Editorial to the special issue on CMBEBIH 2019: biomedical engineering - share the vision

Badnjević, Almir

doi:10.1007/s12553-020-00407-8

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…The challenges, rising costs of care and effects of sleep-related issues on the elderly motivate the need for a system that could assist medical practitioners and caregivers in residential-care in monitoring patients more efficiently. The Internet of Things (IoT) is the network of smart electronics device that are connected through internet equipping them with the capability of data exchange [13][14][15]. This capability of remote connectivity offered by IoT technology can be used remote monitoring of patients lacking access to effective health care.…”

Section: Introductionmentioning

confidence: 99%

CNN-Based Smart Sleep Posture Recognition System

Tang

Kumar

Nadeem

et al. 2021

IoT

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Sleep pattern and posture recognition have become of great interest for a diverse range of clinical applications. Autonomous and constant monitoring of sleep postures provides useful information for reducing the health risk. Prevailing systems are designed based on electrocardiograms, cameras, and pressure sensors, which are not only expensive but also intrusive in nature, and uncomfortable to use. We propose an unobtrusive and affordable smart system based on an electronic mat called Sleep Mat-e for monitoring the sleep activity and sleep posture of individuals living in residential care facilities. The system uses a pressure sensing mat constructed using piezo-resistive material to be placed on a mattress. The sensors detect the distribution of the body pressure on the mat during sleep and we use convolution neural network (CNN) to analyze collected data and recognize different sleeping postures. The system is capable of recognizing the four major postures—face-up, face-down, right lateral, and left lateral. A real-time feedback mechanism is also provided through an accompanying smartphone application for keeping a diary of the posture and send alert to the user in case there is a danger of falling from bed. It also produces synopses of postures and activities over a given duration of time. Finally, we conducted experiments to evaluate the accuracy of the prototype, and the proposed system achieved a classification accuracy of around 90%.

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Section: Introductionmentioning

confidence: 99%

CNN-Based Smart Sleep Posture Recognition System

Tang

Kumar

Nadeem

et al. 2021

IoT

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Health and technology revealing the vision on technological applications in contemporary healthcare

Stoeva

2020

Health Technol.

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The topical collection on Internet of Medical Things in e-Health has a significant contribution to the effective research and development of e-health systems. The guest editors have emphasized the importance of Ehealth for improving the fundamental concepts in traditional medicine, including the diagnostics and treatment processes. Various computational and research problems have been referred in terms of improvement of the scientific environment and provoking growth.

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Editorial to the special issue on CMBEBIH 2019: biomedical engineering - share the vision

Cited by 2 publications

References 13 publications

CNN-Based Smart Sleep Posture Recognition System

CNN-Based Smart Sleep Posture Recognition System

Health and technology revealing the vision on technological applications in contemporary healthcare

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