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3. Human-Centered Intelligent Training for Emergency Responders

Author

Mehta, Ranjana K., Moats, Jason, Karthikeyan, Rohith, Gabbard, Joseph L., Srinivasan, Divya, Du, Eric Jing, Leonessa, Alexander, Burks, Garret, Stephenson, Andrew, and Fernandes, Ron

Subjects
Artificial Intelligence, feedback, neural mechanisms
Abstract

Emergency response (ER) workers perform extremely demanding physical and cognitive tasks that can result in serious injuries and loss of life. Human augmentation technologies have the potential to enhance physical and cognitive work-capacities, thereby dramatically transforming the landscape of ER work, reducing injury risk, improving ER, as well as helping attract and retain skilled ER workers. This opportunity has been significantly hindered by the lack of high-quality training for ER workers that effectively integrates innovative and intelligent augmentation solutions. Hence, new ER learning environments are needed that are adaptive, affordable, accessible, and continually available for reskilling the ER workforce as technological capabilities continue to improve. This article presents the research considerations in the design and integration of use-inspired exoskeletons and augmented reality technologies in ER processes and the identification of unique cognitive and motor learning needs of each of these technologies in context-independent and ER-relevant scenarios. We propose a human-centered artificial intelligence (AI) enabled training framework for these technologies in ER. Finally, how these human-centered training requirements for nascent technologies are integrated in an intelligent tutoring system that delivers across tiered access levels, covering the range of virtual, to mixed, to physical reality environments, is discussed. Published version

Published
2022

8. Effect of Mechanical Properties on the Dynamics of Self-Oscillating Synthetic Vocal Folds.

Author

Burks, Garret, Singh, Manjot, De Vita, Raffaella, Johnson, Blake, and Leonessa, Alexander

Subjects
*VOCAL cords, *MECHANICAL behavior of materials, *POISSON'S ratio, *SILICONE rubber, *MECHANICAL models, *ELECTROMAGNETS
Abstract

This study focuses on the measured changes in dynamic behavior exhibited by eight synthetic vocal fold models with varying mechanical properties. Uniaxial tensile testing was conducted to determine changes in mechanical properties between materials made from silicone rubber and polydimethylsiloxane with varying mixing ratios. The results of the mechanical testing showed that the elastic modulus, E, varied from 20.6 to 437.4 kPa, the measured Poisson ratios, ν, spanned the range of 0.43-0.48, and the density, ρVF⁠, varied from 0.86 to 1.02 g/cm³ across the eight samples. Vocal fold models were dynamically tested using a custom-built experimental setup that supplied a heated and humidified airflow to the synthetic vocal folds. The resulting sounds were recorded and analyzed to identify the change in fundamental frequency which spanned 66.8 to 342.6 Hz across the eight samples. In addition, a mathematical aeroelastic model of phonation was implemented to further investigate the relationship between the mechanical properties and phonation frequency. Finally, a proof-of-concept magnetic actuation method was demonstrated using magnetic elastomers to deform the synthetic vocal folds through the use of an electromagnet. [ABSTRACT FROM AUTHOR]

Published
2021
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