  As part of a perennial project, our team is actively engaged in developing
new synthetic assistant (SA) technologies to assist in training combat medics
and medical first responders. It is critical that medical first responders are
well trained to deal with emergencies more effectively. This would require
real-time monitoring and feedback for each trainee. Therefore, we introduced a
voice-based SA to augment the training process of medical first responders and
enhance their performance in the field. The potential benefits of SAs include a
reduction in training costs and enhanced monitoring mechanisms. Despite the
increased usage of voice-based personal assistants (PAs) in day-to-day life,
the associated effects are commonly neglected for a study of human factors.
Therefore, this paper focuses on performance analysis of the developed
voice-based SA in emergency care provider training for a selected emergency
treatment scenario. The research discussed in this paper follows design science
in developing proposed technology; at length, we discussed architecture and
development and presented working results of voice-based SA. The empirical
testing was conducted on two groups as user studies using statistical analysis
tools, one trained with conventional methods and the other with the help of SA.
The statistical results demonstrated the amplification in training efficacy and
performance of medical responders powered by SA. Furthermore, the paper also
discusses the accuracy and time of task execution (t) and concludes with the
guidelines for resolving the identified problems.

Computers and Society;Artificial Intelligence;Human-Computer Interaction;Systems and Control;Systems and Control