Fully Funded EPSRC and RCNDE PhD Scholarship: Real Time Tracking of Cognitive Load to Assess Human Factors During Inspections

Funding providers: Engineering and Physical Sciences Research Council (EPSRC) and RCNDE

Subject areas: Human-Computer Interaction, Machine Learning

Project start date: 

• 1 October 2024 (Enrolment open from mid-September)
• 1 January 2025 (Enrolment open from mid-December)

Project description: 

Many industries are relocating workers from hazardous environments to supervisory rooms, where they need to engage with automated systems to perform their work. A critical challenge in human-automated systems interaction lies in effectively managing human factors such as cognitive load (CL) and emotions such as stress to ensure optimal task execution. However, currently, measuring CL involves bulky, expensive techniques such as functional magnetic resonance imaging and magnetoencephalography, limiting their practicality. Recent progress in wearable design helps non-invasively measure CL and stress by synchronously analysing physiological indicators such as Pupillometry, heart-rate variability, and skin conductivity. Regardless, previous work involved wearing eye trackers and heart monitors, which may not be suitable for real-time inspection setups. Besides, the tasks utilised to collect data for estimating CL were superficial and consequently, CL measures were task dependent.  

Thus, there is a clear need to develop less invasive and robust task-independent measures for CL. This need is particularly relevant in non-destructive evaluation (NDE), where automation is increasing, and human factors significantly contribute to uncertainties in inspection results. This project will explore corrective methods to enhance inspection reliability by developing robust measure of CL and correlating it with operator performance. With automated systems generating vast volumes of inspection data and data analysis tasks becoming more complex, addressing human factors becomes increasingly vital for ensuring the overall dependability of inspections. 

Eligibility

Candidates must hold an Upper Second Class (2.1) honours degree or an appropriate master’s degree with a minimum overall grade at ‘Merit’ in Computer Science, Mathematics or a closely related discipline. If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency.

Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations. 

Additional Funding Information

This scholarship covers the full cost of tuition fees and an annual stipend at £19,237.

Additional research expenses will also be available.