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Pressure sensors based on advanced materials have gained high attention for their potential applications in various fields, including sports training. This study focuses on the development of poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE))/graphene composite films as high-performance pressure sensors. The composite films were fabricated using a casting method, and their morphological, structural, thermal, mechanical, and electrical properties were comprehensively characterized. The incorporation of graphene nanoplatelets (GnPs) into the P(VDF-TrFE) matrix led to the formation of a percolated conductive network, resulting in enhanced electrical conductivity and pressure sensitivity. The composite film containing 5 wt% GnP exhibited remarkable sensing capabilities, boasting an elevated sensitivity of 0.85 kPa−1, a rapid response time of 50 ms, and exceptional resilience over 1000 loading-unloading cycles. Moreover, the incorporation of GnP substantially augmented the mechanical properties, with a 65 % enhancement in tensile strength and a 92 % surge in Young's modulus when juxtaposed against pristine P(VDF-TrFE) films. The superior property of these P(VDF-TrFE)/graphene composite pressure sensors, along with their excellent mechanical properties, make them promising candidates for sports training applications, enabling the monitoring and analysis of various biomechanical parameters to optimize athletic performance and prevent injuries. [ABSTRACT FROM AUTHOR]

Pressure sensors based on advanced materials have gained high attention for their potential applications in various fields, including sports training. This study focuses on the development of poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE))/graphene composite films as high-performance pressure sensors. The composite films were fabricated using a casting method, and their morphological, structural, thermal, mechanical, and electrical properties were comprehensively characterized. The incorporation of graphene nanoplatelets (GnPs) into the P(VDF-TrFE) matrix led to the formation of a percolated conductive network, resulting in enhanced electrical conductivity and pressure sensitivity. The composite film containing 5 wt% GnP exhibited remarkable sensing capabilities, boasting an elevated sensitivity of 0.85 kPa−1, a rapid response time of 50 ms, and exceptional resilience over 1000 loading-unloading cycles. Moreover, the incorporation of GnP substantially augmented the mechanical properties, with a 65 % enhancement in tensile strength and a 92 % surge in Young's modulus when juxtaposed against pristine P(VDF-TrFE) films. The superior property of these P(VDF-TrFE)/graphene composite pressure sensors, along with their excellent mechanical properties, make them promising candidates for sports training applications, enabling the monitoring and analysis of various biomechanical parameters to optimize athletic performance and prevent injuries.

The integration of sensor technology and automated analytics in wearable devices marks a significant advancement in sports science, aiming to proactively prevent injuries and optimize athletic performance. This paper delves into the application of advanced sensor systems and automated data analysis tools in the realm of athletics. These wearables, equipped with a multitude of sensors, continuously monitor an athlete's physiological and biomechanical data, including heart rate, muscle activity, and movement dynamics. The automated processing of this data through machine learning algorithms enables real-time insights and predictive analytics, offering a novel approach to injury prevention. By analyzing the intricate patterns of an athlete's performance metrics, these sensor-augmented wearables facilitate a data-driven strategy for reducing risks of soft-tissue and heat-related injuries. This technology empowers coaches and athletes with actionable insights, fostering a safer and more efficient training environment. Our exploration showcases the transformative impact of sensor-enhanced wearables and automated analytics in elevating the standards of injury prevention and performance optimization in sports.

Abstract Background Fencing is a highly asymmetrical combat sport, that imposes high mechanical demands over repeated exposures on the musculoskeletal structures, a primary cause of injuries in fencers. However, there are limited epidemiological studies on the structural injuries of the foot and ankle in fencers. This study aimed to investigate foot and ankle structural injuries, and explore how metatarsophalangeal joint structural changes may affect the mechanisms of foot and ankle injuries in asymptomatic fencers. Methods 3D images of foot and ankle morphology using computed tomography were obtained from ten elite fencers. We then constructed finite element models of the first metatarsophalangeal joint in the foot of their trail legs. The validated models were used to simulate stress distribution changes from different ankle joint angles during lunging. Results The findings showed that stress distribution changes at the medial and lateral sesamoid may have caused sesamoid fractures, and that habitual and concentrated stress on the metatarsal bones might have flattened the sesamoid groove. This process may damage the integrity of the first metatarsophalangeal joint, and consequently affect the efficiency of the windlass mechanism in fencers. During lunging, different ankle joint angles of the trail foot increased the total stress difference of the medial and lateral foot, and thus influenced the lunging quality and its stability. Conclusions Our findings revealed that the asymmetric nature of fencing might have caused asymptomatic foot and ankle structural injuries, and finite element analysis results indicated that this might increase the incidence of the serious injuries if unattended. Regular computed tomography examination should be introduced to monitor elite fencers’ lower limb alterations, permitting unique angle adjustments in the trail foot without sacrificing technical or physiologic properties based on the exam results and reduce the lower limb injury risk.

Low-cost and field-viable methods that can simultaneously assess external kinetics and kinematics are necessary to enhance field-based biomechanical monitoring. The aim of this study was to determine the accuracy and usability of ground reaction force (GRF) profiles estimated from segmental kinematics, measured with OpenCap (a low-cost markerless motion-capture system), during common jumping movements. Full-body segmental kinematics were recorded for fifteen recreational athletes performing countermovement, squat, bilateral drop, and unilateral drop jumps, and used to estimate vertical GRFs with a mechanics-based method. Eleven distinct performance-, fatigue-, or injury-related GRF variables were then validated against a gold-standard force platform. Across jumping movements, a total of six and three GRF variables were estimated with a bias or limits of agreement <5 % respectively. Bias and limits of agreement were between 5 and 15 % for seventeen and nineteen variables respectively. Moreover, we show that estimated force variables with a bias <15 % can adequately assess the within-athlete changes in GRF variables between jumping conditions (arm swing or leg dominance). These findings indicate that using a low-cost and field-viable markerless motion capture system (OpenCap) to estimate and assess GRF profiles during common jumping movements is approaching acceptable limits of accuracy. The presented method can be used to monitor force variables of interest and examine underlying segmental kinematics. This application is a jump towards researchers and sports practitioners performing biomechanical monitoring of jumping efficiently, regularly, and extensively in field settings. [ABSTRACT FROM AUTHOR]

Smart wearables with the capability for continuous monitoring, perceiving, and understanding human tactile and motion signals, while ensuring comfort, are highly sought after for intelligent healthcare and smart life systems. However, concurrently achieving high-performance tactile sensing, long-lasting wearing comfort, and industrialized fabrication by a low-cost strategy remains a great challenge. This is primarily due to critical research gaps in novel textile structure design for seamless integration with sensing elements. Here, an all-in-one biaxial insertion knit architecture is reported to topologically integrate sensing units within double-knit loops for the fabrication of a large-scale tactile sensing textile by using low-cost industrial manufacturing routes. High sensitivity, stability, and low hysteresis of arrayed sensing units are achieved through engineering of fractal structures of hierarchically patterned piezoresistive yarns via blistering and twisting processing. The as-prepared tactile sensing textiles show desirable sensing performance and robust mechanical property, while ensuring excellent conformability, tailorability, breathability (288 mm s -1 ), and moisture permeability (3591 g m -2 per day) for minimizing the effect on wearing comfort. The multifunctional applications of tactile sensing textiles are demonstrated in continuously monitoring human motions, tactile interactions with the environment, and recognizing biometric gait. Moreover, we also demonstrate that machine learning-assisted sensing textiles can accurately predict body postures, which holds great promise in advancing the development of personalized healthcare robotics, prosthetics, and intelligent interaction devices.

For many diseases, treatment is more effective in the early stage of a disease; hence detection of the early signs of a disease is highly significant. Biomechanical motion can be such an early indicator. This paper proposes a novel method for monitoring biomechanical motion based on electromagnetic sensing techniques. The proposed method has the advantages of being non-invasive, easy to perform, of low cost, and highly effective. Theoretical models are set up to model the sensor responses and wearable sensor systems are designed. Experiments are performed to monitor various biomechanical movements, including eye blinking frequency, finger/wrist bending level and frequency. From experiments, both the fast blinking behavior with an average frequency of ~1.1 Hz and the slow blinking behavior with an average frequency of 0.4 Hz can be monitored; various finger-bending status are identified, such as the fast finger-bending with an average frequency of ~1.5 Hz and the slow finger-bending with an average frequency of ~1/6 Hz. Both simulations and measurement results indicate that the proposed electromagnetic sensing method can be used for biomechanical movement detection and the system has the advantages of being easy to put on / take off, and without the need for direct contact between sensors and human body. [ABSTRACT FROM AUTHOR]

In this paper, an eco-friendly and biodegradable triboelectric nanogenerator (SBB-TENG) is proposed based on bacterial cellulose (BC), sodium alginate (SA) with the introduction of barium titanate (BTO) nanoparticles. While all the composite membranes can be fully decomposed by cellulase solution within 7 h, the electrical properties of SBB-TENG are significantly improved due to the synergistic effect of enhanced dielectric constant and surface roughness of the composite membrane. Compared with SA/BC-based TENG (SBC-TENG), the voltage and current of SBB-TENGs are increased by 174 % and 193 %, respectively. In addition, the as-designed SBB TENGs are capable of serving as sensors for biomechanical monitoring, touch sensing and signal control, which greatly contributes to the development of high-performance, green and low-cost TENGs on the base of natural biodegradable materials. [Display omitted] • A triboelectric nanogenerator based on bacterial cellulose, sodium alginate with the introduction of BaTiO 3 nanoparticles is proposed. • All the bacterial-cellulose-based composite membranes can be fully decomposed by cellulase solution within 7 h. • The BTO particles are wrapped in the BC nanofibers, forming a uniform and continuous three-dimensional cellulose-based network structure. • The performance of SBB-TENG is improved due to the synergistic effect of dielectric constant and surface roughness of the composite. • The SBB-TENGs can be used as sensors for biomechanical monitoring, touch sensing, and signal control. [ABSTRACT FROM AUTHOR]

This study explored the efficacy of collecting temporal fracture site compliance data via an advanced direct electromagnetic coupling (DEC) system equipped with a Vivaldi-type antenna, novel calibration technique, and multi-antenna setup (termed maDEC) as an approach to monitor acute fracture healing progress in a translational large animal model. The overarching goal of this approach was to provide insights into the acute healing dynamics, offering a promising avenue for optimizing fracture management strategies. A sample of twelve sheep, subjected to ostectomies and intramedullary nail fixations, was divided into two groups, simulating normal and impaired healing scenarios. Sequential maDEC compliance or stiffness measurements and radiographs were taken from the surgery until euthanasia at four or eight weeks and were subsequently compared with post-sacrifice biomechanical, micro-CT, and histological findings. The results showed that the maDEC system offered straightforward quantification of fracture site compliance via a multiantenna array. Notably, the rate of change in the maDEC-measured bending stiffness significantly varied between normal and impaired healing groups during both the 4-week (p = 0.04) and 8-week (p = 0.02) periods. In contrast, radiographically derived mRUST healing measurements displayed no significant differences between the groups (p = 0.46). Moreover, the cumulative normalized stiffness maDEC data significantly correlated with post-sacrifice mechanical strength (r2 = 0.80, p < 0.001), micro-CT measurements of bone volume fraction (r2 = 0.60, p = 0.003), and density (r2 = 0.60, p = 0.003), and histomorphometric measurements of new bone area fraction (r2 = 0.61, p = 0.003) and new bone area (r2 = 0.60, p < 0.001). These data indicate that the enhanced maDEC system provides a non-invasive, accurate method to monitor fracture healing during the acute healing phase, showing distinct stiffness profiles between normal and impaired healing groups and offering critical insights into the healing process's progress and efficiency. [ABSTRACT FROM AUTHOR]

Abstract: Wearable triboelectric nanogenerators (TENGs) with both functionality and comfort have become an appealing field of research for portable electronic devices recently. Here, a breathable, stretchable, and tailorable TENG that enables both energy harvesting and biomechanical monitoring is designed. Two layers of nanofiber membranes, which consist of polyvinylidene fluoride supported by conducting fabric and thermoplastic polyurethanes (TPU) supported by Ag elastic fabric, are welded into arch structures through ultrasonic welding technique. As the bottom layer of the arch, the TPU/Ag layer with consistent stretchability guarantees the stretchable of the TENG. Therefore, the TENG can collect various types of irregular movements, such as stretching, pressing, and twisting motions, even the combination of the above all motions. Under twisting stretch, the open‐circuit voltage and short‐circuit current of one basic unit can reach up to 170 V and 4.5 µA, respectively. Besides, the welded TENG is tailorable and it still maintains certain output even if it is partially cut or damaged. The continuous arch‐structured TENGs can also be used as self‐powered motion sensors to constantly monitor the intensity and frequency of human body movements. Thus, this work opens up a new idea for preparation of wearable TENG with both multifunction and better comfort. [ABSTRACT FROM AUTHOR]

Implantable flexible mechanical sensors have exhibited great potential in health monitoring and disease diagnosis due to continuous and real-time monitoring capability. However, the wires and power supply required in current devices cause inconvenience and potential risks. Magnetic-based devices have demonstrated advantages in wireless and passive sensing, but the mismatched mechanical properties, poor biocompatibility, and insufficient sensitivity have limited their applications in biomechanical monitoring. Here, a wireless and passive flexible magnetic-based strain sensor based on a gelatin methacrylate/Fe 3 O 4 magnetic hydrogel has been fabricated. The sensor exhibits ultrasoft mechanical properties, strong magnetic properties, and long-term stability in saline solution and can monitor strains down to 50 μm. A model of the sensing process is established to identify the optimal detection location and the relation between the relative magnetic permeability and the sensitivity of the sensors. Moreover, an in vitro tissue model is developed to investigate the potential of the sensor in detecting subtle biomechanical signals and avoiding interference with bioactivities. Furthermore, a real-time and high-throughput biomonitoring platform is built and implements passive wireless monitoring of the drug response and cultural status of the cardiomyocytes. This work demonstrates the potential of applying magnetic sensing for biomechanical monitoring and provides ideas for the design of wireless and passive implantable devices.