Wearable and Wireless Systems for Healthcare I

Wearable and wireless systems for gait analysis and reflex quantification.- Traditional clinical evaluation of gait and reflex response by ordinal scale.- Quantification systems appropriate for a clinical setting.- The rise of inertial measurement units.- Portable wearable and wireless systems for gait and reflex response quantification.- Smartphones and portable media devices as wearable and wireless systems for gait and reflex response quantification.- Bluetooth inertial sensors for gait and reflex response quantification with perspectives regarding Cloud Computing and the Internet of Things.- Quantifying the spatial position representation of gait through sensor fusion.- Role of machine learning for gait and reflex response classification.- Homebound therapy with wearable and wireless systems.- Future perspective of Network Centric Therapy.- Evolutions for Wearable and Wireless Systems.- Gait Analysis with Advanced Wearable and Wireless Systems.- New Developments in Homebound Therapy Enabled Through Wearable and Wireless Systems.- New Quantifiable Exercise with Wearable and Wireless Systems.- Deep Learning and Neuromorphic Applications for Classifying Health Status Using Wearable and Wireless Systems.- Future Perspectives for Wearable and Wireless Systems for Healthcare.

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.