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Full-Text Articles in Medicine and Health Sciences
Characterizing The Performance And Behaviors Of Runners Using Twitter, Qian He, Emmanuel Agu, Diane Strong, Bengisu Tulu, Peder Pedersen
Characterizing The Performance And Behaviors Of Runners Using Twitter, Qian He, Emmanuel Agu, Diane Strong, Bengisu Tulu, Peder Pedersen
Emmanuel O. Agu
Running is a popular physical activity that improves physical and mental wellbeing. Unfortunately, up-to- date information about runners’ performance and psychological wellbeing is limited. Many questions remain unanswered, such as how far and how fast runners typically run, their preferred running times and frequencies, how long new runners persist before dropping out, and what factors cause runners to quit. Without hard data, establishing patterns of runner behavior and mitigating the challenges they face are difficult. Collecting data manually from large numbers of runners for research studies is costly and time consuming. Emerging Social Networking Services (SNS) and fitness tracking devices …
Detection Of Diabetic Foot Ulcers Using Svm Based Classification, Lei Wang, Peder Pedersen, Diane Strong, Bengisu Tulu, Emmanuel Agu, Qian He, Ronald Ignotz, Raymond Dunn, David Harlan, Sherry Pagoto
Detection Of Diabetic Foot Ulcers Using Svm Based Classification, Lei Wang, Peder Pedersen, Diane Strong, Bengisu Tulu, Emmanuel Agu, Qian He, Ronald Ignotz, Raymond Dunn, David Harlan, Sherry Pagoto
Emmanuel O. Agu
Diabetic foot ulcers represent a significant health issue, for both patients’ quality of life and healthcare system costs. Currently, wound care is mainly based on visual assessment of wound size, which suffers from lack of accuracy and consistency. Hence, a more quantitative and computer-based method is needed. Supervised machine learning based object recognition is an attractive option, using training sample images with boundaries labeled by experienced clinicians. We use forty sample images collected from the UMASS Wound Clinic by tracking 8 subjects over 6 months with a smartphone camera. To maintain a consistent imaging environment and facilitate the capture process …
A Context-Aware Activity Recommendation Smartphone Application To Mitigate Sedentary Lifestyles, Qian He, Emmanuel Agu
A Context-Aware Activity Recommendation Smartphone Application To Mitigate Sedentary Lifestyles, Qian He, Emmanuel Agu
Emmanuel O. Agu
A sedentary lifestyle involves irregular or no physical activity. In this kind of lifestyle, people’s activities do not increase their energy expenditure substantially above resting levels. Long periods of sitting, lying, watching television, playing video games, and using the computer are typical examples. Energy expenditures at 1.0-1.5 Metabolic Equivalent Units (METs) are considered sedentary behaviors. A recent study of sedentary lifestyles found that the length of sedentary times is associated with an increased risk of diabetes, cardiovascular disease, and cardiovascular and all-cause mortality. In this study, we developed a smartphone application called “On11”, which continuously tracks and informs the user …