Implementation of a Wearable Sensor Vest for the Safety and Well-being of Children

Jutila, Mirjami; Rivas, Helena; Karhula, Pekka; Pantsar-Syväniemi, Susanna

doi:10.1016/j.procs.2014.05.507

Cited by 24 publications

(8 citation statements)

References 12 publications

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“…In this work, they analyzed activities, such as wiggling, rolling, standing still, standing up, sitting down, walking, toddling, crawling, climbing up, climbing down, and stopping, achieving an accuracy of 98.43%. Jutila et al [ 15 ] presented a work where they developed a prototype of a portable vest to improve the safety and well-being of children in kindergarten and elementary schools, which contains a GPS, temperature sensors and accelerometers. Through this garment and the sensors it contains, they collected information on the general well-being, behavior and activities of children, being able to categorize activities, such as walking, running, sitting, staying still, as well as data on body temperature and the location of the children.…”

Section: Related Workmentioning

confidence: 99%

Children’s Activity Classification for Domestic Risk Scenarios Using Environmental Sound and a Bayesian Network

et al. 2021

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Children’s healthcare is a relevant issue, especially the prevention of domestic accidents, since it has even been defined as a global health problem. Children’s activity classification generally uses sensors embedded in children’s clothing, which can lead to erroneous measurements for possible damage or mishandling. Having a non-invasive data source for a children’s activity classification model provides reliability to the monitoring system where it is applied. This work proposes the use of environmental sound as a data source for the generation of children’s activity classification models, implementing feature selection methods and classification techniques based on Bayesian networks, focused on the recognition of potentially triggering activities of domestic accidents, applicable in child monitoring systems. Two feature selection techniques were used: the Akaike criterion and genetic algorithms. Likewise, models were generated using three classifiers: naive Bayes, semi-naive Bayes and tree-augmented naive Bayes. The generated models, combining the methods of feature selection and the classifiers used, present accuracy of greater than 97% for most of them, with which we can conclude the efficiency of the proposal of the present work in the recognition of potentially detonating activities of domestic accidents.

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Section: Related Workmentioning

confidence: 99%

Children’s Activity Classification for Domestic Risk Scenarios Using Environmental Sound and a Bayesian Network

et al. 2021

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“…The mostly round shape, however, enables wearing these boards unhidden on the outer side of smart clothes, using them as additional design elements, as shown in Fig. 4 [48,49]. In the designer and maker scenes, a broad range of highly creative projects exist, mostly based on SBMs.…”

Section: Recent Sbcs and Sbmsmentioning

confidence: 99%

“…a) Safety vest for children, applying an Arduino LilyPad, from[48], originally published under a CC-BY-NC-ND license; (b) wireless smart glove, from[49], originally published under a CC-BY license.…”

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confidence: 99%

Suitability of common single circuit boards for sensing and actuating in smart textiles

Ehrmann¹,

Ehrmann

2020

cdatp

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Single-board computers and microcontrollers such as Raspberry Pi or Arduino are nowadays used in a broad range of applications. Their relatively low power consumption and low price, compact dimensions and relative ease to program them make them suitable for diverse areas of measuring and controlling various parameters. In the textile area, however, such single-board computers are still less often used than in other projects, in spite of their aforementioned advantages in comparison to other solutions. Here we give an overview of the differences between single-board computers and single-board microcontrollers in general, compare different versions and give examples which projects are reported in the scientific literature, in design or in the maker scene, enabling researchers, designers and makers to decide which future projects necessitate which single circuit boards.

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“…), children going missing and parents fetching their children from the nursery/school. For more detailed information about the vest implementation, see our recent publications (Jutila et al, 2014(Jutila et al, , 2015.…”

Section: Safety Vest Prototypementioning

confidence: 99%

Wearable and mobile sensors connected to social media in human well-being applications

Mian

Oinas-Kukkonen

Riekki

et al. 2016

Telematics and Informatics

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Implementation of a Wearable Sensor Vest for the Safety and Well-being of Children

Cited by 24 publications

References 12 publications

Children’s Activity Classification for Domestic Risk Scenarios Using Environmental Sound and a Bayesian Network

Children’s Activity Classification for Domestic Risk Scenarios Using Environmental Sound and a Bayesian Network

Suitability of common single circuit boards for sensing and actuating in smart textiles

Wearable and mobile sensors connected to social media in human well-being applications

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