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Wearable materials and devices are developing toward flexibility， lightness， imperceptibility， intelligence， and long-term wearability to meet the personalized needs such as physiological and psychological demands of human body. This trend brought innovation to the field of sports and health monitoring， receiving extensive attention from the academic and industrial communities. However， while meeting the individualized development needs of the human body， wearable flexible materials and devices also face challenges in terms of mechanical robustness， signal stability， soft-hard interface connection， and biocompatibility. Therefore， this review aims to discuss the materials， structures， and fabrication processes for constructing wearable flexible materials and devices from the perspective of practical sports and health monitoring needs，and proposes the major challenging factors and their solutions in terms of mechanical， electrical， and biological performance. Finally， this paper predicts the future development directions of wearable flexible electronic materials and devices， including fully flexible integration， enhanced mechanical robustness， high-precision signal decoupling and recognition， stability，and sensitivity of monitoring， rapid responsiveness， ultra-thin imperceptible design， multimodal signal processing， as well as intelligent adaptive feedback.

BackgroundPhysical inactivity is a risk factor for chronic noncommunicable diseases. Insufficient physical activity has become an important public health problem worldwide. As mobile apps have rapidly developed, physical activity apps have the potential to improve the level of physical activity among populations. ObjectiveThis study aimed to evaluate the effect of physical activity apps on levels of physical activity among college students. MethodsA Web-based questionnaire was used to survey college students in Beijing from December 27, 2017, to January 5, 2018. According to a previous survey, 43% of college students using physical activity apps and 36% of those who never used such apps achieved the physical activity recommendations. In this study, the sample size was calculated to be 500. The questionnaire consisted of 5 parts: the use of physical activity apps, sports habits, social support, self-efficacy, and social demographic information. Structural equation modeling was used to test the relationships between the use of physical activity apps, self-efficacy, social support, and level of physical activity. ResultsOf the 1245 participants, 384 college students (30.8%) used physical activity apps (in the past month). Of these 384 students, 191 (49.7%) gained new friends via the app. College students who were using physical activity apps had a higher level of physical activity and higher scores for social support and self-efficacy (P