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).
@inproceedings{Li:2026:10.1145/3772318.3790839,
author = {Li, Y and Wang, M and Young, IA and Stewart, R and Nissen, B},
doi = {10.1145/3772318.3790839},
title = {Holding MenstaRay: Expressing Menstrual Pain through Tactile and Knitted Soft Robotic Interactions},
url = {http://dx.doi.org/10.1145/3772318.3790839},
year = {2026}
}
TY - CPAPER
AB - Menstrual pain is an embodied, unpredictable, and diverse lived experience. However, current menstrual tracking technologies mainly adopt medicalised and quantitative approaches, reducing pain to numerical data, concealing its organic and messy nature. To uncover the felt, lived experience of pain, we explored soft robotics as a tactile, dynamic medium. Through a series of material workshops, we designed MenstaRay, a novel artefact that mimics the temporality and fluctuations of menstrual pain. Findings from sensory interactions with MenstaRay show that soft robotic materials sensitise and enhance menstruators' bodily awareness, supporting them in contextually recalling, introspecting, and reflecting on their pain experiences, and encouraging a sense of self-care, self-acceptance, and companionship toward menstrual pain. We frame MenstaRay's dynamic entanglements with fluid bodily experiences as a meaningful material practice through a feminist lens, highlighting the creative potential of novel programmable interactions of knitted soft robotics to express nuanced pain characteristics, extending to other somatic experience design beyond menstruation.
AU - Li,Y
AU - Wang,M
AU - Young,IA
AU - Stewart,R
AU - Nissen,B
DO - 10.1145/3772318.3790839
PY - 2026///
TI - Holding MenstaRay: Expressing Menstrual Pain through Tactile and Knitted Soft Robotic Interactions
UR - http://dx.doi.org/10.1145/3772318.3790839
ER -