Applied Biomechatronics Using Mathematical Models

Applied Biomechatronics Using Mathematical Models provides an appropriate methodology to detect and measure diseases and injuries relating to human kinematics and kinetics. It features mathematical models that, when applied to engineering principles and techniques in the medical field, can be used in assistive devices that work with bodily signals. The use of data in the kinematics and kinetics analysis of the human body, including musculoskeletal kinetics and joints and their relationship to the central nervous system (CNS) is covered, helping users understand how the complex network of symbiotic systems in the skeletal and muscular system work together to allow movement controlled by the CNS.
With the use of appropriate electronic sensors at specific areas connected to bio-instruments, we can obtain enough information to create a mathematical model for assistive devices by analyzing the kinematics and kinetics of the human body. The mathematical models developed in this book can provide more effective devices for use in aiding and improving the function of the body in relation to a variety of injuries and diseases.

• Focuses on the mathematical modeling of human kinematics and kinetics
• Teaches users how to obtain faster results with these mathematical models
• Includes a companion website with additional content that presents MATLAB examples

Dr. Garza-Ulloa has focused his research in the development of mathematical models for Electrical and Computer Engineering: Biomedical applications, such as his Mathematical Model for the Validation of the Ground Reaction Force Sensor in Human Gait Analysis, the Mathematical model to predict Transition-to-Fatigue during isometric exercise on muscles of the lower extremities, and his mathematical model to be used in the Assessment and evaluation of dynamic behavior of muscles with special reference to subjects with Diabetes Mellitus. Dr. Garza-Ulloa also conducts research in Sensor Validation using Computational Intelligence, to detect common factors that cause low reliability of the acquired data. Dr. Garza-Ulloa has been the recipient of numerous honors and awards including a University of Texas at El Paso Graduate School Research Award, Richard Schellenger Foundation, and funds for his research from Stern Foundation. He has founded three international technologies consultant companies and been leader in developing new specialized electronic manufacturing equipment to improve production.