Lena Berglin

Electrical characteristics of conductive yarns and textile electrodes for medical applications

Clothing with conductive textiles for health care applications has in the last decade been of an upcoming research interest. An advantage with the technique is its suitability in distributed and home health care. The present study investigates the electrical properties of conductive yarns and textile electrodes in contact with human skin, thus representing a real ECG-registration situation. The yarn measurements showed a pure resistive characteristic proportional to the length. The electrodes made of pure stainless steel (electrode A) and 20% stainless steel/80% polyester (electrode B) showed acceptable stability of electrode potentials, the stability of A was better than that of B. The electrode made of silver plated copper (electrode C) was less stable. The electrode impedance was lower for electrodes A and B than that for electrode C. From an electrical properties point of view we recommend to use electrodes of type A to be used in intelligent textile medical applications.

Adaptive spatio-temporal filtering of disturbed ECGs: a multi-channel approach to heartbeat detection in smart clothing

Intermittent disturbances are common in ECG signals recorded with smart clothing: this is mainly because of displacement of the electrodes over the skin. We evaluated a novel adaptive method for spatio-temporal filtering for heartbeat detection in noisy multi-channel ECGs including short signal interruptions in single channels. Using multi-channel database recordings (12-channel ECGs from 10 healthy subjects), the results showed that multi-channel spatio-temporal filtering outperformed regular independent component analysis. We also recorded seven channels of ECG using a T-shirt with textile electrodes. Ten healthy subjects performed different sequences during a 10-min recording: resting, standing, flexing breast muscles, walking and pushups. Using adaptive multi-channel filtering, the sensitivity and precision was above 97% in nine subjects. Adaptive multi-channel spatio-temporal filtering can be used to detect heartbeats in ECGs with high noise levels. One application is heartbeat detection in noisy ECG recordings obtained by integrated textile electrodes in smart clothing.

Improvement of electro-mechanical properties of strain sensors made of elastic-conductive hybrid yarns

Fabric-based strain sensors have been developed using different technologies, among which flat knitting is one of the most effective and economical methods. However, knitted strain sensors are not often used in practical applications because the sensors usually exhibit large elastic hysteresis when they are deformed and subjected to stress during application. One possible approach to overcome these shortcomings is to introduce elastic properties at the yarn level by combining the conductive materials with elastic materials. In this paper, we demostrate a hybrid yarn made of a conductive yarn that winds around an elastic core yarn in a direct twisting device. The electro-mechanical properties of strain sensors knitted from the hybrid yarns were tested in order to characterize the sensors. This study consisted of two stages: the yarn preparation and the sensor characterization. In the first stage, two kinds of elastic core components (polyamide/Lycra and polyamide) and two kinds of conductive winding yarns (Bekinox BK50/1 and Bekinox BK50/2) were selected for twisting. The twisting was done with a constant twisting speed and four different numbers of twists. Mechanical properties, that is, the tenacity, force at break and elongation at break, were tested in order to determine the optimal parameters for producing the hybrid yarns. The results indicated that among the tested yarns those with a polyamide core and Bekinox BK50/1 winding yarns at 450 twist/meter and with a polyamide/Lycra core and Bekinox BK 50/2 winding yarns at 600 twist/meter had the best properties. These were thus selected as the materials for producing knitted strain sensors. In the second stage, electro-mechanical properties of the knitted strain sensors were determined under tensile stress and multi-cyclic tensile stress. The results show that the hybrid yarns can effectively enhance the electro-mechanical properties of the knitted strain sensors without compromising processiablity and comfortability.

Design of a garment-based sensing system for breathing monitoring

The long-term monitoring of biophysiological signals requires new types of sensor systems that are wearable and at the same time convenient for the users. This paper describes the design of a novel garment-based sensing system for the long-term monitoring of breathing rhythm. The system concept was realized in a prototype garment, integrated with coated piezoresistive sensors. The prototype garment was tested by five subjects, and compared with a standard piezoelectric respiratory belt. Each signal was quantitatively and qualitatively evaluated in the time and frequency domain to make sure that no medical and diagnostic information was lost. The results showed a good agreement between the garment-based sensors and the standard reference, where errors occurred only when the breathing rate was extremely high. The garment-based sensor system could also distinguish the predominance breathing compartment (chest versus abdominal breathing). The system could detect a 10 s pause in breathing, which could be of importance in studies of sleep apnea. A garment-based sensing system maintains the accuracy of the signal quality without reducing the comfort for the user. It makes possible long-term ambulatory monitoring and has home-based healthcare applications.

Osteogenic Differentiation of Human Mesenchymal Stem cells in a 3D Woven Scaffold

Fiber-based scaffolds produced by textile manufacturing technology offer versatile materials for tissue engineering applications since a wide range of crucial scaffold parameters, including porosity, pore size and interconnectivity, can be accurately controlled using 3D weaving. In this study, we developed a weavable, bioactive biodegradable composite fiber from poly (lactic acid) (PLA) and hydroxyapatite powder by melt spinning. Subsequently, scaffolds of these fibers were fabricated by 3D weaving. The differentiation of human mesenchymal stem cells (hMSCs) in vitro was studied on the 3D scaffolds and compared with differentiation on 2D substrates having the same material composition. Our data showed that the 3D woven scaffolds have a major impact on hMSCs proliferation and activation. The 3D architecture supports the differentiation of the hMSCs into osteoblast cells and enhances the production of mineralized bone matrix. The present study further confirms that a 3D scaffold promotes hMSCs differentiation into the osteoblast–lineage and bone mineralization.

An assistive sleeping bag for children with autism spectrum disorder

Children suffering from autism spectrum disorder are often reported to encounter sleeping disorder several causes such as hypersensitivity as result of irregular brain and muscle functions. Disturbance in sleep affects not only their health but also daytime activities including the risk of other cognitive and behavioral impairments. Such hindrance in sleep have been demonstrated to treat therapeutically by measures like application of deep pressure touch and full body vibration which can be beneficially integrated into the sleeping environment such as on the textile-based platform around the bed. With such a vision, this pilot design project aimed to develop a smart textile based sleeping bag incorporated with sensors to detect awakening stage of the child and thereby actuating stimuli for assuaging the child to fall asleep. To serve the purpose, a micro-controllable body movement detection sensor, based on conductive yarns connected to a vibrating motor was prosperously embedded at the interior of the sleeping bag along with weighted slots to exert deep touch and soothing sensation in the form of wearable technology.