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Self-Care
Published in Christopher Langer, Mindful Safety, 2021
Perhaps no one quite anticipated how much technology could reduce our lives to a set of numbers. Smartphones and activity trackers can measure all manner of things: steps taken, floors climbed, kilometres walked, time spent sitting down, heart rate and calories burned, to name a few. You’d be forgiven for thinking the quantified self is the whole self, and nothing but the self. It is not, of course, but the ability to track our every move enables effective goal setting and progress tracking. Electronic notifications and alerts can sometimes be a rude interruption in our working lives. However, when we are discreetly reminded to stretch our legs after a period of staring at our screens, the technology seems to have our best interests at heart. We can take a quick break and return to work feeling refreshed. Productivity goes up, as does the generation of creative ideas.
Emerging Methods for Patient Ergonomics
Published in Richard J. Holden, Rupa S. Valdez, The Patient Factor, 2021
Mustafa Ozkaynak, Laurie Lovett Novak, Yong K. Choi, Rohit Ashok Khot
Sleep self-management strategies that incorporate sensors have the potential to empower patients to track and improve their sleep quality. With the uptake of smartphone ownership, Depose have been developed that utilize embedded sensors in a smartphone to self-monitor activity levels and visualize sleep patterns. Such apps often instruct a user to connect the phone to the charger and place it on the sleeping surface or under the pillow to passively collect data. Using the data, the sleep tracking apps can provide information on sleep patterns (e.g., bedtime, wakeup time, and average time in bed). Additionally, consumer-grade wearable devices such as wrist-worn activity trackers and smart watches also provide users with estimates of sleep-related parameters using proprietary algorithms, including the amount of time in light, deep, and rapid eye movement stage of sleep (Choi et al., 2018). The wearables can collect biometric parameters such as heart rate and blood pressure and potentially provide more detailed estimates than smartphone sensor-based apps. However, sleep estimates generated by wearable devices are under scrutiny for inaccuracy and cannot be used as a substitute for data collected by polysomnography in a sleep lab (Haghayegh et al., 2019). The limitations of wrist-worn sensors also include limited battery life and discomfort of wearing the device during sleep. Despite the shortcomings, consumer-grade IoT sensors provide simple and economical means to longer-term sleep monitoring.
Why Do People Abandon Activity Trackers? The Role of User Diversity in Discontinued Use
Published in International Journal of Human–Computer Interaction, 2023
Christiane Attig, Thomas Franke
Wearable activity trackers (i.e., fitness trackers or smartwatches) are increasingly widely used devices for monitoring various personal activities, fitness, and health parameters (e.g., step count, heart rate, energy expenditure, sleep cycles). Because of their broad functionality, they are used by different user groups with individualized goals. For instance, athletes use activity trackers to check their training progress and customize their workout routine (Wiesner et al., 2018) or people with many sedentary activities use activity trackers to enhance their everyday movement (Alley et al., 2016). The latter group might profit especially from activity tracker use (Chandrasekaran et al., 2020), as pronounced sedentary behavior is associated with poorer metabolic and cardiovascular health (Owen et al., 2010; Warren et al., 2010). Even moderate physical exercise such as walking is associated with increased fitness and cardiovascular health (Murphy et al., 2007). However, for substantial and sustained health effects to manifest, regular physical exercise is necessary (Wei et al., 2015).
Health on the move—can we keep up? Activity tracker performance test to measure data and strategic skills
Published in International Journal of Human–Computer Interaction, 2022
Pia S. de Boer, Alexander J. A. M. van Deursen, Thomas J. L. van Rompay
The Internet of Things is a system in which ubiquitous everyday “smart” devices gather and analyze data about their environment, share these data with both users and other devices, and make autonomous decisions based on algorithms (Van Deursen & Mossberger, 2018). An important application domain is health, wherein smart devices provide users with insights into current health conditions and support health-related decision making (Islam et al., 2015; Miorandi et al., 2012). A common smart device in the health domain is the activity tracker. Activity trackers continuously gather data on user activity (e.g., by measuring the number of steps, distance covered, and stairs climbed), on the intensity of activity (e.g., by measuring heartrate and calculating the number of calories burned), and on recovery from activity (e.g., by measuring sleep duration and phases). Collected data are used for setting or adjusting goals related to behavior change (e.g., improving one’s physical condition), or for improved self-understanding motivated by curiosity or fascination with numbers (Rooksby et al., 2014).
Factors associated with validity of consumer-oriented wearable physical activity trackers: a meta-analysis
Published in Journal of Medical Engineering & Technology, 2021
Willie Leung, Layne Case, Jaehun Jung, Joonkoo Yun
In sum, there are many existing devices available to the public that are not included in the analysis. Manufacturers are constantly producing new devices with more functions and desirable features. Many consumer-oriented wearable physical activity trackers, for example, have become waterproof or water-resistant, enabling people to track physical activity levels during water activities. With more functions, however, the validity and accuracy in measuring physical activity metrics may also be changing and is not guaranteed based on previous versions. There is a need for future studies to investigate the validity of these newer consumer-orientated wearable physical activity trackers and continually validate updated versions of popular trackers. In addition to the various brands of devices, further investigations should be conducted regarding the placement of devices and activity types. There may be a need for additional algorithms in determining the types of activities before determining the amount of energy burned, as seen in a research-oriented accelerometry [69].