Wearable and Wireless Systems for Healthcare I: Gait and Reflex Response Quantification (Smart Sensors, Measurement and Instrumentation, 47, Band 47)

This book is the second edition of the one originally published in 2017. The original publication features the discovery of numerous novel applications for the use of smartphones and portable media devices for the quantification of gait, reflex response, and an assortment of other concepts that constitute first-in-the-world applications for these devices. Since the first edition, numerous evolutions involving the domain of wearable and wireless systems for healthcare have transpired warranting the publication of the second edition.

This volume covers wearable and wireless systems for healthcare that are far more oriented to the unique requirements of the biomedical domain. The paradigm-shifting new wearables have been successfully applied to gait analysis, homebound therapy, and quantifiable exercise. Additionally, the confluence of wearable and wireless systems for healthcare with deep learning and neuromorphic applications for classification is addressed. The authors expect that these significant developments make this book valuable for all readers.

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 wearable and wireless systems, such as for the domain of gait, reflex response, movement disorders, and therapeutic interventions. 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 four books, which have been cited more than 2000 times, spanning a broad array of subjects, such as the rampant assortment of applications for wearable and wireless systems.

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.