Flood management and media production planning are both tasks that require timely and sound decision making, as well as effective collaboration between professionals in a team split between remote headquarter operators and in situ actors. This paper presents an extended reality (XR) platform that utilizes interactive and immersive technologies and integrates artificial intelligence (AI) algorithms to support the professionals and the public involved in such incidents and events. The developed XR tools address various specialized end-user needs of different target groups and are fueled by modules that intelligently collect, analyze, and link data from heterogeneous sources while considering user-generated content. This platform was tested in a flood-prone area and in a documentary planning scenario, where it was used to create immersive and interactive experiences. The findings demonstrate that it increases situation awareness and improves the overall performance of the professionals involved. The proposed XR system represents an innovative technological approach for tackling the challenges of flood management and media production, one that also has the potential to be applied in other fields.

In this paper we describe the xR4DRAMA system, a solution that makes use of XR capabilities to support professionals who deal with disasters, man-made crises or media productions. The key contribution of this work in progress is the increase of situation awareness, which is achieved by the innovative combination of data collection, multimedia and sensor analysis, linking data, GIS and interactive XR technologies. The proposed platform is designed to facilitate the creation of immersive environments using semantically enriched content and comprises a powerful tool that is applicable to multiple real use case scenarios.

This paper describes a study performed in the frame of Wearables project and reports preliminary results. Objective of the study was the implementation of an integrated service finalized to increase employees' well-being through the investigation on the correlation between daily working activity and the observed physical parameters. The project monitored 28 volunteers employed in the field of waste collection (at the Amey's contract with Wolverhampton City Council), for a total of 275 data acquisition sessions. The study has been performed using sensing textiles, to collect objective work-correlated parameters during daily activity, aiming at the acquisition of objective indicators for an improved wellbeing. Physical parameters like heart rate, energy expenditure and heart rate activity-zones distribution have been evaluated from data acquired during normal working activity. The service produced encouraging results both in terms of monitoring individual subjects and in identifying trends correlated to different roles or tasks covered by workers. Also in term of usability and acceptability the system showed interesting potentialities, proving how wearable technologies can trigger innovative approaches and open new prospective in the growing field of workplace wellness.

This paper describes a study performed in the frame of WEARABLES project and reports about preliminary analysis of the results on the activity, HR and breathing rate distribution. Objective of the study was the monitoring of employees' well-being finalized at the investigation on the correlation between daily working activity and the observed physical parameters. The study has been performed by using sensing textiles, to collect objective work-correlated parameters during daily activity aiming at the acquisition of objective indicators for an improved management of people within teams. Scope of the project was to monitor a sample of 28 volunteers in environmental service delivery (at the Amey's contract with Wolverhampton City Council), for a period of two non-consecutive weeks per volunteer, with a total of 275 data acquisition sessions.

Here we investigate the feasibility of textile based piezoresistive sensors to accurately measure increases in spinal extension, on-body for clinical application in the Modified Modified Schober's test. The proposed sensor combines the accuracy of standard metallic strain sensors with the comfort and usability of textiles, offering innumerable wearable applications. Calibration testing of the textile sensors showed a linear dependency between sensor's electrical resistance and strain in the region of interest (25-60% strain) with great reproducibility (relative standard deviation 0.0296-2.04%, n=10). On-body testing of the device has shown accurate results validated by standard measurements done with a steel measuring tape, proving the viability of the sensor for real-time monitoring of spinal extension.

Wearable sensors have the potential to provide new methods of non-invasive physiological measurement in real-time. This work presents an alternative to the current clinical measurement of spinal flexion; the modified Schober’s test. The accuracy of the test is determined by each clinician, which causes a large tendency towards error [1]. By implementing a strain sensor as an alternative to the measuring tape currently used, it is proposed that inter-observer error would be reduced and more consistent measurements would be provided over time. Herein, two types of textile based sensors were tested for use in this application; a knitted spandex cylindrical structure with integrated carbon nanotubes (CNT) and a flat, knitted piezoresistive fabric (KPF) knitted with Lycra® [2]. Of each type, numerous samples were fabricated with varying length, width, core size, tension and knit direction. Each sensor was tested for resistance changes versus strain in the laboratory where it was clear that KPF sensors knit under high tension provided accurate and reproducible electrical properties. All varieties of CNT sensors showed inconsistent resistance measurements over time, rendering them unsuitable for use of such precise measurements. After calibration, it is proposed that these sensors can be easily integrated into a wearable device to be used in a clinical setting.

Wearable sensors have the potential to enable continuous real-time health monitoring of people during normal daily activities. In contrast, the current paradigm requires patients to devote a period of time to attend for tests in specialist facilities and under conditions that, at best, are not representative of their normal life patterns, and at worst, may induce considerable stress, leading to significantly biased data. Physical therapy, training technique, rehabilitation, respiration monitoring and diagnostics could all be improved by implementing wearable sensors and data acquisition software. This will not only improve the accuracy of the measurements, but the ability to analyze the data over time.

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.

This paper presents a kinesthetic glove realized with knitted piezoresistive fabric (KPF) sensor technology. The glove forefinger area is sensorized by two KPF goniometers obtained on the same piezoresistive substrate. The piezoresistive textile is used for the realization of both electrogoniometers and connections, thus avoiding mechanical constraints due to metallic wires. Sensors are characterized in comparison with commercial goniometers. The glove behavior is pointed out in terms of methacarpal-phalangeal and interphalangeal joint movement reconstruction.

Research and development in smart wearable systems for personalized services, especially for monitoring purposes, has significantly increased worldwide. Electronic textiles (e-textiles) are relevant promoters of technological progress for sectors like biomonitoring, rehabilitation, telemedicine, teleassistance, and sport medicine. The integration of biosensors into clothes enables daily physiological monitoring through a continuous and personalized detection of vital signs, while garments with strain- and stress-sensing capabilities enable tracking of posture and gestures of the subject. The e-textile systems comprise fabric electrodes and sensors capable of capturing bioelectrical and biomechanical signals like electrocardiogram, electromyogram, respiration, bioimpedance, skin conductivity, and sweat characteristics. This chapter begins with a detailed description of the technology for the design and the implementation of sensing textiles, starting from the fiber and ending with the final textile configuration in the garment. Several types of textile sensors for biomonitoring are described, and several examples of smart fabric and textile platforms developed for healthcare applications are reported.

This work focus on the characterization of piezoresistive fabric sensors, realized with conductive yarns that are similar in term of conductive components, but different only in term of geometry, the yarns have been realized according two different production processes while the sensors have been produced following the same process, fabric structure and same materials. The different geometry of the yarns affects dramatically conductivity and functionality of the sensors in term of sensitivity and hysteresis minimization. This result confirms that the functional components can be engineered during the different phases of the process production; to get new properties and new applications. Small changes at fibers level can be fundamental to improve the properties of the fabric sensors.

Since birth the first and the most natural interface for the body is fabric, a soft, warm and reassuring material. Cloth is usually covering more than 80 % of the skin; which leads us to consider textile material as the most appropriate interface where new sensorial and interactive functions can be implemented. The new generation of personalised monitoring systems is based on this paradigm: functions like sensing, transmission and elaboration are implementable in the materials through the textile technology. Functional yarns and fibres are usable to realise garments where electrical and computing properties are combined with the traditional mechanical characteristics, giving rise to textile platforms that are comparable with the cloths that are normally used to produce our garments. The feel of the fabric is the same, but the functionality is augmented. Nowadays, consumers demand user-friendly connectivity and interactivity; sensing clothes are the most natural and ordinary interface able to follow us, everywhere in a non-intrusive way, in natural harmony with our body.

This paper focus on SFIT platforms for rehabilitations and FES therapy. Two systems will be described, one developed to support patients during motor therapy, when they are still hospitalized, and after discharge, at home; the other is a sleeve integrating multi-electrodes patches, designed to allow FES therapy and EMG acquisition for patients affected by tremor. These examples prove that it is possible to combine fabric electrodes and biomechanical textile sensors to conceive systems where gesture recognition function can be combined with EMG detection and FES capability. These platforms can be easily used at home for daily therapy, as well as for telemedicine services.

In this paper is presented the study leading to the implementation of an innovative sensing textile platform, based on a wearable monitoring system named Wealthy, where novel piezoresistive sensors have been integrated to increase system capability in the field of pulmonary and cardiovascular diseases monitoring. Two different typologies of textile sensors for plethysmograpic measurements have been characterized and compared to evaluate sensors performance, through electro-dynamic laboratory tests and in vivo measurements. The whole system allows continuous remote monitoring of electrocardiogram and impedance pneumography signals through textile electrodes, while piezoresistive fabric sensors placed at the abdominal and thoracic level are able to discriminate between different breathing patterns. All the signals have been acquired simultaneously allowing a comparative control of cardiopulmonary activity and artifact rejection, while a comparative study with standard BIOPAC® MP30 respiratory transducers has been performed in basal condition.

Within the European integrated project "Proetex" (FP6-2004-IST-4-026987) three different wearable systems are under development to monitor physiological signals of firemen, detect environmental conditions and determine triage of victims during emergencies. All these systems use sensors that are integrated or embedded in garments to combine comfort to real wearability and real-time transmission. The present work is about the development and testing of electrodes and piezoresistive sensors made of yarn and integrated in the fireman's inner garment to monitor breathing.

In this paper is reported the experience gained in the last five years, in the implementation of wearable systems for personalized health care and their evolution in time. Sensing bio clothes for vital signs monitoring and wearable systems for gesture and posture recognition are specifically illustrated, resulting from the EU funded projects: Wealthy and My Heart.

In this paper is described the study leading to the implementation of two novel classes of textile piezoresistive sensors, for application in the field of post stroke rehabilitation and cardiovascular diseases monitoring. Two different approaches have been used, the first one leading to the realization of knitted transducer fabric to be integrated in bio-clothes for motion activity and respiration monitoring through plethysmography, the other one leading to printed sensing clothes for movement and posture detection. In particular, this work focuses on the optimization of sensors performances in term of sensing properties with the final objective to go towards a mass production.