IoT-Enabled Health Promotion

Tan, Vanessa; Varghese, Susheela Abraham

doi:10.1145/2933566.2933571

Cited by 9 publications

(3 citation statements)

References 3 publications

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“…With the increase in the popularity of wearables as a consumer-level technology, bringing devices closer to ubiquity, and the potential of their effectiveness in healthcare, we believe that in the near future, factors such as cost (Fisch et al, 2016) will no longer impede wide-scale organizational policies. In fact, there have been nationwide initiatives such as National Step Challenge (MOH, 2020;Tan & Varghese, 2016) and the TraceTogether COVID-19 token involving the distribution and use of trackers in Singapore. With further development and acceptance of wearables devices, we predict that health wearables will become ubiquitous at the organizational and community levels.…”

Section: Policy Perspectivesmentioning

confidence: 99%

The state of wearable health technologies: a transdisciplinary literature review

Lin

Chib

2020

Mobile Media & Communication

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This review evaluated transdisciplinary empirical research on wearable health technologies using the input-mechanism-output model and addressed a major concern relating to the invasiveness of wearables. The dataset consisted of 250 published papers that investigated wearables for health-related purposes. Papers focused on technological inputs and health output factors, de-emphasizing theoretical mechanisms that could effectively translate the former into the latter. The lack of transdisciplinary research in the field is limiting both identification of effectiveness and evidence of beneficial health outcomes, with a considerable divide between technologists and public health researchers. Privacy concerns relate to increasing trends in collecting data for mental health and physical health, with the latter escalating exponentially. Invasiveness of wearables has increased over time in terms of collected signals and the derived health information, monitoring both users and their social and physical environments. We conclude with reflections for conceptual development, commercial application and policy regulation.

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Section: Policy Perspectivesmentioning

confidence: 99%

The state of wearable health technologies: a transdisciplinary literature review

Lin

Chib

2020

Mobile Media & Communication

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“…Various companies have already started making efforts to improve the office environment. Also, various projects and promotions that cooperate with multiple research fields for employee well-being have been launched in several countries [8].…”

Section: Related Workmentioning

confidence: 99%

Sensing and Changing Human Behavior for Workplace Wellness

Arakawa

2019

Journal of Information Processing

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Recently, companies have begun to care more about the well-being of their employees. With the spread of sensors, the Internet of Things, and artificial intelligence, the movement to build a better working environment by utilizing these technologies has been spreading. Especially, research on behavior that can change lifestyle habits is becoming popular. In this paper, we summarize workplace behavior research and projects for sensing and changing human behavior in a workplace and aim to improve the productivity and wellness of employees. Also, we introduce concepts for future workplaces and some of our related achievements. For physical state sensing, we have developed a continuous posture-sensing chair, which will soon be available commercially. For internal state sensing, we propose a method for estimating quality of life with wearable sensors. Our system have already achieved to estimate QoL (Quality of Life) around 90% with only 9 questions. In addition, we propose interactive digital signage to provide habit-changing reminders. Through one month experiment, we confirmed that our system can be feasible in daily life.

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“…Among them, MIoT accounts for a large proportion. Tan and Varghese [3] pointed out that there is a huge potential for the application of IoT in the health industry. Nevertheless, practical constraints must be taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

Neural Model Stealing Attack to Smart Mobile Device on Intelligent Medical Platform

Zhang

Lin

Gao

et al. 2020

Wireless Communications and Mobile Computing

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To date, the Medical Internet of Things (MIoT) technology has been recognized and widely applied due to its convenience and practicality. The MIoT enables the application of machine learning to predict diseases of various kinds automatically and accurately, assisting and facilitating effective and efficient medical treatment. However, the MIoT are vulnerable to cyberattacks which have been constantly advancing. In this paper, we establish a MIoT platform and demonstrate a scenario where a trained Convolutional Neural Network (CNN) model for predicting lung cancer complicated with pulmonary embolism can be attacked. First, we use CNN to build a model to predict lung cancer complicated with pulmonary embolism and obtain high detection accuracy. Then, we build a copycat model using only a small amount of data labeled by the target network, aiming to steal the established prediction model. Experimental results prove that the stolen model can also achieve a relatively high prediction outcome, revealing that the copycat network could successfully copy the prediction performance from the target network to a large extent. This also shows that such a prediction model deployed on MIoT devices can be stolen by attackers, and effective prevention strategies are open questions for researchers.

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IoT-Enabled Health Promotion

Cited by 9 publications

References 3 publications

The state of wearable health technologies: a transdisciplinary literature review

The state of wearable health technologies: a transdisciplinary literature review

Sensing and Changing Human Behavior for Workplace Wellness

Neural Model Stealing Attack to Smart Mobile Device on Intelligent Medical Platform

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