In this section
Our research centres around the body and how technology can be used to improve how that body exists and interacts with the surrounding environment. We focus on haptic and aural modalities, using textiles as the physical medium for building wearable computational systems. Some of the research projects we undertake focus exclusively on textile sensing and interfaces whilst other focus solely on how auditory displays can be improved for users. A growing area of our work is looking towards how these two complementary technologies can be brought together in novel applications.
Below is a selection of projects grouped by theme of work:
Utilising novel textiles or electronic integrations to track and measure different forms of motion directly through fabric interventions.
Investigating next-generation haptic outputs embedded within textiles, with the unique ability to provide localised bodily sensations and tactile effects currently unavailable from other technologies.
Utilising novel textiles or electronic integrations to track and measure different forms of motion directly through fabric interventions.
Utilising novel textiles or electronic integrations to track and measure different forms of motion directly through fabric interventions.
The most developed strand of research in the group is tracking human motion through textile sensors. SensiKnit was developed by Dr Yi (Joy) Zhou during her PhD. SensiKnit is a graphene-based wearable monitoring system. The ergonomic sensors, crafted with digital knitting and laser-cutting, ensure close skin contact for accurate data collection and allow a full range of motion for user comfort. Integrated into wearables, SensiKnit can monitor body movements, such as knee bends and arm gestures, making it ideal for exercise interfaces and injury rehabilitation. Resistant to UV rays and washing, it offers consistent, real-time activity feedback under any condition.
This work has been published in Advanced intelligent Systems (Zhou, Y., Sun, Y., Li, Y., Shen, C., Lou, Z., Min, X. and Stewart, R. (2024), A Highly Durable and UV-Resistant Graphene-Based Knitted Textile Sensing Sleeve for Human Joint Angle Monitoring and Gesture Differentiation. Adv. Intell. Syst. 2400124. https://doi.org/10.1002/aisy.202400124).
The video was filmed and produced by Xiannuo Phoenix Zhao (Xcellent Productions Ltd).
@article{Pope:2026:pnasnexus/pgaf394,
author = {Pope, VC and Stewart, R and Chew, E},
doi = {pnasnexus/pgaf394},
journal = {PNAS Nexus},
title = {Timing structures in live comedy: A matched-sequence approach to mapping performance dynamics.},
url = {http://dx.doi.org/10.1093/pnasnexus/pgaf394},
volume = {5},
year = {2026}
}
TY - JOUR
AB - Live performance is a ubiquitous cultural and social behavior that has not yet benefited from systematic scientific study. We present a computational methodology that visualizes and describes timing structures in live performance, showcasing their engineering. This novel analysis framework, Topology Analysis of Matching Sequences (TAMS), automatically detects matching sequences and maps their timing. Locating material that is repeated across performances reveals the skill behind apparently effortless communication between performer and audience. Applying TAMS to two stand-up comedy tours uncovered structural features at the macro- and microlevels, including consistently placed novel material at the beginning of shows and sections dedicated to tightly timed repeated material. TAMS also provides a new frame of reference for examining audience-performer dynamics through speech microtiming and laughter. TAMS can be applied to other forms of repeated speech, such as political stump speeches, as well as extended to other types of performance, such as dance.
AU - Pope,VC
AU - Stewart,R
AU - Chew,E
DO - pnasnexus/pgaf394
PY - 2026///
TI - Timing structures in live comedy: A matched-sequence approach to mapping performance dynamics.
T2 - PNAS Nexus
UR - http://dx.doi.org/10.1093/pnasnexus/pgaf394
UR - https://www.ncbi.nlm.nih.gov/pubmed/41567929
VL - 5
ER -