Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

Fazio, Roberto De; Giannoccaro, Nicola Ivan; Carrasco, Miguel; Velázquez, Ramiro; Visconti, Paolo

doi:10.1631/fitee.2100085

Cited by 15 publications

(13 citation statements)

References 79 publications

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“…This article reviews 8 IoT-based wearable device surveys [2]- [6], [45]- [47]. In addition, we also collected 36 studies on wearable devices applied in medical, healthcare, and other fields [7]- [32], [50]-Error!…”

Section: Research Selection Methodsmentioning

confidence: 99%

“…To be able to fight the virus, there are many innovative wearable devices. De Fazio et al [6] propose a survey of applications for remote monitoring of infected patients, tracing contacts with infected people, and breaking the chain of infection. Using a wearable device to deal with virus-related affairs has significantly reduced the risk for people.…”

Section: Related Workmentioning

confidence: 99%

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The Internet of Things for Applications in Wearable Technology

et al. 2022

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The advent of the Internet of Things (IoT) era has propelled the development of wearable technology. Wearable devices are widely used in medical, healthcare, sports, and safety applications, bringing more convenience to the living environment. Wearable devices can be worn on the body, collect body data using sensors, and process the collected data to obtain valuable information. IoT enables devices to connect and exchange and transmit data. Wearable devices in IoT can collect data for analysis and automatically adjust wearable device functions by connecting the obtained information to other devices. In this paper, we collect and organize articles on wearable devices used in IoT from 2017 to 2022 in terms of their applications, advantages, and disadvantages. We evaluate articles to identify wearable device application areas and evaluation criteria. Finally, we discussed the open issues of wearable devices and clarified how to face the future development and efforts of wearable devices in IoT.

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Section: Research Selection Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

The Internet of Things for Applications in Wearable Technology

et al. 2022

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“…This alternate approach has mainly been described in theory [41,42] and some versions have been tested in laboratory settings [43]. There are also examples of available wearables in the market employing this approach, and various devices have been implemented in real-life settings [64]. Compared with CTAs, the research on this approach is scarce, but evaluative studies are emerging [65].…”

Section: Technologiesmentioning

confidence: 99%

Addressing Complexity in the Pandemic Context: How Systems Thinking Can Facilitate Understanding of Design Aspects for Preventive Technologies

Zetterholm

Jokela

2023

Informatics

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The COVID-19 pandemic constitutes a wicked problem that is defined by rapidly evolving and dynamic conditions, where the physical world changes (e.g., pathogens mutate) and, in parallel, our understanding and knowledge rapidly progress. Various preventive measures have been developed or proposed to manage the situation, including digital preventive technologies to support contact tracing or physical distancing. The complexity of the pandemic and the rapidly evolving nature of the situation pose challenges for the design of effective preventive technologies. The aim of this conceptual paper is to apply a systems thinking model, DSRP (distinctions, systems, relations, perspectives) to explain the underlying assumptions, patterns, and connections of the pandemic domain, as well as to identify potential leverage points for design of preventive technologies. Two different design approaches, contact tracing and nudging for distance, are compared, focusing on how their design and preventive logic are related to system complexity. The analysis explains why a contact tracing technology involves more complexity, which can challenge both implementation and user understanding. A system utilizing nudges can operate using a more distinct system boundary, which can benefit understanding and implementation. However, frequent nudges might pose challenges for user experience. This further implies that these technologies have different contextual requirements and are useful at different levels in society. The main contribution of this work is to show how systems thinking can organize our understanding and guide the design of preventive technologies in the context of epidemics and pandemics.

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“…In this context, wearable devices represent powerful tools for gathering information related to the user’s condition directly from home. These tools were widely employed during the COVID-19 pandemic to avoid the overload of health systems [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Social Media Devices’ Influence on User Neck Pain during the COVID-19 Pandemic: Collaborating Vertebral-GLCM Extracted Features with a Decision Tree

et al. 2023

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The prevalence of neck pain, a chronic musculoskeletal disease, has significantly increased due to the uncontrollable use of social media (SM) devices. The use of SM devices by younger generations increased enormously during the COVID-19 pandemic, being—in some cases—the only possibility for maintaining interpersonal, social, and friendship relationships. This study aimed to predict the occurrence of neck pain and its correlation with the intensive use of SM devices. It is based on nine quantitative parameters extracted from the retrospective X-ray images. The three parameters related to angle_1 (i.e., the angle between the global horizontal and the vector pointing from C7 vertebra to the occipito-cervical joint), angle_2 (i.e., the angle between the global horizontal and the vector pointing from C1 vertebra to the occipito-cervical joint), and the area between them were measured from the shape of the neck vertebrae, while the rest of the parameters were extracted from the images using the gray-level co-occurrence matrix (GLCM). In addition, the users’ ages and the duration of the SM usage (H.mean) were also considered. The decision tree (DT) machine-learning algorithm was employed to predict the abnormal cases (painful subjects) against the normal ones (no pain). The results showed that angle_1, area, and the image contrast significantly increased statistically with the time of SM-device usage, precisely in the range of 2 to 9 h. The DT showed a promising result demonstrated by classification accuracy and F1-scores of 94% and 0.95, respectively. Our findings confirmed that the objectively detected parameters, which elucidate the negative impacts of SM-device usage on neck pain, can be predicted by DT machine learning.

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Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey

Cited by 15 publications

References 79 publications

The Internet of Things for Applications in Wearable Technology

The Internet of Things for Applications in Wearable Technology

Addressing Complexity in the Pandemic Context: How Systems Thinking Can Facilitate Understanding of Design Aspects for Preventive Technologies

Social Media Devices’ Influence on User Neck Pain during the COVID-19 Pandemic: Collaborating Vertebral-GLCM Extracted Features with a Decision Tree

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