A textile-based platform for real-time sweat collection and analysis

The ability to perform real-time chemical measurements of body fluids is an exciting concept for the healthcare sector and the sports industry. This work is part of the BIOTEX project, an EU FP6 project which involved the development of textile-based sensors to measure the chemical composition of sweat. This is a challenging task involving the collection of sweat samples, delivery to an active surface and the removal of waste products. A textile based platform which would be in immediate contact with the skin was developed for this purpose. The system uses capillary action and exhibits a passive pumping mechanism. This is achieved by using a combination of moisture wicking fabric and a highly absorbent material. A fabric channel is created for the integration of sensors. The channel is produced using a mask and screen-printing hydrophobic material onto the fabric. Different channel lengths and widths affect the flow rate of the system. The channel dimensions were designed based on typical sweat rates and also to accommodate sensor placement. A textile patch was developed and integrated into a waistband for collection of sweat on the lower back. Real-time measurements of sweat pH, sodium concentration, conductivity and temperature were measured during exercise using the textile patch

Wearable Textile Platform for Assessing Stroke Patient Treatment in Daily Life Conditions

Monitoring physical activities during post-stroke rehabilitation in daily life may help physicians to optimize and tailor the training program for patients. The European research project INTERACTION (FP7-ICT-2011-7-287351) evaluated motor capabilities in stroke patients during the recovery treatment period. We developed wearable sensing platform based on the sensor fusion among inertial, knitted piezoresistive sensors and textile EMG electrodes. The device was conceived in modular form and consists of a separate shirt, trousers, glove, and shoe. Thanks to the novel fusion approach it has been possible to develop a model for the shoulder taking into account the scapulo-thoracic joint of the scapular girdle, considerably improving the estimation of the hand position in reaching activities. In order to minimize the sensor set used to monitor gait, a single inertial sensor fused with a textile goniometer proved to reconstruct the orientation of all the body segments of the leg. Finally, the sensing glove, endowed with three textile goniometers and three force sensors showed good capabilities in the reconstruction of grasping activities and evaluating the interaction of the hand with the environment, according to the project specifications. This paper reports on the design and the technical evaluation of the performance of the sensing platform, tested on healthy subjects

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

QRS Complex Separation from Convolutive Mixtures of Biolectrical Signals Acquired by Wearable Systems

Independent component analysis (ICA) has been widely used to remove artefacts from multichannel biomedical signal acquisitions under the hypothesis that there is statistical independence among the original sources. However, the basic ICA model does not take into account the influence on the mixing process of the different paths from the signal sources to the sensors In this study we propose a convolutive mixtures model in order to overcome the limitations of the basic ICA approach. The independent components are estimated in the frequency domain, where the convolutive model can be solved through an instantaneous mixing model. The signals are reconstructed back to the observation space resolving the ICA model ambiguities. Simulations are carried out to optimize of the proposed method for convolutive mixtures of electrocardiographic (ECG) and motion artefacts signals. The algorithm is tested on real ECG signals acquired by wearable systems in order to preserve the QRS complex when the signals are degraded by real life conditions of acquisition

WEALTHY – a wearable healthcare system: new frontier on e-textile, Journal of Telecommunications and Information Technology, 2005, nr 4

A comfortable health monitoring system named WEALTHY is presented. The system is based on a wearable interface implemented by integrating fabric sensors, advanced signal processing techniques and modern telecommunication systems, on a textile platform. Conducting and piezoresistive materials in form of fibre and yarn are integrated in a garment and used as sensors, connectors and electrode elements. Simultaneous recording of vital signs allows extrapolation of more complex parameters and inter-signal elaboration that contribute to produce alert messages and patient table. The purpose of this publication is to evaluate the performance of the textile platform and the possibility of the simultaneous acquisition of several biomedical signals

BIOTEX-biosensing textiles for personalised healthcare management.

Textile-based sensors offer an unobtrusive method of continually monitoring physiological parameters during daily activities. Chemical analysis of body fluids, noninvasively, is a novel and exciting area of personalized wearable healthcare systems. BIOTEX was an EU-funded project that aimed to develop textile sensors to measure physiological parameters and the chemical composition of body fluids, with a particular interest in sweat. A wearable sensing system has been developed that integrates a textile-based fluid handling system for sample collection and transport with a number of sensors including sodium, conductivity, and pH sensors. Sensors for sweat rate, ECG, respiration, and blood oxygenation were also developed. For the first time, it has been possible to monitor a number of physiological parameters together with sweat composition in real time. This has been carried out via a network of wearable sensors distributed around the body of a subject user. This has huge implications for the field of sports and human performance and opens a whole new field of research in the clinical setting

Proetex: protective e-textiles to enhance the safety of emergency/disaster operators: current state of the projects' achievements

Proetex is a European Integrated Project dedicated to the realization of a micro- and nano-technology-based wearable equipment for emergency operators. During the first 3 years of work, two different and progressively improved versions of a complete “smart” uniform for fire-fighters and emergency rescuers have been realized. These garments aim at monitoring both physiological parameters, position and posture of the operators and the presence of external potential sources of danger and to send these data to a remote coordinating unit. In the following, the main issues of the design and realization will be described and discussed

A protocol for a multicentre, parallel-group, pragmatic randomised controlled trial to evaluate the NEVERMIND system in preventing and treating depression in patients with severe somatic conditions

Background Depressive symptoms are common in individuals suffering from severe somatic conditions. There is a lack of interventions and evidence-based interventions aiming to reduce depressive symptoms in patients with severe somatic conditions. The aim of the NEVERMIND project is to address these issues and provide evidence by testing the NEVERMIND system, designed to reduce and prevent depressive symptoms in comparison to treatment as usual. Methods The NEVERMIND study is a parallel-groups, pragmatic randomised controlled trial to assess the effectiveness of the NEVERMIND system in reducing depressive symptoms among individuals with severe somatic conditions. The NEVERMIND system comprises a smart shirt and a user interface, in the form of a mobile application. The system is a real-time decision support system, aiming to predict the severity and onset of depressive symptoms by modelling the well-being condition of patients based on physiological data, body movement, and the recurrence of social interactions. The study includes 330 patients who have a diagnosis of myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants are randomised in blocks of ten to either the NEVERMIND intervention or treatment as usual as the control group. Clinical interviews and structured questionnaires are administered at baseline, at 12 weeks, and 24 weeks to assess whether the NEVERMIND system is superior to treatment as usual. The endpoint of primary interest is Beck Depression Inventory II (BDI-II) at 12 weeks defined as (i) the severity of depressive symptoms as measured by the BDI-II. Secondary outcomes include prevention of the onset of depressive symptoms, changes in quality of life, perceived stigma, and self-efficacy. Discussion There is a lack of evidence-based interventions aiming to reduce and prevent depressive symptoms in patients with severe somatic conditions. If the NEVERMIND system is effective, it will provide healthcare systems with a novel and innovative method to attend to depressive symptoms in patients with severe somatic conditions. Trial registration DRKS00013391. Registered 23 November 2017