Researchers use machine learning to predict exercise adherence
Sticking to an exercise routine is a challenge many people face. But a University of Mississippi research team is using machine learning to uncover what keeps individuals committed to their workouts. The team -- Seungbak Lee and Ju-Pil Choe, both doctoral students in physical education, and Minsoo Kang, professor of sport analytics in the Department of Health, Exercise Science and Recreation Management -- hopes to predict whether a person is meeting physical activity guidelines based on their body measurements, demographics and lifestyle. They have examined data from about 30,000 surveys. To quickly sort through such a huge data set, they've turned to machine learning, a way of using computers to identify patterns and make predictions based on the information. The group's results, published in the Nature Portfolio journal Scientific Reports are timely, Kang said "Physical activity…
