Affine Deformation and Self-Assembly Alignment in Hydrogel Nanocomposites.

Tailoring the order in hierarchical structures is a key goal of bioinspired nanocomposite design. Recently, nacre-like materials have been developed by solvent evaporation methods that are scalable and attain advanced functionalities. However, understanding the alignment mechanisms of 2D fillers, nanosheets, or platelets remains challenging. This work explores possible pathways for nanocomposite ordering via orientation distribution functions. We demonstrate how the immobilization of 2D materials via (pseudo)network formation is crucial to alignment based on evaporation. We show a modified affine deformation model that describes such evaporative methods. In this, a gel network develops enough yield stress and uniformly deforms as drying proceeds, along with the immobilized particles, causing an in-plane orientation. Herein, we tested the dominance of this approach by using a thermo-reversible gel for rapid montmorillonite (MMT) particle fixation. We researched gelatin/MMT as a model system to investigate the effects of high loadings, orientational order, and aspect ratio. The nacre-like nanocomposites showed a semiconstant order parameter (⟨P2⟩ ∼ 0.7) over increasing nanofiller content up to 64 vol % filler. This remarkable alignment resulted in continuously improved mechanical and water vapor barrier properties over unusually large filler fractions. Some variations in stiffness and diffusion properties were observed, possibly correlated to the applied drying conditions of the hybrid hydrogels. The affine deformation strategy holds promise for developing next-generation advanced materials with tailored properties even at (very) high filler loadings. Furthermore, a gelling approach offers the advantages of simplicity and versatility in the formulation of the components, which is useful for large-scale fabrication methods.

Design of Wearable Finger Sensors for Rehabilitation Applications.

As an emerging technology, smart textiles have attracted attention for rehabilitation purposes or to monitor heart rate, blood pressure, breathing rate, body posture, as well as limb movements. Traditional rigid sensors do not always provide the desired level of comfort, flexibility, and adaptability. To improve this, recent research focuses on the development of textile-based sensors. In this study, knitted strain sensors that are linear up to 40% strain with a sensitivity of 1.19 and a low hysteresis characteristic were integrated into different versions of wearable finger sensors for rehabilitation purposes. The results showed that the different finger sensor versions have accurate responses to different angles of the index finger at relaxation, 45° and 90°. Additionally, the effect of spacer layer thickness between the finger and sensor was investigated.

Upper-Body versus Lower-Body Cooling in Individuals with Paraplegia during Arm-Crank Exercise in the Heat.

PURPOSE: For wheelchair users with a spinal cord injury, the lower body may be a more convenient cooling site than the upper body. However, it remains unknown if leg cooling reduces thermal strain in these individuals. We compared the impact of upper-body versus lower-body cooling on physiological and perceptual outcomes during submaximal arm-crank exercise under heat stress in individuals with paraplegia. METHODS: Twelve male participants with paraplegia (T4-L2, 50% complete lesion) performed a maximal exercise test in temperate conditions, and three heat stress tests (32°C, 40% relative humidity) in which they received upper-body cooling (COOL-UB), lower-body cooling (COOL-LB), or no cooling (CON) in a randomized counterbalanced order. Each heat stress test consisted of four exercise blocks of 15 min at 50% of peak power output, with 3 min of rest in between. Cooling was applied using water-perfused pads, with 14.8-m tubing in both COOL-UB and COOL-LB. RESULTS: Gastrointestinal temperature was 0.2°C (95% confidence interval (CI), 0.1°C to 0.3°C) lower during exercise in COOL-UB versus CON (37.5°C ± 0.4°C vs 37.7°C ± 0.3°C, P = 0.009), with no difference between COOL-LB and CON ( P = 1.0). Heart rate was lower in both COOL-UB (-7 bpm; 95% CI, -11 to -3 bpm; P = 0.01) and COOL-LB (-5 bpm; 95% CI, -9 to -1 bpm; P = 0.049) compared with CON. The skin temperature reduction at the cooled skin sites was larger in COOL-LB (-10.8°C ± 1.1°C) than in COOL-UB (-6.7°C ± 1.4°C, P < 0.001), which limited the cooling capacity in COOL-LB. Thermal sensation of the cooled skin sites was improved and overall thermal discomfort was lower in COOL-UB ( P = 0.01 and P = 0.04) but not in COOL-LB ( P = 0.17 and P = 0.59) compared with CON. CONCLUSIONS: Upper-body cooling more effectively reduced thermal strain than lower-body cooling in individuals with paraplegia, as it induced greater thermophysiological and perceptual benefits.

Development of Low Hysteresis, Linear Weft-Knitted Strain Sensors for Smart Textile Applications.

In recent years, knitted strain sensors have been developed that aim to achieve reliable sensing and high wearability, but they are associated with difficulties due to high hysteresis and low gauge factor (GF) values. This study investigated the electromechanical performance of the weft-knitted strain sensors with a systematic approach to achieve reliable knitted sensors. For two elastic yarn types, six conductive yarns with different resistivities, the knitting density as well as the number of conductive courses were considered as variables in the study. We focused on the 1 × 1 rib structure and in the sensing areas co-knit the conductive and elastic yarns and observed that positioning the conductive yarns at the inside was crucial for obtaining sensors with low hysteresis values. We show that using this technique and varying the knitting density, linear sensors with a working range up to 40% with low hysteresis can be obtained. In addition, using this technique and varying the knitting density, linear sensors with a working range up to 40% strain, hysteresis values as low as 0.03, and GFs varying between 0 and 1.19 can be achieved.

Impact of different climatic conditions on peak core temperature of elite athletes during exercise in the heat: a Thermo Tokyo simulation study.

Objectives: To evaluate how separate and combined climatic parameters affect peak core temperature during exercise in the heat using computer simulations fed with individual data. Methods: The impact of eight environmental conditions on rectal temperature (Tre) was determined for exercise under heat stress using the Fiala-thermal-Physiology-and-Comfort simulation model. Variations in ambient temperature (Ta±6°C), relative humidity (RH±15%) and solar radiation (SR+921 W/m2) were assessed in isolation and combination (worst-case/best-case scenarios) and compared with baseline (Ta32°C, RH 75%, SR 0 W/m2). The simulation model was fed with personal, anthropometric and individual exercise characteristics. Results: 54 athletes exercised for 46±10 min at baseline conditions and achieved a peak core temperature of 38.9±0.5°C. Simulations at a higher Ta (38°C) and SR (921 W/m2) resulted in a higher peak Tre compared with baseline (+0.6±0.3°C and +0.5±0.2°C, respectively), whereas a higher RH (90%) hardly affected peak Tre (+0.1±0.1°C). A lower Ta (26°C) and RH (60%) reduced peak Tre by -0.4±0.2°C and a minor -0.1±0.1°C, respectively. The worst-case simulation yielded a 1.5±0.4°C higher Tre than baseline and 2.0±0.7°C higher than the best-case condition. Conclusion: Combined unfavourable climatic conditions produce a greater increase in peak core temperature than the sum of its parts in elite athletes exercising in the heat.

Low-Cost Wearable Fluidic Sweat Collection Patch for Continuous Analyte Monitoring and Offline Analysis.

Sweat sensors allow for new unobtrusive ways to continuously monitor an athlete's performance and health status. Significant advances have been made in the optimization of sensitivity, selectivity, and durability of electrochemical sweat sensors. However, comparing the in situ performance of these sensors in detail remains challenging because standardized sweat measurement methods to validate sweat sensors in a physiological setting do not yet exist. Current collection methods, such as the absorbent patch technique, are prone to contamination and are labor-intensive, which limits the number of samples that can be collected over time for offline reference measurements. We present an easy-to-fabricate sweat collection system that allows for continuous electrochemical monitoring, as well as chronological sampling of sweat for offline analysis. The patch consists of an analysis chamber hosting a conductivity sensor and a sequence of 5 to 10 reservoirs that contain level indicators that monitor the filling speed. After testing the performance of the patch in the laboratory, elaborate physiological validation experiments (3 patch locations, 6 participants) were executed. The continuous sweat conductivity measurements were compared with laboratory [Na+] and [Cl-] measurements of the samples, and a strong linear relationship (R2 = 0.97) was found. Furthermore, sweat rate derived from ventilated capsule measurement at the three locations was compared with patch filling speed and continuous conductivity readings. As expected from the literature, sweat conductivity was linearly related to sweat rate as well. In short, a successfully validated sweat collection patch is presented that enables sensor developers to systematically validate novel sweat sensors in a physiological setting.

An End-to-End Deep Learning Pipeline for Football Activity Recognition Based on Wearable Acceleration Sensors.

Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvantage that they are costly and not easily transportable to new locations. In this study, we investigated the possibility to extract these statistics from acceleration sensor data generated by a previously developed sensor garment. We used deep learning-based models to recognize five football-related activities (jogging, sprinting, passing, shooting and jumping) in an accurate, robust, and fast manner. A combination of convolutional (CNN) layers followed by recurrent (bidirectional) LSTM layers achieved up to 98.3% of accuracy. Our results showed that deep learning models performed better in evaluation time and prediction accuracy than traditional machine learning algorithms. In addition to an increase in accuracy, the proposed deep learning architecture showed to be 2.7 to 3.4 times faster in evaluation time than traditional machine learning methods. This demonstrated that deep learning models are accurate as well as time-efficient and are thus highly suitable for cost-effective, fast, and accurate human activity recognition tasks.

Performance and thermoregulation of Dutch Olympic and Paralympic athletes exercising in the heat: Rationale and design of the Thermo Tokyo study: The journal Temperature toolbox.

The environmental conditions during the Tokyo Olympic and Paralympic Games are expected to be challenging, which increases the risk for participating athletes to develop heat-related illnesses and experience performance loss. To allow safe and optimal exercise performance of Dutch elite athletes, the Thermo Tokyo study aimed to determine thermoregulatory responses and performance loss among elite athletes during exercise in the heat, and to identify personal, sports-related, and environmental factors that contribute to the magnitude of these outcomes. For this purpose, Dutch Olympic and Paralympic athletes performed two personalized incremental exercise tests in simulated control (15°C, relative humidity (RH) 50%) and Tokyo (32°C, RH 75%) conditions, during which exercise performance and (thermo)physiological parameters were obtained. Thereafter, athletes were invited for an additional visit to conduct anthropometric, dual-energy X-ray absorptiometry (DXA), and 3D scan measurements. Collected data also served as input for a thermophysiological computer simulation model to estimate the impact of a wider range of environmental conditions on thermoregulatory responses. Findings of this study can be used to inform elite athletes and their coaches on how heat impacts their individual (thermo)physiological responses and, based on these data, advise which personalized countermeasures (i.e. heat acclimation, cooling interventions, rehydration plan) can be taken to allow safe and maximal performance in the challenging environmental conditions of the Tokyo 2020 Olympic and Paralympic Games.

Performance Evaluation of Knitted and Stitched Textile Strain Sensors.

By embedding conductive yarns in, or onto, knitted textile fabrics, simple but robust stretch sensor garments can be manufactured. In that way resistance based sensors can be fully integrated in textiles without compromising wearing comfort, stretchiness, washability, and ease of use in daily life. The many studies on such textile strain sensors that have been published in recent years show that these sensors work in principle, but closer inspection reveals that many of them still have severe practical limitations like a too narrow working range, lack of sensitivity, and undesired time-dependent and hysteresis effects. For those that intend to use this technology it is difficult to determine which manufacturing parameters, shape, stitch type, and materials to apply to realize a functional sensor for a given application. This paper therefore aims to serve as a guideline for the fashion designers, electronic engineers, textile researchers, movement scientists, and human-computer interaction specialists planning to create stretch sensor garments. The paper is limited to textile based sensors that can be constructed using commercially available conductive yarns and existing knitting and embroidery equipment. Within this subtopic, relevant literature is discussed, and a detailed quantitative comparison is provided focusing on sensor characteristics like the gauge factor, working range, and hysteresis.

A wearable fluidic collection patch and ion chromatography method for sweat electrolyte monitoring during exercise.

This paper presents a method to continuously collect and reliably measure sweat analyte concentrations during exercise. The method can be used to validate newly developed sweat sensors and to obtain insight into intraindividual variations of sweat analytes in athletes. First, a novel design of a sweat collection system is created. The sweat collection patch, that is made from hydrophilized foil and a double-sided acrylate adhesive, consists of a reservoir array that collects samples consecutively in time. During a physiological experiment, sweat can be collected from the back of a participant and the filling speed of the collector is monitored by using a camera. After the experiment, Na+, Cl- and K+ levels are measured with ion chromatography. Sweat analyte variations are measured during exercise for an hour at three different locations on the back. The Na+ and Cl- variations show a similar trend and the absolute concentrations vary with the patch location. Na+ and Cl- concentrations increase and K+ concentrations seem to decrease during this exercise. With this new sweat collection system, sweat Na+, Cl- and K+ concentrations can be collected over time during exercise at medium to high intensity, to analyse the trend in electrolyte variations per individual.

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field.

Current athlete monitoring practice in team sports is mainly based on positional data measured by global positioning or local positioning systems. The disadvantage of these measurement systems is that they do not register lower extremity kinematics, which could be a useful measure for identifying injury-risk factors. Rapid development in sensor technology may overcome the limitations of the current measurement systems. With inertial measurement units (IMUs) securely fixed to body segments, sensor fusion algorithms and a biomechanical model, joint kinematics could be estimated. The main purpose of this article is to demonstrate a sensor setup for estimating hip and knee joint kinematics of team sport athletes in the field. Five male subjects (age 22.5 ± 2.1 years; body mass 77.0 ± 3.8 kg; height 184.3 ± 5.2 cm; training experience 15.3 ± 4.8 years) performed a maximal 30-meter linear sprint. Hip and knee joint angles and angular velocities were obtained by five IMUs placed on the pelvis, both thighs and both shanks. Hip angles ranged from 195° (± 8°) extension to 100.5° (± 8°) flexion and knee angles ranged from 168.6° (± 12°) minimal flexion and 62.8° (± 12°) maximal flexion. Furthermore, hip angular velocity ranged between 802.6 °·s-1 (± 192 °·s-1) and -674.9 °·s-1 (± 130 °·s-1). Knee angular velocity ranged between 1155.9 °·s-1 (± 200 °·s-1) and -1208.2 °·s-1 (± 264 °·s-1). The sensor setup has been validated and could provide additional information with regard to athlete monitoring in the field. This may help professionals in a daily sports setting to evaluate their training programs, aiming to reduce injury and optimize performance.

Towards High Performance Metal-Organic Framework-Microporous Polymer Mixed Matrix Membranes: Addressing Compatibility and Limiting Aging by Polymer Doping.

Membrane separation for gas purification is an energy-efficient and environment-friendly technology. However, the development of high performance membranes is still a great challenge. In principle, mixed matrix membranes (MMMs) have the potential to overcome current materials limitations, but in practice there is no straightforward method to match the properties of fillers and polymers (the main components of MMMs) in such a way that the final membrane performance reflects the high performance of the microporous filler and the processability of the continuous polymer phase. This issue is especially important when high flux polymers are utilized. In this work, we demonstrate that the use of small amounts of a glassy polymer in combination with high performance PIM-1 allow for the preparation of metal-organic framework (MOF)-based MMMs with superior separation properties and low aging rates under humid conditions, meeting the commercial target for post-combustion CO2 capture.

Hydrophobin gene deletion and environmental growth conditions impact mechanical properties of mycelium by affecting the density of the material.

Filamentous fungi colonize substrates by forming a mycelium. This network of hyphae can be used as a bio-based material. Here, we assessed the impact of environmental growth conditions and deletion of the hydrophobin gene sc3 on material properties of the mycelium of the mushroom forming fungus Schizophyllum commune. Thermogravimetric analysis showed that Δsc3 mycelium retained more water with increasing temperature when compared to the wild type. The Young's modulus (E) of the mycelium ranged between 438 and 913 MPa when the wild type strain was grown in the dark or in the light at low or high CO2 levels. This was accompanied by a maximum tensile strength (σ) of 5.1-9.6 MPa. In contrast, E and σ of the Δsc3 strain were 3-4- fold higher with values of 1237-2727 MPa and 15.6-40.4 MPa, respectively. These values correlated with mycelium density, while no differences in chemical composition of the mycelia were observed as shown by ATR-FTIR. Together, genetic modification and environmental growth conditions impact mechanical properties of the mycelium by affecting the density of the mycelium. As a result, mechanical properties of wild type mycelium were similar to those of natural materials, while those of Δsc3 were more similar to thermoplastics.

Inhibition of glycosaminoglycan incorporation influences collagen network formation during cartilage matrix production.

To understand cartilage degenerative diseases and improve repair procedures, we investigate the influence of glycosaminoglycans (GAGs) on cartilage matrix biochemistry and functionality. Bovine articular chondrocytes were cultured in alginate beads with(out) para-nitrophenyl-beta-d-xyloside (PNPX) to inhibit GAG incorporation into newly formed proteoglycans. As expected, GAG deposition in alginate beads decreased with increasing PNPX concentration. Next to GAGs, collagen deposition and cross-linking also decreased. In the presence of PNPX, GAGs and collagen were deposited further away from the chondrocyte than in the control and increased amounts were found in the culture medium. These changes resulted in decreased functional properties of the construct. We conclude that in our culture system, intact proteoglycans play a role in deposition of collagen and thus the formation of a functional matrix. The effect of less proteoglycans on the collagen network could explain why cartilage repair is ineffective in osteoarthritis and help us with development of new therapies.