IPAB Workshop-23/11/2023

Speaker: David Hanley

Title: The Tradeoff Between Spatial Resolution and High Curvature Bending in Fibre Bragg Grating-Based Shape Sensing.

Abstract: Fiber Bragg grating (FBG)-based shape sensing is an emerging technology used for the navigation of flexible medical instruments, such as needles, catheters, and endoscopes. FBG-based sensors operate by measuring strain induced wavelength shifts in the reflected light, which are used to determine the curvature along a fibre’s length. While an increased number of gratings enhances shape-sensing accuracy, incorporating many within a fixed spectrum can induce interference in wavelength shifts, specifically during high curvature bending, limiting the detectable bending range. Such interference severely compromises shape estimation, posing challenges for instruments requiring high curvature bends. In this talk, this tradeoff between resolution and bending curvature will be explained. Next, an algorithm that leverages the reflectivity and full-width half maximum of FBG nodes for improved bend estimation, even in high-curvature scenarios, will be introduced. We will end by covering some work in-progress and next steps in shape estimation. 

Speaker: Longfei Chen

Title: Monitor Weakness of Individuals Living Alone at Home Using a Camera.

Abstract: With ageing and chronic health conditions significantly affecting the daily lives of older adults, the early detection of developing health conditions is crucial. This study focuses on monitoring behavioural changes related to physical weakness in individuals using a non-intrusive camera sensor. Weakness often accompanies many prevalent health conditions and can lead to alterations in physical movements and daily activities. However, detecting such changes can be challenging due to their subtle and gradual nature. To address this challenge, we employ a camera sensor to monitor individuals' common daily sitting activities for signs of weakness. The system captures fine-grained features related to body motion, inactivity, and environmental context in real time while prioritizing privacy. Bayesian Networks and other classifiers are used to analyse the relationships between features, activities, and health conditions. The study aims to identify specific features and activities that significantly indicate such changes and determine the most suitable time scale for observing the change.