PhD in Related Subjects

Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided. Overview Falls are one of the most serious safety risks for older adults, and rapid, reliable detection can significantly reduce long-term injury and improve emergency response. Building on recent advances in vibration-based sensing, this PhD will explore how the structural and material characteristics of floor systems influence the vibration signatures produced by human falls and other everyday activities. While existing research often assumes a single, uniform floor condition, real buildings vary widely, from timber and composite systems to reinforced concrete slabs, each with unique stiffness, damping, and boundary conditions. These structural differences fundamentally shape how vibration signals are transmitted and recorded. This project will therefore investigate how these variations affect signal detectability and classification performance of AI models for fall detection. The research will combine experimental studies on different floor systems, finite element simulations of vibration propagation, and AI-based signal analysis to establish a physics-informed understanding of the relationship between structural behaviour and fall detection accuracy.