Textile-based wearable sensors for assisting sports performance

There is a need for wearable sensors to assess physiological signals and body kinematics during exercise. Such sensors need to be straightforward to use, and ideally the complete system integrated fully within a garment. This would allow wearers to monitor their progress as they undergo an exercise training programme without the need to attach external devices. This takes physiological monitoring into a more natural setting. By developing textile sensors the intelligence is integrated into a sports garment in an innocuous manner. A number of textile based sensors are presented here that have been integrated into garments for various sports applications

Conductive Yarn Embroidered Circuits for System on Textiles

With the recent convergence of electronics and textile technology, various kinds of smart wearables are being developed, such as heating clothes, health monitoring clothes, and motion sensing clothes. In this study, the novel conductive embroidery yarns for touch sensing and signal transmission for system on textile (SoT) are introduced. The conductive yarn for touch sensing can be used as a user interface of smart clothes by constructing an embroidery circuit. The conductive yarn for signal transmission can be embroidered on smart clothing and used as a transmission line to transmit power and signal. The conductive yarns and their embroidered circuits were characterized and SoT prototypes using the embroidered circuit of these conductive yarns were presented. These e-textiles based on touch sensing and signal transmission can be comfortably applied for SoT and maintain electrical performance without being damaged by tensile force generated by the movement of the wearer

New generation of wearable goniometers for motion capture systems

Background Monitoring joint angles through wearable systems enables human posture and gesture to be reconstructed as a support for physical rehabilitation both in clinics and at the patient's home. A new generation of wearable goniometers based on knitted piezoresistive fabric (KPF) technology is presented. Methods KPF single-and double-layer devices were designed and characterized under stretching and bending to work as strain sensors and goniometers. The theoretical working principle and the derived electromechanical model, previously proved for carbon elastomer sensors, were generalized to KPF. The devices were used to correlate angles and piezoresistive fabric behaviour, to highlight the differences in terms of performance between the single layer and the double layer sensors. A fast calibration procedure is also proposed. Results The proposed device was tested both in static and dynamic conditions in comparison with standard electrogoniometers and inertial measurement units respectively. KPF goniometer capabilities in angle detection were experimentally proved and a discussion of the device measurement errors of is provided. The paper concludes with an analysis of sensor accuracy and hysteresis reduction in particular configurations. Conclusions Double layer KPF goniometers showed a promising performance in terms of angle measurements both in quasi-static and dynamic working mode for velocities typical of human movement. A further approach consisting of a combination of multiple sensors to increase accuracy via sensor fusion technique has been presented

A Multi-Modal Sensing Glove for Human Manual-Interaction Studies

We present an integrated sensing glove that combines two of the most visionary wearable sensing technologies to provide both hand posture sensing and tactile pressure sensing in a unique, lightweight, and stretchable device. Namely, hand posture reconstruction employs Knitted Piezoresistive Fabrics that allows us to measure bending. From only five of these sensors (one for each finger) the full hand pose of a 19 degrees of freedom (DOF) hand model is reconstructed leveraging optimal sensor placement and estimation techniques. To this end, we exploit a-priori information of synergistic coordination patterns in grasping tasks. Tactile sensing employs a piezoresistive fabric allowing us to measure normal forces in more than 50 taxels spread over the palmar surface of the glove. We describe both sensing technologies, report on the software integration of both modalities, and describe a preliminary evaluation experiment analyzing hand postures and force patterns during grasping. Results of the reconstruction are promising and encourage us to push further our approach with potential applications in neuroscience, virtual reality, robotics and tele-operation

Smart Fabric sensors for foot motion monitoring

Smart Fabrics or fabrics that have the characteristics of sensors are a wide and emerging field of study. This thesis summarizes an investigation into the development of fabric sensors for use in sensorized socks that can be used to gather real time information about the foot such as gait features. Conventional technologies usually provide 2D information about the foot. Sensorized socks are able to provide angular data in which foot angles are correlated to the output from the sensor enabling 3D monitoring of foot position. Current angle detection mechanisms are mainly heavy and cumbersome; the sensorized socks are not only portable but also non-invasive to the subject who wears them. The incorporation of wireless features into the sensorized socks enabled a remote monitoring of the foot

Comparison of E-Textile Techniques and Materials for 3D Gesture Sensor with Boosted Electrode Design

[EN] There is an interest in new wearable solutions that can be directly worn on the curved human body or integrated into daily objects. Textiles offer properties that are suitable to be used as holders for electronics or sensors components. Many sensing technologies have been explored considering textiles substrates in combination with conductive materials in the last years. In this work, a novel solution of a gesture recognition touchless sensor is implemented with satisfactory results. Moreover, three manufacturing techniques have been considered as alternatives: screen-printing with conductive ink, embroidery with conductive thread and thermosealing with conductive fabric. The main critical parameters have been analyzed for each prototype including the sensitivity of the sensor, which is an important and specific parameter of this type of sensor. In addition, user validation has been performed, testing several gestures with different subjects. During the tests carried out, flick gestures obtained detection rates from 79% to 89% on average. Finally, in order to evaluate the stability and strength of the solutions, some tests have been performed to assess environmental variations and washability deteriorations. The obtained results are satisfactory regarding temperature and humidity variations. The washability tests revealed that, except for the screen-printing prototype, the sensors can be washed with minimum degradation.This work was supported by the Spanish Government/FEDER funds (RTI2018-100910-B-C43) (MINECO/FEDER). The work presented is also funded by the Conselleria d'Economia Sostenible, Sectors Productius i Treball, through IVACE (Instituto Valenciano de Competitividad Empresarial) and cofounded by ERDF funding from the EU. Application No.: IMAMCI/2020/1Ferri Pascual, J.; Llinares Llopis, R.; Martinez, G.; Lidon-Roger, JV.; Garcia-Breijo, E. (2020). Comparison of E-Textile Techniques and Materials for 3D Gesture Sensor with Boosted Electrode Design. Sensors. 20(8):1-19. https://doi.org/10.3390/s20082369S11920

A review of contemporary techniques for measuring ergonomic wear comfort of protective and sport clothing

Protective and sport clothing is governed by protection requirements, performance, and comfort of the user. The comfort and impact performance of protective and sport clothing are typically subjectively measured, and this is a multifactorial and dynamic process. The aim of this review paper is to review the contemporary methodologies and approaches for measuring ergonomic wear comfort, including objective and subjective techniques. Special emphasis is given to the discussion of different methods, such as objective techniques, subjective techniques, and a combination of techniques, as well as a new biomechanical approach called modeling of skin. Literature indicates that there are four main techniques to measure wear comfort: subjective evaluation, objective measurements, a combination of subjective and objective techniques, and computer modeling of human–textile interaction. In objective measurement methods, the repeatability of results is excellent, and quantified results are obtained, but in some cases, such quantified results are quite different from the real perception of human comfort. Studies indicate that subjective analysis of comfort is less reliable than objective analysis because human subjects vary among themselves. Therefore, it can be concluded that a combination of objective and subjective measuring techniques could be the valid approach to model the comfort of textile materials

A Weft Knit Data Glove

Rehabilitation of stoke survivors can be expedited by employing an exoskeleton. The exercises are designed such that both hands move in synergy. In this regard often motion capture data from the healthy hand is used to derive control behaviour for the exoskeleton. Therefore, data gloves can provide a low-cost solution for the motion capture of the joints in the hand. However, current data gloves are bulky, inaccurate or inconsistent. These disadvantages are inherited because the conventional design of a glove involves an external attachment that degrades overtime and causes inaccuracies. This paper presents a weft knit data glove whose sensors and support structure are manufactured in the same fabrication process thus removing the need for an external attachment. The glove is made by knitting multifilament conductive yarn and an elastomeric yarn using WholeGarment technology. Furthermore, we present a detailed electromechanical model of the sensors alongside its experimental validation. Additionally, the reliability of the glove is verified experimentally. Lastly, machine learning algorithms are implemented for classifying the posture of hand on the basis of sensor data histograms

A Flexible Strain Sensor Based on a Conductive Polymer Composite for in situ Measurement of Parachute Canopy Deformation

A sensor based on a Conductive Polymer Composite (CPC), fully compatible with a textile substrate and its general properties, has been developed in our laboratory, and its electromechanical characterization is presented herein. In particular the effects of strain rate (from 10 to 1,000 mm/min) and of repeated elongation cycles on the sensor behaviour are investigated. The results show that strain rate seems to have little influence on sensor response. When submitted to repeated tensile cycles, the CPC sensor is able to detect accurately fabric deformations over each whole cycle, taking into account the mechanical behaviour of the textile substrate. Complementary information is given concerning the non-effect of aging on the global resistivity of the CPC sensor. Finally, our sensor was tested on a parachute canopy during a real drop test: the canopy fabric deformation during the critical inflation phase was successfully measured, and was found to be less than 9%