329). The search was performed through nine scientific databases. The review included 78 articles, including 142 ML models. The applied ML models revealed significant heterogeneity in the various methodologies used to identify and classify patient behaviors and postures. The assortment of ML models encompassed artificial neural networks, deep learning architectures, and multimodal sensor integration approaches. This review shows that the models for analyzing and interpreting in-bed movements perform well in experimental settings. Large-scale real-life studies are lacking in diverse patient populations.

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Exploration Of Lossy Posture Classification Model Using In-Bed Flexible Pressure Sensors

Cited by 2 publications

References 10 publications

Effective Posture Classification Using Statistically Significant Data From Flexible Pressure Sensors

Effective Posture Classification Using Statistically Significant Data From Flexible Pressure Sensors

In-Bed Monitoring: A Systematic Review of the Evaluation of In-Bed Movements Through Bed Sensors

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