System Design-Basal Metabolic Rate Calculator Outstanding Scholars Research Project
Standing
Undergraduate
Type of Proposal
Oral Presentation
Faculty
Faculty of Engineering
Faculty Sponsor
Dr. R. J. Urbanic
Proposal
Present-day obesity has become an international epidemic. The process of permanently losing body fat/improving body composition is complex and often intimidating; but it is a critical step that must be taken to reduce obesity. It would be expected that resources available to the public to guide weight loss would be made simple-to-follow and as accurate as possible, however, this is not the case. Almost all resources made available to the general public are very generic and inaccurate-starting right from the initial estimations of variables such as body composition (lean vs. fat mass) and overall DEE (daily energy expenditure). Inaccuracy in these estimations will inevitably cause the user to be misguided-resulting in high failure and quitting rates. The purpose of this project is multi-fold-the main objective is to create an accurately-predictive weight loss application to better assist self-driven weight loss attempts. In the first phase of the project, a flow diagram and VBA-driven system was developed that allows a user to input more detailed information to better predict initial body composition data. Currently, the validity of this model is being tested through experiment work. The pilot study was conducted on four participants of varying age, gender and activity level; and actual values for body fat percentage and DEE were found using the BOD POD and Body Media arm band equipment in the Human Kinetics Department. These actual values were compared to several values computed using various formulas found online and in the literature. Conclusions were made about the accuracy of methods based on initial conditions and these findings serve as a basis for further experiment work. These findings will be considered to improve the current system. After the experiment work is finished, the weight loss phase and real-time decision support system will be researched, developed and tested. It is hopeful that these models and systems can be brought to the public through a mobile application to help reduce obesity.
Grand Challenges
Viable, Healthy and Safe Communities
Special Considerations
n/a
System Design-Basal Metabolic Rate Calculator Outstanding Scholars Research Project
Present-day obesity has become an international epidemic. The process of permanently losing body fat/improving body composition is complex and often intimidating; but it is a critical step that must be taken to reduce obesity. It would be expected that resources available to the public to guide weight loss would be made simple-to-follow and as accurate as possible, however, this is not the case. Almost all resources made available to the general public are very generic and inaccurate-starting right from the initial estimations of variables such as body composition (lean vs. fat mass) and overall DEE (daily energy expenditure). Inaccuracy in these estimations will inevitably cause the user to be misguided-resulting in high failure and quitting rates. The purpose of this project is multi-fold-the main objective is to create an accurately-predictive weight loss application to better assist self-driven weight loss attempts. In the first phase of the project, a flow diagram and VBA-driven system was developed that allows a user to input more detailed information to better predict initial body composition data. Currently, the validity of this model is being tested through experiment work. The pilot study was conducted on four participants of varying age, gender and activity level; and actual values for body fat percentage and DEE were found using the BOD POD and Body Media arm band equipment in the Human Kinetics Department. These actual values were compared to several values computed using various formulas found online and in the literature. Conclusions were made about the accuracy of methods based on initial conditions and these findings serve as a basis for further experiment work. These findings will be considered to improve the current system. After the experiment work is finished, the weight loss phase and real-time decision support system will be researched, developed and tested. It is hopeful that these models and systems can be brought to the public through a mobile application to help reduce obesity.