On Track: Seeing Engineering as Sociotechnical using Fitness Trackers

Author(s):  
Susan M. Lord ◽  
Laura A. Gelles
Keyword(s):  
2021 ◽  
Vol 13 (13) ◽  
pp. 7017
Author(s):  
Inje Cho ◽  
Kyriaki Kaplanidou ◽  
Shintaro Sato

Recently, gamified wearable fitness trackers have received greater attention and usage among sport consumers. Although a moderate amount of aerobic physical activity can significantly reduce the risk of many serious illnesses, physical inactivity issues are still prominent. Although wearable fitness trackers have the potential to contribute to physical activity engagement and sustainable health outcomes, there are dwindling engagement and discontinuance issues. Thus, examining its gamification elements and role in physical activity becomes critical. This study examined the gamification elements in wearable fitness trackers and their role in physical activity and sports engagement. A comprehensive literature review yielded 26 articles that empirically measured a variety of gamification features and the effect of the device on physical activity and sports engagement. The study suggests three key gamification themes: goal-based, social-based, and rewards-based gamification that can be a point of interest for future scholars and practitioners. Based on the review, we propose a conceptual framework that embraces motivational affordances and engagement in physical activity and sports.


Author(s):  
Junqing Xie ◽  
Dong Wen ◽  
Lizhong Liang ◽  
Yuxi Jia ◽  
Li Gao ◽  
...  

BACKGROUND Wearable devices have attracted much attention from the market in recent years for their fitness monitoring and other health-related metrics; however, the accuracy of fitness tracking results still plays a major role in health promotion. OBJECTIVE The aim of this study was to evaluate the accuracy of a host of latest wearable devices in measuring fitness-related indicators under various seminatural activities. METHODS A total of 44 healthy subjects were recruited, and each subject was asked to simultaneously wear 6 devices (Apple Watch 2, Samsung Gear S3, Jawbone Up3, Fitbit Surge, Huawei Talk Band B3, and Xiaomi Mi Band 2) and 2 smartphone apps (Dongdong and Ledongli) to measure five major health indicators (heart rate, number of steps, distance, energy consumption, and sleep duration) under various activity states (resting, walking, running, cycling, and sleeping), which were then compared with the gold standard (manual measurements of the heart rate, number of steps, distance, and sleep, and energy consumption through oxygen consumption) and calculated to determine their respective mean absolute percentage errors (MAPEs). RESULTS Wearable devices had a rather high measurement accuracy with respect to heart rate, number of steps, distance, and sleep duration, with a MAPE of approximately 0.10, whereas poor measurement accuracy was observed for energy consumption (calories), indicated by a MAPE of up to 0.44. The measurements varied for the same indicator measured by different fitness trackers. The variation in measurement of the number of steps was the highest (Apple Watch 2: 0.42; Dongdong: 0.01), whereas it was the lowest for heart rate (Samsung Gear S3: 0.34; Xiaomi Mi Band 2: 0.12). Measurements differed insignificantly for the same indicator measured under different states of activity; the MAPE of distance and energy measurements were in the range of 0.08 to 0.17 and 0.41 to 0.48, respectively. Overall, the Samsung Gear S3 performed the best for the measurement of heart rate under the resting state (MAPE of 0.04), whereas Dongdong performed the best for the measurement of the number of steps under the walking state (MAPE of 0.01). Fitbit Surge performed the best for distance measurement under the cycling state (MAPE of 0.04), and Huawei Talk Band B3 performed the best for energy consumption measurement under the walking state (MAPE of 0.17). CONCLUSIONS At present, mainstream devices are able to reliably measure heart rate, number of steps, distance, and sleep duration, which can be used as effective health evaluation indicators, but the measurement accuracy of energy consumption is still inadequate. Fitness trackers of different brands vary with regard to measurement of indicators and are all affected by the activity state, which indicates that manufacturers of fitness trackers need to improve their algorithms for different activity states.


2021 ◽  
Author(s):  
Magdalena Jachymek ◽  
Michał Tomasz Jachymek ◽  
Radosław Marek Kiedrowicz ◽  
Jarosław Kaźmierczak ◽  
Małgorzata Peregud-Pogorzelska

BACKGROUND Recent advances in mobile sensor technology have led to increased popularity of wrist-worn fitness trackers. The possibility to use a smartwatch as a rehabilitation tool to monitor patients’ heart rate during exercise has won the attention of many researchers. OBJECTIVE The aim of the study was to evaluate the accuracy and precision of HR measurement performed by two wrist monitors: Fitbit Charge 4 (Fitbit) and Xiaomi Mi Band 5 (Xiaomi). METHODS 31 healthy volunteers were asked to perform a stress test on a treadmill. During the test their heart rate was recorded simultaneously by both wristbands and ECG at 1minute intervals. The mean absolute error percentage (MAPE), Lin’s concordance correlation coefficient (LCCC) and Bland-Altman were calculated to compare precision and accuracy of heart rate measurements. The estimated validation criteria were MAPE < 10% and LCCC < .8 RESULTS The overall MAPE of the Fitbit device was 10.19% (±11.79%) and the MAPE of Xiaomi was (6.89 % ± 9.75). LCCC of Fitbit HR measurements was .753 (95% CI:0.717-0.785) and of Xiaomi – .903 (0.886-0.917). In both devices the precision and accuracy were decreasing with the increasing exercise intensity. Age, sex, height, weight, BMI did not influence the accuracy of both devices. CONCLUSIONS The accuracy of a wearable wrist-worn heart rate monitor varies and depends on the intensity of training. The decision concerning the application of such a device as a monitor during in-home rehabilitation should be taken with caution, as it may prove not reliable enough.


Author(s):  
Michael Schwartz ◽  
Paul Oppold ◽  
P. A. Hancock

Prior research has reported that novelty affects the usage cycle of wearable devices. This chapter investigates the effects of sensation seeking, intensity, novelty, gender, and prior experience on the workload experienced during one aspect of using wearable fitness trackers, the device installation process. Contrary to the authors' hypotheses, prior experience, sensation seeking, intensity, and novelty did not significantly affect workload. The findings suggest that males tend to experience less workload during the setup of wearable fitness trackers; however, only for the Basis B1 and only for some aspects of workload. The claims made by prior research may be limited to specific aspects of the wearable fitness tracker use cycle, and more investigation is needed before broader claims can be made.


2020 ◽  
Vol 6 ◽  
pp. 205520761990005 ◽  
Author(s):  
Zakkoyya H. Lewis ◽  
Lauren Pritting ◽  
Anton-Luigi Picazo ◽  
Milagro JeanMarie-Tucker

2019 ◽  
Vol 17 (1/2) ◽  
pp. 132-138 ◽  
Author(s):  
Constantine Gidaris

This paper examines the relationship between interactive life insurance companies and their policyholders and the way in which wearable fitness devices are deployed by these companies as data-generating surveillance technologies instead of personal health and fitness devices. Working within an expanded framework of “surveillance capitalism” (Zuboff 2015), I argue that while the notion of self-care generally associated with wearable fitness devices is underpinned by neoliberal constructs, the incentivization of interactive life insurance programs works to obscure the immense value placed on information capital. This paper briefly considers the legal loopholes involved in the harvesting of sensitive health and fitness information from consumer wearables and suggests that the push toward fitness trackers has little to do with any real concerns for the health and fitness of consumers and policyholders. Lastly, I consider different forms of unwaged labour in the relationship between policyholders and interactive life insurance programs. I contend that policyholders do not recognise the free and immaterial labour that goes into sustaining the data-based business model that interactive life insurance companies and social media platforms use and rely on for profit. In so doing, they relinquish power and control over the data they work to produce, only so that the information can be commodified and used against them.


2016 ◽  
Vol 15 (2) ◽  
pp. 447-459 ◽  
Author(s):  
Mahmudur Rahman ◽  
Bogdan Carbunar ◽  
Umut Topkara
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document