Fabric sensors – modelling deformation in knitted fabrics

Fabric sensors are made from knitted conductive yarn and can be used to measure extension in wearable technologies and composite structures. Wearable technologies have considerable potential in sport and medical applications, for example recording limb movement in injury monitoring or sporting technique analysis. The electrical resistance through the fabric varies with extension due to the change in contact area and contact force between yarns. The resistance can be interpreted using correlations with displacement to calculate the deformation experienced by the fabric sensor. This paper describes a study which works towards a realistic digital model of a single jersey knitted fabric sensor by considering a non-idealised monofilament yarn of varied cross-section in a dense knit geometry. Models are created using TexGen, software developed at the University of Nottingham, taking advantage of its facility to create complex cross-sections which vary along the length of the yarn. Subsequent finite element analysis using ABAQUS with small representative volume elements and periodic boundary conditions showed high peak stresses at the boundaries, possibly caused by the contact surface being split across the boundary. Subsequent simulations using larger numbers of stitches and with relaxed boundary conditions in the x-direction showed more realistic deformations including reduction in width and curling of the material, reducing the impact of the boundaries on the overall fabric simulation, but with significant computational cost. The results give an initial assessment of deformations and contact pressures, which will aid understanding of the non-linear response found in mechanical testing and improve knowledge of how the inter-yarn contact varies. This work lays the foundation for further work which will aim to improve the similarity between the digital knit geometry and the physical sample, model larger areas of knitted fabric, include residual stresses from manufacture and use a multifilament yarn model. Subsequently the much more complex knitting patterns produced by the manufacturer of these sensors will then be able to be modelled

Finite element investigation of the effect of spina bifida on loading of the vertebral isthmus

Background: Spondylolysis (SL) of the lower lumbar spine is frequently associated with spina bifida occulta (SBO). There has not been any study that has demonstrated biomechanical or genetic predispositions to explain the coexistence of these two pathologies. In axial rotation, the intact vertebral arch allows torsional load to be shared between the facet joints. In SBO, the load cannot be shared across the arch, theoretically increasing the mechanical demand of the vertebral isthmus during combined axial loading and rotation when compared to the normal state. Purpose: To test the hypothesis that fatigue failure limits will be exceeded in the case of a bifid arch, but not in the intact case, when the segment is subjected to complex loading corresponding to normal sporting activities. Study Design: Descriptive Laboratory Study. Methods: Finite element models of natural and SBO (L4-S1) including ligaments were loaded axially to 1kN and were combined with axial rotation of 3°. Bilateral stresses, alternating stresses and shear fatigue failure on intact and SBO L5 isthmus were assessed and compared. Results: Under 1kN axial load, the von Mises stresses observed in SBO and in the intact cases were very similar (differences <5MPa) having a maximum at the ventral end of the isthmus that decreases monotonically to the dorsal end. However, under 1kN axial load and rotation, the maximum von Mises stresses observed in the ipsilateral L5 isthmus in the SBO case (31MPa) was much higher than the intact case (24.2MPa) indicating a lack of load sharing across the vertebral arch in SBO. When assessing the equivalent alternating shear stress amplitude, this was found to be 22.6 MPa for the SBO case and 13.6 MPa for the intact case. From this it is estimated that shear fatigue failure will occur in less than 70,000 cycles, under repetitive axial load & rotation conditions in the SBO case, while for the intact case, fatigue failure will occur only over 10 million cycles. Conclusion: SBO predisposes spondylolysis by generating increased stresses across the inferior isthmus of the inferior articular process, specifically in combined axial rotation and anteroposterior shear. Clinical Relevance: Athletes with SBO who participate in sports that require repetitive lumbar rotation, hyperextension and/or axial loading are at a higher risk of developing spondylolysis compared to athletes with an intact spine

Smartphone monitoring of in-ambulance vibration and noise

Transferring sick premature infants between hospitals increases the risk of severe brain injury, potentially linked to the excessive exposure to noise, vibration and driving-related accelerations. One method of reducing these levels may be to travel along smoother and quieter roads at an optimal speed, however this requires mass data on the effect of roads on the environment within ambulances. An app for the Android operating system has been developed for the purpose of recording vibration, noise levels, location and speed data during ambulance journeys. Smartphone accelerometers were calibrated using sinusoidal excitation and the microphones using calibrated pink noise. Four smartphones were provided to the local neonatal transport team and mounted on their neonatal transport systems to collect data. Repeatability of app recordings was assessed by comparing 37 journeys, made during the study period, along an 8.5 km single carriageway. The smartphones were found to have an accelerometer accurate to 5% up to 55 Hz and microphone accurate to 0.8 dB up to 80 dB. Use of the app was readily adopted by the neonatal transport team, recording more than 97,000 km of journeys in 1 year. To enable comparison between journeys, the 8.5 km route was split into 10 m segments. Interquartile ranges for vehicle speed, vertical acceleration and maximum noise level were consistent across all segments (within 0.99 m . s−1, 0.13 m · s−2 and 1.4 dB, respectively). Vertical accelerations registered were representative of the road surface. Noise levels correlated with vehicle speed. Android smartphones are a viable method of accurate mass data collection for this application. We now propose to utilise this approach to reduce potential harmful exposure, from vibration and noise, by routing ambulances along the most comfortable roads

Computational mechanical characterization of geometrically transformed Schwarz P lattice tissue scaffolds fabricated via two photon polymerization (2PP)

Schwarz P unit cell-based tissue scaffolds comprised of poly(D,L-lactide-co-caprolactone)(PLCL) fabricated via the additive manufacturing technique, two-photon polymerisation (2PP) were found to undergo geometrical transformations from the original input design. A Schwarz P unit cell surface geometry CAD model was reconstructed to take into account the geometrical transformations through CAD modeling techniques using measurements obtained from an image-based averaging technique before its implementation for micromechanical analysis. Effective modulus results obtained from computational mechanical characterization via micromechanical analysis of the reconstructed unit cell assigned with the same material model making up the fabricated scaffolds demonstrated excellent agreement with a small margin of error at 6.94% from the experimental mean modulus (0.69 0.29MPa). The possible sources for the occurrence of geometrical transformations are discussed in this paper. The interrelationships between different dimensional parameters making up the Schwarz P architecture and resulting effective modulus are also assessed and discussed. With the ability to accommodate the geometrical transformations, maintain efficiency in terms of time and computational resources, micromechanical analysis has the potential to be implemented in tissue scaffolds with a periodic microstructure as well as other structures outside the field of tissue engineering in general

A systematic literature review and meta‐analysis on digital health interventions for people living with dementia and Mild Cognitive Impairment

Abstract: Objectives: Digital health interventions enable services to support people living with dementia and Mild Cognitive Impairment (MCI) remotely. This literature review gathers evidence on the effectiveness of digital health interventions on physical, cognitive, behavioural and psychological outcomes, and Activities of Daily Living in people living with dementia and MCI. Methods/Design: Searches, using nine databases, were run in November 2021. Two authors carried out study selection/appraisal using the Critical Appraisal Skills Programme checklist. Study characteristics were extracted through the Cochrane handbook for systematic reviews of interventions data extraction form. Data on digital health interventions were extracted through the template for intervention description and replication (TIDieR) checklist and guide. Intervention effectiveness was determined through effect sizes. Meta‐analyses were performed to pool data on intervention effectiveness. Results: Twenty studies were included in the review, with a diverse range of interventions, modes of delivery, activities, duration, length, frequency, and intensity. Compared to controls, the interventions produced a moderate effect on cognitive abilities (SMD = 0.36; 95% CI = −0.03 to 0.76; I2 = 61%), and a negative moderate effect on basic ADLs (SMD = −0.40; 95% CI = −0.86 to 0.05; I2 = 69%). Stepping exergames generated the largest effect sizes on physical and cognitive abilities. Supervised training produced larger effect sizes than unsupervised interventions. Conclusion: Supervised intervention delivery is linked to greatest benefits. A mix of remote and face‐to‐face delivery could maximise benefits and optimise costs. Accessibility, acceptability and sustainability of digital interventions for end‐users must be pre‐requisites for the development of future successful services

Effect of mechanical preconditioning on the electrical properties of knitted conductive textiles during cyclic loading

This paper presents, for the first time, the electrical response of knitted conductive fabrics to a considerable number of cycles of deformation in view of their use as wearable sensors. The changes in the electrical properties of four knitted conductive textiles, made of 20% stainless steel and 80% polyester fibers, were studied during unidirectional elongation in an Instron machine. Two tests sessions of 250 stretch–recovery cycles were conducted for each sample at two elongation rates (9.6 and 12 mm/s) and at three constant currents (1, 3 and 6 mA). The first session assessed the effects of an extended cyclic mechanical loading (preconditioning) on the electrical properties, especially on the electrical stabilization. The second session, which followed after a 5 minute interval under identical conditions, investigated whether the stabilization and repeatability of the electrical features were maintained after rest. The influence of current and elongation rate on the resistance measurements was also analyzed. In particular, the presence of a semiconducting behavior of the stainless steel fibers was proved by means of different test currents. Lastly, the article shows the time-dependence of the fabrics by means of hysteresis graphs and their non-linear behavior thanks to a time–frequency analysis. All knit patterns exhibited interesting changes in electrical properties as a result of mechanical preconditioning and extended use. For instance, the gauge factor, which indicates the sensitivity of the fabric sensor, varied considerably with the number of cycles, being up to 20 times smaller than that measured using low cycle number protocols