Advances for Prosthetic Technology: From Historical Perspective to Current Status to Future Application

This book offers insights into the complexities associated with neurological control of gait and details extrinsic capabilities demonstrating conceptual advancements in prosthetic control. The first edition of this book achieved 15,000 accesses by January 2025. This subsequent edition explores the current advancements in powered transtibial prosthetics. The development of electromyography (EMG) feedback to enhance prosthetic control is thoroughly analyzed. Evolved control architectures and their corresponding components and subsystems in prosthetic technology are concisely summarized. Furthermore, the rapidly advancing patents relevant to powered prosthetics are examined. Lastly, the integration of artificial intelligence (AI) and robotics is discussed, with a focus on their implications for advancements in prosthetic technology. This edition not only delves into the realm of cutting-edge powered prosthetic systems but also addresses the intersection of AI (machine learning) and robotics. It encompasses extrinsic capabilities critical for advanced control in prosthetic technology, appealing not only to those with a vested interest in prosthetic innovations but also to enthusiasts in the fast-evolving fields of AI and robotics.

Dr. Robert LeMoyne presently is an Adjunct Professor for Northern Arizona University for the Department of Biological Sciences and an Adjunct Professor for Czech Technical University in Prague for the Department of Biomedical Technology. Dr. LeMoyne is researching advanced concepts for prosthetic technology, such as machine learning, which is an aspect of artificial intelligence. His Ph.D. in Biomedical Engineering was earned at University of California Los Angeles (UCLA) (2010). He has first authored more than 150 technical proceedings, including six books, which have been cited more than 2000 times, spanning a broad array of subjects, such as an assortment of applications for advanced concepts for prosthetic technology.  

Timothy Mastroianni is a cognitive scientist, researcher, and entrepreneur. He pioneered the non-invasive use of computer vision and pattern recognition to uncover the internal states of random number generators in machines (HiLoClient2002). Mastroianni developed the first model and algorithms capable of predicting a person's thoughts using machine learning and fMRI, presenting these groundbreaking methods at Carnegie Mellon University to map the human brain and identify brain states during specific tasks. He is also the founder of Cognition Engineering, a subsidiary of Cognition International LLC.