Themes of Work

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 an non-exhaustive list of some of the research we have undertaken.

Current EU Funded Projects

SONICOM

SONICOM is a research project that aims to revolutionise the way we interact socially within augmented and virtual reality (AR/VR) environments and applications, from online meetings to VR gaming.

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STELEC

STELEC, short for Sustainable Textile ELECtronics, is an interdisciplinary research project funded by the European Innovation Council (EIC) under the Pathfinder programmes in the responsible electronics topic seeking cutting-edge innovation with an end goal at TRL 2-3. The project is a multinational collaboration of research institutes, universities and companies across Europe. It aims at developing next generation textile-based electronics in applications from sensing, processing to AI, with a commitment to full lifecycle sustainability.

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Citation

BibTex format

@inproceedings{Li:2024:10.1145/3623509.3633374,
author = {Li, Y and Zhou, Y and Shen, C and Stewart, R},
doi = {10.1145/3623509.3633374},
pages = {1--10},
publisher = {ACM},
title = {E-textile sleeve with graphene strain sensors for arm gesture classification of mid-air interactions},
url = {http://dx.doi.org/10.1145/3623509.3633374},
year = {2024}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Arm gestures play a pivotal role in facilitating natural mid-air interactions. While computer vision techniques aim to detect these gestures, they encounter obstacles like obfuscation and lighting conditions. Alternatively, wearable devices have leveraged interactive textiles to recognize arm gestures. However, these methods predominantly emphasize textile deformation-based interactions, like twisting or grasping the sleeve, rather than tracking the natural body movement.This study bridges this gap by introducing an e-textile sleeve system that integrates multiple ultra-sensitive graphene e-textile strain sensors in an arrangement that captures bending and twisting along with an inertia measurement unit into a sports sleeve. This paper documents a comprehensive overview of the sensor design, fabrication process, seamless interconnection method, and detachable hardware implementation that allows for reconfiguring the processing unit to other body parts. A user study with ten participants demonstrated that the system could classify six different fundamental arm gestures with over 90% accuracy.
AU  - Li,Y
AU  - Zhou,Y
AU  - Shen,C
AU  - Stewart,R
DO  - 10.1145/3623509.3633374
EP  - 10
PB  - ACM
PY  - 2024///
SP  - 1
TI  - E-textile sleeve with graphene strain sensors for arm gesture classification of mid-air interactions
UR  - http://dx.doi.org/10.1145/3623509.3633374
UR  - http://0.0.0.26/
ER  -
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