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• Conference paper
  Li Y, Wang M, Young IA, Stewart R, Nissen Bet al., 2026,

  Holding MenstaRay: Expressing Menstrual Pain through Tactile and Knitted Soft Robotic Interactions

  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.

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• Conference paper
  Herron MT, Kohler M, Nieri T, Spinelli DS, Canesi I, Kutz Z, Greinke B, Stewart Ret al., 2026,

  Tear-able to Wearable: Exploring End-of-Life Pathways for E-Textiles

  Electronic textiles (e-textiles) represent a growing area in HCI, yet their end-of-life remains largely underexplored, leaving no established pathways for addressing this emerging waste stream. This study represents the first step in an ongoing research program exploring recycling possibilities for e-textiles. This work examines the post-disassembly potential of conductive textile substrates to explore whether these materials retain functional value and if they can be reintegrated into new interactive systems. Using commercially available conductive woven fabrics, we apply mechanical recycling techniques adapted from traditional textile processing to produce new nonwoven materials suitable for medium-pressure, low-resolution piezoresistive sensing. Through electromechanical characterization, we identify both the opportunities and limitations of this approach.

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• Conference paper
  Wang M, Li Y, Nissen B, Stewart Ret al., 2026,

  MenstaRay: A Knitted Soft Wearable Robotic Interface for Somatosensory Communication of Menstrual Experience

  , Pages: 902-906

  MenstaRay is a soft knit robotic interface designed to explore how tactile actuation can support somatosensory communication of menstrual experiences. The prototype was created using a fabrication method for knit-integrated soft wearable robotics with two core structural elements: (1) an extensible EcoFlex 00-10 silicone cavity containing internal air chambers and (2) a strain-limiting textile layer knitted with Spandex Super Stretch Yarn (81% nylon, 19% elastane). This configuration enables regulated inflation patterns that preserve the softness of textiles while providing targeted haptic feedback that is suitable for intimate, safe, and therapeutically appropriate interactions. Through a series of workshops, we investigated and evaluated how these dynamic tactile behaviours shaped participants’ embodied reflections on menstrual sensations. This work contributes to human robotic interaction by introducing MenstaRay, a novel artifact coupled with textile-integrated actuation that can externalize intimate bodily sensations and foster new modes of communicating, reflecting on and representing menstrual experiences through wearable interfaces.

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• Journal article
  Pope VC, Stewart R, Chew E, 2026,

  Timing structures in live comedy: A matched-sequence approach to mapping performance dynamics.

  , PNAS Nexus, Vol: 5

  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.

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• Conference paper
  Zhou B, Liu M, Bian S, Geiβler D, Lukowicz P, Miranda J, Dan J, Atienza D, Riahi MA, Wehn N, Torah R, Yong S, Liu J, Beeby S, Kohler M, Greinke B, Yu J, Nierstrasz V, Sheldrick L, Stewart R, Nieri T, Maccanti M, Spinelli Det al., 2025,

  Multi-partner project: Sustainable Textile Electronics (STELEC)

  , DATE 2025, Publisher: IEEE, Pages: 1-5

  E-textiles are rapidly emerging as an important area of electronic circuit applications. It also facilitates many socially important applications such as personalized health, elderly care, and smart agriculture. However, the environmental impact and sustainability of e-textiles remain very problematic. STELEC, short for Sustainable Textile ELECtronics, is an interdisciplinary research project funded by the European Innovation Council (EIC) under the Pathfinder programme on the responsible elec-tronics topic seeking cutting-edge innovation. STELEC started in September 2024 and is in its initial stage. 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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• Journal article
  Zhou Y, Sun Y, Li Y, Shen C, Lou Z, Min X, Stewart Ret al., 2024,

  A highly durable and UV‐resistant graphene‐based knitted textile sensing sleeve for human joint angle monitoring and gesture differentiation

  , Advanced Intelligent Systems, Vol: 6, ISSN: 2640-4567

  Flexible strain sensors based on textiles have attracted extensive attention owing to their light weight, flexibility, and comfort when wearing. However, challenges in integrating textile strain sensors into wearable sensing devices include the need for outstanding sensing performance, long-term monitoring stability, and fast, convenient integration processes to achieve comprehensive monitoring. The scalable fabrication technique presented here addresses these challenges by incorporating customizable graphene-based sensing networks into knitted structures, thus creating sensing sleeves for precise motion detection and differentiation. The performance and real-world application potential of the sensing sleeve are evaluated by its precision in angle estimation and complex joint motion recognition during intra- and intersubject studies. For intra-subject analysis, the sensing sleeve only exhibits a 2.34° angle error in five different knee activities among 20 participants, and the sensing sleeves show up to 94.1% and 96.1% accuracy in the gesture classification of knee and elbow, respectively. For inter-subject analysis, the sensing sleeve demonstrates a 4.21° angle error, and it shows up to 79.9% and 85.5% accuracy in the gesture classification of knee and elbow, respectively. An activity-guided user interface compatible with the sensing sleeves for human motion monitoring in home healthcare applications is presented to illustrate the potential applications.

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• Journal article
  Lou Z, Min X, Li G, Avery J, Stewart Ret al., 2024,

  Advancing sensing resolution of impedance hand gesture recognition devices

  , IEEE Journal of Biomedical and Health Informatics, Vol: 28, Pages: 5855-5864, ISSN: 2168-2194

  Gestures are composed of motion information (e.g. movements of fingers) and force information (e.g. the force exerted on fingers when interacting with other objects). Current hand gesture recognition solutions such as cameras and strain sensors primarily focus on correlating hand gestures with motion information and force information is seldom addressed. Here we propose a bio-impedance wearable that can recognize hand gestures utilizing both motion information and force information. Compared with previous impedance-based gesture recognition devices that can only recognize a few multi-degrees-of-freedom gestures, the proposed device can recognize 6 single-degree-of-freedom gestures and 20 multiple-degrees-of-freedom gestures, including 8 gestures in 2 force levels. The device uses textile electrodes, is benchmarked over a selected frequency spectrum, and uses a new drive pattern. Experimental results show that 179 kHz achieves the highest signal-to-noise ratio (SNR) and reveals the most distinct features. By analyzing the 49,920 samples from 6 participants, the device is demonstrated to have an average recognition accuracy of 98.96%. As a comparison, the medical electrodes achieved an accuracy of 98.05%.

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• Conference paper
  Wang M, Zhou Y, Stewart R, 2024,

  Soft wearable robotics: innovative knitting-integrated approaches for pneumatic actuators design

  , DIS '24: Designing Interactive Systems Conference, Publisher: ACM, Pages: 234-238

  Soft wearable robotics presents an opportunity to bridge robotics and textiles, offering lightweight, flexible, and ergonomic solutions for human-robot interaction, but previous studies on wearable soft robotics primarily focus on actuator performance without also considering wearability and interactivity. A rudimentary attachment method is usually adopted using external fixation devices such as straps to attach actuators to the user’s body, resulting in a poor wearing experience. This study focus on compatible and compact textile architectures to support actuators to be seamlessly integrated into daily wearing. It presents a research-through-design method to propose innovative knitting-integrated approaches for pneumatic actuator design to provide soft wearable robots with both aesthetic and functional values. Through a series of tests in which various knitting techniques and parameters are used to create sleeves that house silicone actuators, it explores design possibilities and understands the complex relationships between textiles and actuators. The findings contribute to advancing soft wearable robotics by offering practical solutions for integrating pneumatic actuators seamlessly into wearable textiles, thereby unlocking new possibilities for human-centered robotic systems.

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• Conference paper
  Li Y, Zhou Y, Shen C, Stewart Ret al., 2024,

  E-textile sleeve with graphene strain sensors for arm gesture classification of mid-air interactions

  , TEI '24: Eighteenth International Conference on Tangible, Embedded, and Embodied Interaction, Publisher: ACM, Pages: 1-10

  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.

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• Conference paper
  Dave RJ, Min X, Lou Z, Stewart Ret al., 2024,

  Investigating construction and integration techniques of dry silver-based textile electrodes on electromyography of biceps Brachii muscle

  , 5th International Conference on the Challenges, Opportunities, Innovations and Applications in Electronic Textiles, Publisher: MDPI, ISSN: 2673-4591

  This research paper recommends an electrode construction and integration technique for dry silver-based textile electrodes capturing electromyographic (EMG) signals. Three integration methods with two different conductive textiles were compared using two analysis methods; analysis was also conducted before and after six washing cycles. Six wearable arm bands with each of the design parameter combinations were worn on the biceps brachii muscle to capture EMG signals from three users under a controlled task both before any washing of the bands occurred and after four washing cycles were completed. Additionally, impedance measurements over six frequency bands were recorded after each washing cycle. Textile electrodes made of Shieldex Techniktex P180B using an extended electrode integration method were found to perform best.

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