fitness trackers
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Fitness trackers are increasingly popular. The data they collect provides substantial benefits to their users, but it also creates privacy risks. In this work, we investigate how fitness-tracker users perceive the utility of the features they provide and the associated privacy-inference risks. We conduct a longitudinal study composed of a four-month period of fitness-tracker use (N = 227), followed by an online survey (N = 227) and interviews (N = 19). We assess the users' knowledge of concrete privacy threats that fitness-tracker users are exposed to (as demonstrated by previous work), possible privacy-preserving actions users can take, and perceptions of utility of the features provided by the fitness trackers. We study the potential for data minimization and the users' mental models of how the fitness tracking ecosystem works. Our findings show that the participants are aware that some types of information might be inferred from the data collected by the fitness trackers. For instance, the participants correctly guessed that sexual activity could be inferred from heart-rate data. However, the participants did not realize that also the non-physiological information could be inferred from the data. Our findings demonstrate a high potential for data minimization, either by processing data locally or by decreasing the temporal granularity of the data sent to the service provider. Furthermore, we identify the participants' lack of understanding and common misconceptions about how the Fitbit ecosystem works.

The article presents the experience of organizing the use of wearable electronic devices (fitness trackers) by schoolchildren to solve the problem of low physical activity. The existing methods of motivating schoolchildren to increase the level of physical activity do not give the desired result. Physical education classes in school cannot compensate for the movement deficit. During extracurricular hours, most schoolchildren also cannot organize their physical activity independently and choose sedentary types of leisure. One way to tackle the problem is to encourage the use of fitness trackers. The use of fitness trackers allows the teacher to monitor the level of physical activity of schoolchildren, analyze the achievements jointly, and help organize the physical activity of schoolchildren outside the classroom. To solve the problem, the authors of the article have developed two experimental programs of supplementary education for schoolchildren with the use of fitness trackers. The first program involves the regular, supervised use of fitness trackers in animation training. The second program includes training assignments for assembling and testing fitness trackers in the course of programming training. The second program showed higher efficiency. For the statistical assessment of the results of the educational programs implementation, the Wilcoxon T-test was used. The implementation of educational programs led to increase of the level of physical activity of students by 7–15 %. The authors give recommendations on the use of fitness trackers in the supplementary education system.

The Internet of Things (IoT) is used to describe a network of physical objects which are connected to each other with the help of embedded sensors, transceivers and software code to communicate and share data with each other. The Internet of Things, which first took shape back in the 1980s through an ARPA-NET connected Coca-Cola Vending machine in Carnegie Mellon University has come a long way since then. In today’s world a growing proportion of new home appliances are coming with IoT features embedded in them. These include, but are not limited to Television Sets, Refrigerators, Microwave Ovens, Fitness trackers, Smart watches and even IoT enabled light bulbs. IoT devices are not only used in Homes but also in Industries where they can play a pivotal role in bringing down operating costs and helping companies make better business decisions to align their companies in the right direction. With the advent of Industrial Internet of Things (IIoT) and Industry 4.0, a new standard has been set that organizations follow to gain a lot of key advantages such as improving productivity, customer experience, driving down costs and taking better informed decisions. IoT devices have also entered the healthcare industry where they play a paramount role in monitoring vital signs of patients. These devices continuously monitor all the vital signs such as heart rate, blood pressure and oxygen saturation.

Background: A self-monitoring approach utilizing fitness trackers that provide feedback regarding physical activities has been recently applied to rehabilitation patients to promote voluntary walking activities. Although this approach has been proven to increase physical activity, it is uncertain whether the intervention improves walking ability.Aim: This review investigated whether the additional self-monitoring approach using activity trackers would improve walking ability in any type of rehabilitation setting.Methods: A systematic search was performed in four databases [PubMed (MEDLINE), The Cochrane Library, SPORTDiscus, and Cumulative Index to Nursing and Allied Health Literature] to identify studies that examined the self-monitoring approach combined with rehabilitative intervention vs. the same rehabilitative intervention only in participants with any unhealthy conditions. Two review authors independently assessed the eligibility of all the retrieved English literature published from 2009 to 2019, then discussed the final inclusion. The risk of bias was assessed referring to the criteria of the Cochrane Risk of Bias tool. The key findings were synthesized using narrative synthesis. In addition, a quantitative synthesis was conducted when more than two studies investigating the same disease were identified.Results: Eleven randomized controlled trials satisfied the eligibility criteria, nine of which had a lower risk of bias. The types of diseases included stroke, chronic obstructive pulmonary disease (COPD), cancer, Parkinson's disease, hemophilia, peripheral artery disease, post-total knee arthroplasty, and geriatric rehabilitation. Eight studies reported measures of walking endurance and four reported measures of gait speed. In the quantitative synthesis of two studies investigating COPD, there was a significant between-group difference in terms of changes in the 6-min walking distance from the baseline, which was favorable to the additional self-monitoring intervention group (mean difference: 13.1 m; 95% confidence interval, 1.8–24.5; 2 studies, 124 participants; p = 0.02; I2 = 0%). Other available data revealed no consistent evidence regarding effectiveness of the intervention.Conclusions: The findings indicate that there is little evidence suggesting the effectiveness of the self-monitoring approach in improving walking ability in rehabilitation settings. However, a weak recommendation for patients with stable COPD was implicated in the quantitative synthesis. Further research would be required to explore the best indications for this self-monitoring approach.Systematic Review Registration: CRD 42020157695.

Background Fitness trackers allow users to collect, manage, track, and monitor fitness-related activities, such as distance walked, calorie intake, sleep quality, and heart rate. Fitness trackers have become increasingly popular in the past decade. One in five Americans use a device or an app to track their fitness-related activities. These devices generate massive and important data that could help physicians make better assessments of their patients’ health if shared with health providers. This ultimately could lead to better health outcomes and perhaps even lower costs for patients. However, sharing personal fitness information with health care providers has drawbacks, mainly related to the risk of privacy loss and information misuse. Objective This study investigates the influence of granting users granular privacy control on their willingness to share fitness information. Methods The study used 270 valid responses collected from Mtrurkers through Amazon Mechanical Turk (MTurk). Participants were randomly assigned to one of two groups. The conceptual model was tested using structural equation modeling (SEM). The dependent variable was the intention to share fitness information. The independent variables were perceived risk, perceived benefits, and trust in the system. Results SEM explained about 60% of the variance in the dependent variable. Three of the four hypotheses were supported. Perceived risk and trust in the system had a significant relationship with the dependent variable, while trust in the system was not significant. Conclusions The findings show that people are willing to share their fitness information if they have granular privacy control. This study has practical and theoretical implications. It integrates communication privacy management (CPM) theory with the privacy calculus model.

AbstractThe paper presents a qualitative study to explore the use of fitness trackers and their social functions in intergenerational settings. The study covered three phases of semi-structured interviews with older and younger adults during individual and intergenerational use of the fitness trackers. The study revealed comparability as common fitness practice for older adults. The findings show that intergenerational fitness tracking practices can increase in-person meetings and daily discourses and thus enhance family social bonds. An unexpected benefit of this practice is its ability to help older adults overcome technology barriers related to the use of fitness trackers. Overall speaking, families whose intergenerational members already enjoy a strong relationship are likely to gain the most from such practices. Many challenges remain especially concerning the motivation and involvement of younger partners and the user experience design aspect of such digital programs. For this purpose, we have developed some recommendations for the future development and deployment of intergenerational fitness tracking systems to stimulate interactions between younger and older family members and thus to promote their physical and emotional well-being.

Technology use for personal health management should not only be assessed in terms of the rate of adoption but also examined in the form of sustained use to ensure the long-term benefit. This study addressed the issue of the continued use of wearable devices by ensuring value co-creation among a user, the wearable device, and other users within a service system. This study was a scenario-based experiment to examine interaction design, including interactivity level and game dynamics, which act as a combination of value co-creation mechanisms to elicit a user’s intentions to continuously use wearables. The study also examined user perception factors, such as self and social perceptions, as moderators. This study contributes to existing literature by using the value co-creation and service system perspective to examine continued use behavior. The findings of the research also offer practical insights into designing the features of wearable fitness trackers to promote long-term value for their users.

Internet of things (IoT) is transforming the way we imagine healthcare with ubiquitous connectivity, faster response and deeper personalized insights using large amounts of data. Fitness trackers provide useful insights to maintain balance of a healthy lifestyle. Nowadays, fitness trackers are available as wearable devices which creates a sense of unease in exercise and may cause skin irritation. In this paper, we present mmFiT, an edge computing enabled, contactless, real-time fitness tracker using a single mmwave radar point cloud data. It has the inherent advantage of user privacy preservation while tracking indoor fitness activities. Experimental results show that the system can classify various exercises with real-time accuracy of 95.53\% and is also capable of counting repetitions of exercises. This implementation is computationally inexpensive, and therefore, the system can be deployed in an IoT connected edge device for real-time operations. This system will be an ideal fit in a smart home or smart gymnasium setting.