Elaboration of a Methodology and its Implementation for Processing Biometric Data to Study Human Performance

In aviation and other industries most incidents and accidents occur due to human error. To improve this it is necessary to understand the operator's behaviour. A methodology to digitalize human performance is applied in training to enrich feedback about fundamental performance aspects.

Key data

Description

To augment human reliability, technologies have been developed that substitute unreliable human actions with automation. This leaves the human operator in the role of a supervisory controller. But supervising a machine is a difficult task for a human as attentional resources are soon depleted so monitoring becomes ineffective and machines are highly reliable so there is little to detect.

In addition, skills erode with lack of practice and may not be sufficiently accessible in case the machine fails. As an alternative, machine monitoring of the human operator and feedback on situation awareness could allow to keep the human operator as an active task manager in the loop, if complexity and task load permit.

With our research endeavour, we intend to provide feedback in training and operational environments to identify and manage human errors and foster individual and organisational learning. This would allow to keep the human operator in this expert role and maintain knowledge and skills necessary to decide and react in situations when automation should fail.

For that purpose, a system that collects and processes biometric and simulator data for the analysis and visualisation of critical performance aspects is developed. In a first step, the system is applied and refined for Evidence-Based Training in aviation. This is a new training paradigm initiated by ICAO (International Civil Aviation Organization) to improve pilots' competencies and resilience. Evaluation of pilots' competencies is supported by objective performance feedback.

With the appropriate technical tools for data collection, integration and analysis instructors and examiners can be supported with objective performance indicators in assessing competencies and with visualisations for debriefing. This can promote trainees' self-reflection on the causes of their performance. In the first instance, this tool is used in pilot training, but it can be extended to other areas.