Big Data Analytics for Resilience Assessment and Development in Tactical Training Serious Games

Training activities utilising virtual reality environments are being used increasingly to create training scenarios to promote resilience for mental and physical wellbeing and to enable repeatable scenarios to allow trainees to learn techniques for various stressors. However, assessment of the trainees' response to these training activities has either been limited to various pre and post training assessment metrics or collected in parallel during experiments and analysed retrospectively. We have created a Big Data analytics platform, Athena, that in real-time acquires data from a first person shooter game, ArmA 3, as well as the data ArmA 3 sends to the muscle stimulation component of a multisensory garment, ARAIG that provides on the body feedback to the wearer for communications, weapon fire and being hit and integrates that data with physiological response data such as heart rate, breathing behaviour and blood oxygen saturation. This paper presents a method to create structured resilience training scenarios that incorporate Big Data analytics for resilience analytics for new approaches for resilience assessment and development in tactical training serious games.