Projects

Center members are engaged in several research projects with major funding from the National Science Foundation. This page will showcase three projects. For other member projects see respective pages.

Reproducibility in simulation­-based prediction of natural knee mechanics

CSU PI: Jason Halloran; Lead PI: Ahmet Erdemir (Cleveland Clinic)
National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (Grant No. R01EB024573). 2017-2021

This project aims for understanding the influence of modelers’ approaches and decisions (essentially their art) throughout the lifecycle of modeling and simulation. Across five separate groups with knee modeling expertise, it will demonstrate the uncertainty of delivering consistent simulation predictions when the founding data to feed into models remain the same.

Project Website

Optimal Prosthesis Design with Energy Regeneration

PI: Dan Simon; co-PIs: Hanz Richter and Ton van den Bogert
NSF Smart and Connected Health Grant 1344954, 2013-2017

The goals of this research are three-fold: (1) To develop new approaches for the simulation of human limb control; (2) To develop new approaches for optimizing prosthetic limb control, capture energy during walking, and store that energy to lengthen useful prosthesis life; and (3) To develop a prosthesis prototype. In order to accomplish these high-level goals, the following specific objectives will be pursued: (1) Study both able-bodied gait and amputee gait in our human motion lab; (2) Develop mathematical models for human motion control to provide a foundation for artificial limb control; (3) Develop electronic prosthesis controls; (4) Develop new approaches for optimizing prosthesis design parameters based on computer intelligence; (5) Fabricate a prosthesis prototype and test the prototype in a robotic system; (6) Conduct human trials of the prosthesis prototype.

Project Website

Cyber-Enabled Exercise Machines

PI: Hanz Richter; co-PIs: Dan Simon, Ken Sparks and Ton van den Bogert
NSF Cyber-Physical Systems Grant 1544702, 2015-2019

This research will contribute to the foundations of cyber-physical system science in the following aspects: biomechanical modeling and real-time musculoskeletal state estimation; estimation theory and unscented H-infinity estimation; control theory and human-machine interaction dynamics, and micro-evolutionary optimization for real-time systems. The proposed Cyber-Enabled Exercise Machines (CEEMs) are highly reconfigurable devices which adapt to the user in pursuit of an optimization objective, namely maximal activation of target muscle groups. Machine adaptation occurs through port impedance modulation, and optimal cues are generated for the exerciser to follow. The goals of the project are threefold: i) development of foundational cyber-physical science and technology in the field of human-machine systems; ii) development of new approaches to modeling, design, control and optimization of advanced exercise machines, and iii) application of the above results to develop two custom-built CEEMs: a rowing ergometer and a 2-degree-of-freedom resistance machine.

Project Website

Safe Patient Handling among STNAs in Nursing Homes: Compliance, Monitoring, and Continuous Quality Improvement of Best Practices

PI: Glenn Goodman; co-PIs: Beth Ekelman, Joan Niederriter, Debbie Espy, Anne Reinthal and Wenbing Zhao
Ohio Bureau of Workers’ Compensation, 2015-2017

Lost productivity from lower back injuries in workplaces costs billions of US dollars per year. A significant fraction of such workplace injuries are the result of workers not following best practices. Previous studies have shown that a multifaceted approach would have to be used to improve the situation. Hence, in this project, we are integrating body mechanics training and a technology-based real-time intervention solution to reduce workplace injuries. As part of this project, Dr. Zhao has developed a novel computer-vision based system to track the activities of consented workers using the depth sensors, alert them on detection of non-compliant activities, and produce cumulative reports on their performance. Essentially, the system provides a valuable set of services for both workers and administrators towards a healthier, and therefore, more productive workplace.