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As part of a perennial project, our team is actively engaged in developingnew synthetic assistant (SA) technologies to assist in training combat medicsand medical first responders. It is critical that medical first responders arewell trained to deal with emergencies more effectively. This would requirereal-time monitoring and feedback for each trainee. Therefore, we introduced avoice-based SA to augment the training process of medical first responders andenhance their performance in the field. The potential benefits of SAs include areduction in training costs and enhanced monitoring mechanisms. Despite theincreased 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 developedvoice-based SA in emergency care provider training for a selected emergencytreatment scenario. The research discussed in this paper follows design sciencein developing proposed technology; at length, we discussed architecture anddevelopment and presented working results of voice-based SA. The empiricaltesting was conducted on two groups as user studies using statistical analysistools, one trained with conventional methods and the other with the help of SA.The statistical results demonstrated the amplification in training efficacy andperformance of medical responders powered by SA. Furthermore, the paper alsodiscusses the accuracy and time of task execution (t) and concludes with theguidelines for resolving the identified problems.

Effects of Voice-Based Synthetic Assistant on Performance of Emergency Care Provider in Training