Over 35% of adults in the U.S. are obese and another 35% are overweight according to the most recent estimates. Obesity contributes to cardiovascular disease, diabetes, osteoarthritis, and other conditions, leading to an estimated total annual healthcare cost of $190 billion. To date, a larger research focus has been placed on diet, even though physical activity plays an essential role in weight management. Successful obesity prevention and weight management must include physical activity and more fully combine knowledge of physiology and biomechanics with behavioral and social environmental theories to account for the many factors at play.
The promise of mobile technology
Mobile technology is already facilitating chronic disease management in diverse ways. Health tracking apps are increasingly common, particularly as wearable devices gain more wireless sensors to gather data. The promise of such enormous and diverse datasets is unheralded.
Limitations of current commercial applications for promoting physical activity
Many commercial applications geared toward promoting healthy activities, such as physical activity, are available today, but few have been systematically tested for efficacy in different populations, and none have systematically incorporated evidence from the many factors (e.g., activity, diet, and social environment) contributing to successful (or failed) weight management.
Developing personalized interventions for weight management
Given the substantial heterogeneity across the population, our innovative machine learning and pattern matching strategies are needed to identify what “works” for a given individual, both at present and across time.
The Mobilize Center will combine mechanistic knowledge about joint loads and metabolic cost with the large-scale datasets for large and diverse populations to understand how to effectively motivate physical activity in people with varied genders, ethnicities, locations, socioeconomic statuses, and other factors. Specifically, the Mobilize Center will:
- Utilize biomechanical modeling to identify physical activities that maximize metabolic energy expenditure, while minimizing joint loading and muscle-specific fatigue. This knowledge will guide us in the development of safe, effective exercise prescription paradigms for overweight and obese individuals, which we will validate against experimental data.
- Integrate social/behavioral modeling and statistical learning to develop models that describe how intrinsic and extrinsic factors affect decision-making related to weight management, particularly in relation to physical activity.
- Apply this newly acquired knowledge to develop and validate specific apps to promote activity and weight management in collaboration with our industry partners.
The principles and methods we develop in this health application will be applied specifically to the areas of personalized motivation, targeted feedback, and exercise prescription for weight management, but this framework will also be readily extensible to other areas, including encouraging healthy eating, the prevention of osteoporosis and promotion of healthy bone mass, or encouraging activity and limiting functional loss in the aging population.