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BackgroundOver the past few years, the world has witnessed an unprecedented growth in smartphone use. With sensors such as accelerometers and gyroscopes on board, smartphones have the potential to enhance our understanding of health behavior, in particular physical activity or the lack thereof. However, reliable and valid activity measurement using only a smartphone in situ has not been realized.ObjectiveTo examine the validity of the iPod Touch (Apple, Inc.) and particularly to understand the value of using gyroscopes for classifying types of physical activity, with the goal of creating a measurement and feedback system that easily integrates into individuals’ daily living.MethodsWe collected accelerometer and gyroscope data for 16 participants on 13 activities with an iPod Touch, a device that has essentially the same sensors and computing platform as an iPhone. The 13 activities were sitting, walking, jogging, and going upstairs and downstairs at different paces. We extracted time and frequency features, including mean and variance of acceleration and gyroscope on each axis, vector magnitude of acceleration, and fast Fourier transform magnitude for each axis of acceleration. Different classifiers were compared using the Waikato Environment for Knowledge Analysis (WEKA) toolkit, including C4.5 (J48) decision tree, multilayer perception, naive Bayes, logistic, k-nearest neighbor (kNN), and meta-algorithms such as boosting and bagging. The 10-fold cross-validation protocol was used.ResultsOverall, the kNN classifier achieved the best accuracies: 52.3%–79.4% for up and down stair walking, 91.7% for jogging, 90.1%–94.1% for walking on a level ground, and 100% for sitting. A 2-second sliding window size with a 1-second overlap worked the best. Adding gyroscope measurements proved to be more beneficial than relying solely on accelerometer readings for all activities (with improvement ranging from 3.1% to 13.4%).ConclusionsCommon categories of physical activity and sedentary behavior (walking, jogging, and sitting) can be recognized with high accuracies using both the accelerometer and gyroscope onboard the iPod touch or iPhone. This suggests the potential of developing just-in-time classification and feedback tools on smartphones.

Purpose-To investigate associations among adolescent screen time behaviors and screen time rules and electronic media in adolescents' bedrooms.Methods-Parents and adolescents (N = 160 dyads) from Boston, Cincinnati and San Diego completed demographic, screen time rules, availability of media devices, and screen time behavior questions. Separate multiple regression models for adolescent report and parent report tested correlates of adolescent TV watching, video game play, and computer use for entertainment.Results-Data from adolescents indicated that rules for TV, computer use, and total number of screen time rules were significant correlates of time spent watching TV (ß = −.22, p < .01), playing video or computer games (ß = −.18, p < .05), and using the internet/computer for entertainment (ß = −.18, p < .05), respectively. Data from parents indicated that TV rules were significantly associated with lower TV viewing, and parent/adolescent agreement on rules strengthened this relationship. Both parent and adolescent data indicated that having a TV in the bedroom was positively associated with TV viewing time (ß = .18 and .24, p < .05, respectively). Adolescent data indicated a positive association between having at least one video game system in the bedroom with time spent playing video games (ß = .19, p < .05).Conclusion-Having clear rules, setting limits on screen time, and not having screen-based media in the bedroom were associated with fewer hours of screen time for adolescents.

Characterizing COVID-19 and Influenza Illnesses in the Real World via Person-Generated Health Data Highlights d We use data from smartphones and wearables from~7,000 people to compare flu and COVID-19 d While symptoms have some overlap, patients report longer COVID-19 illnesses than flu d Elevated resting heart rate measures are more frequent around illness symptoms onset d It is important to consider flu as a confounder in COVID-19 real-world studies

Exergames are video games that use exertion-based interfaces to promote physical activity, fitness, and gross motor skill development. The purpose of this paper is to describe the development of an organizing framework based on principles of learning theory to classify and rank exergames according to embedded behavior change principles. Behavioral contingencies represent a key theory-based game design principle that can be objectively measured, evaluated, and manipulated to help explain and change the frequency and duration of game play. Case examples are presented that demonstrate how to code dimensions of behavior, consequences of behavior, and antecedents of behavior. Our framework may be used to identify game principles which, in the future, might be used to predict which games are most likely to promote adoption and maintenance of leisure time physical activity.