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Article

Exploring a Fuzzy Rule Inferred ConvLSTM for Discovering and Adjusting the Optimal Posture of Patients with a Smart Medical Bed

1
SKK Business School, Sungkyunkwan University, Seoul 03063, Korea
2
Predictive Analytics and Data Science, Economics Department, Airports Council International (ACI) World, Montreal, QC H4Z 1G8, Canada
3
Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul 03063, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2021, 18(12), 6341; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18126341
Received: 17 April 2021 / Revised: 26 May 2021 / Accepted: 4 June 2021 / Published: 11 June 2021
(This article belongs to the Special Issue Technological Innovation in Clinical Healthcare and Health Management)
Several countries nowadays are facing a tough social challenge caused by the aging population. This public health issue continues to impose strain on clinical healthcare, such as the need to prevent terminal patients’ pressure ulcers. Provocative approaches to resolve this issue include health information technology (HIT). In this regard, this paper explores one technological solution based on a smart medical bed (SMB). By integrating a convolutional neural network (CNN) and long-short term memory (LSTM) model, we found this model enhanced performance compared to prior solutions. Further, we provide a fuzzy inferred solution that can control our proposed proprietary automated SMB layout to optimize patients’ posture and mitigate pressure ulcers. Therefore, our proposed SMB can allow autonomous care to be given, helping prevent medical complications when lying down for a long time. Our proposed SMB also helps reduce the burden on primary caregivers in fighting against staff shortages due to public health issues such as the increasing aging population. View Full-Text
Keywords: smart medical bed; health information technology; ConvLSTM; fuzzy inference; clinical healthcare; public health smart medical bed; health information technology; ConvLSTM; fuzzy inference; clinical healthcare; public health
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MDPI and ACS Style

Costello, F.J.; Kim, M.G.; Kim, C.; Lee, K.C. Exploring a Fuzzy Rule Inferred ConvLSTM for Discovering and Adjusting the Optimal Posture of Patients with a Smart Medical Bed. Int. J. Environ. Res. Public Health 2021, 18, 6341. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18126341

AMA Style

Costello FJ, Kim MG, Kim C, Lee KC. Exploring a Fuzzy Rule Inferred ConvLSTM for Discovering and Adjusting the Optimal Posture of Patients with a Smart Medical Bed. International Journal of Environmental Research and Public Health. 2021; 18(12):6341. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18126341

Chicago/Turabian Style

Costello, Francis J., Min G. Kim, Cheong Kim, and Kun C. Lee 2021. "Exploring a Fuzzy Rule Inferred ConvLSTM for Discovering and Adjusting the Optimal Posture of Patients with a Smart Medical Bed" International Journal of Environmental Research and Public Health 18, no. 12: 6341. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18126341

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