BACKGROUND: Surgical procedures on the lower extremities often require weight-bearing on crutches as part of the rehabilitation process. Orthopedic elective procedures enable patients to learn the correct use of crutches in a controlled preoperative setting. Digital assistance systems can safely circumvent a shortage of skilled staff and any contact restrictions that may be necessary.
OBJECTIVE: The usability of a newly developed gait training assistant (GTA) for the use of crutches will be evaluated. An intervention group trained to use crutches by the digital trainer will be compared with a control group trained to use crutches conventionally by a physiotherapist.
METHODS: As part of the development and implementation of a novel GTA, 14 patients learned to walk with crutches by completing specific exercises while receiving live feedback. Their movements were detected by a depth sensor and evaluated in real time. Specific parameters (step length, synchronous movement, crutch angle, and crutch distance to the feet) were compared with a control group (n=14) trained to use crutches by physiotherapists. The intervention group was also assessed by a physiotherapist. At the end of the study, the patients completed questionnaires to evaluate the usability of the system (Brooke\'s System Usability Scale score) and patient satisfaction.
RESULTS: All patients trained by the novel GTA were able to use crutches correctly. The intervention group showed significantly better values for crutch angle (mean -6.3°, SD 3.5° vs mean -12.4°, SD 4.5°; P<.001) and crutch position (mean 3.3, SD 5.1 cm vs mean -8.5, SD 4.9 cm; P=.02). Both groups reported that they felt confident in the use of crutches, were able to follow the instructions, and enjoyed the training. Even though the majority (12/14, 86%) preferred physical therapy over a purely digital approach, most participants enjoyed using the system (13/14, 93%) and were interested in trying out other digital assistants (11/14, 79%). The usability of the GTA was rated above average by the majority (9/14, 64%) of the patients.
CONCLUSIONS: The newly designed GTA is a safe method of teaching the use of crutches and is statistically superior to training by a physiotherapist. Even if patients prefer interaction with a physiotherapist over a purely digital approach, digital devices provide a safe and motivating opportunity to learn the essential locomotor skills for rehabilitation.

Food safety has garnered global attention, necessitating advanced methods for the quick and accurate detection of contaminants. Sensors, notable for their ease of use, high sensitivity, and fast analysis, are prominent. Two-dimensional (2D) nanomaterials have been employed to improve sensor performance. Particularly, black phosphorus (BP) stands out with its multifunctional capabilities, attributed to unique layered structure, ultra-high charge mobility, easy surface functionalization, enhanced optical absorption, and tunable direct bandgap. These characteristics suggest that BP could significantly enhance sensor selectivity, sensitivity, and response speed for contaminant detection. Despite numerous studies on BP-based sensors in food safety, few reviews have been comprehensively summarized. Moreover, challenges in BP\'s preparation and stability restrict its wider use. This paper reviews recent research on BP\'s role in food safety, covering preparation, passivation, and applications. Through analysis of challenges and prospects, this review aims to provide insightful guidance for upcoming research in this area.

In recent years, there has been a significant increase in the prevalence of electronic wearables, among which flexible magnetoelectronic skin has emerged as a key component. This technology is part of the rapidly progressing field of flexible wearable electronics, which has facilitated a new human perceptual development known as the magnetic sense. However, the magnetoelectronic skin is limited due to its low sensitivity and substantial field limitations as a wearable electronic device for sensing minor magnetic fields. Additionally, achieving efficient and non-destructive delamination in flexible magnetic sensors remains a significant challenge, hindering their development. In this study, we demonstrate a novel magnetoelectronic touchless interactive device that utilizes a flexible giant magnetoresistive sensor array. The flexible magnetic sensor array was developed through an electrochemical delamination process, and the resultant ultra-thin flexible electronic system possessed both ultra-thin and non-destructive characteristics. The flexible magnetic sensor is capable of achieving a bending angle of up to 90 degrees, maintaining its performance integrity even after multiple repetitive bending cycles. Our study also provides demonstrations of non-contact interaction and pressure sensing. This research is anticipated to significantly contribute to the advancement of high-performance flexible magnetic sensors and catalyze the development of more sophisticated magnetic electronic skins.

The advent of wearable sensing platforms capable of continuously monitoring physiological parameters indicative of health status have resulted in a paradigm shift for clinical medicine. The accessibility and adaptability of such portable, unobtrusive devices enables proactive, personalized care based on real-time physiological insights. While wearable sensing platforms exhibit powerful capabilities for continuously monitoring physiological parameters, device fabrication often requires specialized facilities and technical expertise, restricting deployment opportunities and innovation potential. The recent emergence of rapid prototyping approaches to sensor fabrication, such as laser-induced graphene (LIG), provides a pathway for circumventing these barriers through low-cost, scalable fabrication. However, inherent limitations in laser processing restrict the spatial resolution of LIG-based flexible electronic devices to the minimum laser spot size. For a CO2 laser-a commonly reported laser for device production-this corresponds to a feature size of ∼120 μm. Here, we demonstrate a facile, low-cost stencil-masking technique to reduce the minimum resolvable feature size of a LIG-based device from 120 ± 20 μm to 45 ± 3 μm when fabricated by CO2 laser. Characterization of device performance reveals this stencil-masked LIG (s-LIG) method yields a concomitant improvement in electrical properties, which we hypothesize is the result of changes in macrostructure of the patterned LIG. We showcase the performance of this fabrication method via production of common sensors including temperature and multi-electrode electrochemical sensors. We fabricate fine-line microarray electrodes not typically achievable via native CO2 laser processing, demonstrating the potential of the expanded design capabilities. Comparing microarray sensors made with and without the stencil to traditional macro LIG electrodes reveals the s-LIG sensors have significantly reduced capacitance for similar electroactive surface areas. Beyond improving sensor performance, the increased resolution enabled by this metal stencil technique expands capabilities for scalable fabrication of high-performance wearable sensors in low-resource settings without reliance on traditional fabrication pathways.

Food safety and authenticity analysis play a pivotal role in guaranteeing food quality, safeguarding public health, and upholding consumer trust. In recent years, significant social progress has presented fresh challenges in the realm of food analysis, underscoring the imperative requirement to devise innovative and expedient approaches for conducting on-site assessments. Consequently, cellulose paper-based devices (PADs) have come into the spotlight due to their characteristics of microchannels and inherent capillary action. This review summarizes the recent advances in cellulose PADs in various food products, comprising various fabrication strategies, detection methods such as mass spectrometry and multi-mode detection, sampling and processing considerations, as well as applications in screening food safety factors and assessing food authenticity developed in the past 3 years. According to the above studies, cellulose PADs face challenges such as limited sample processing, inadequate multiplexing capabilities, and the requirement for workflow integration, while emerging innovations, comprising the use of simplified sample pretreatment techniques, the integration of advanced nanomaterials, and advanced instruments such as portable mass spectrometer and the innovation of multimodal detection methods, offer potential solutions and are highlighted as promising directions. This review underscores the significant potential of cellulose PADs in facilitating decentralized, cost-effective, and simplified testing methodologies to maintain food safety standards. With the progression of interdisciplinary research, cellulose PADs are expected to become essential platforms for on-site food safety and authentication analysis, thereby significantly enhancing global food safety for consumers.

The aim of the present study was to analyze changes in young swimmers\' in-water force, performance, kinematics, and anthropometrics during one full competitive season. Twenty-five swimmers (11 girls and 14 boys, 12.04 ± 0.16 years) were assessed over four distinct time points throughout a competitive season. The in-water force of both hands (D, dominant; ND, non-dominant) was retrieved during two bouts of 25 m front crawl allowing the estimation of the symmetry index. The velocity (v25) was calculated from the time to complete the 25 m and considered the performance outcome, while the stroke rate, stroke length, and the stroke index were used as kinematic variables. For anthropometric variables, body mass, stature, arm span and the hand surface area were measured. The in-water force (16-24%) and performance (8%) improved over the competitive season with significant changes in the first macrocycle. The stroke index was the only kinematic variable that changed between M1 and M4 (12.7%), accompanied by a higher asymmetric motion later in the season. A time effect was found in the stature (p < 0.001, ηp 2 = 0.71), the arm span (p < 0.001, ηp 2 = 0.79), and the hand surface area (D = p < 0.001, ηp 2 = 0.63; ND = p < 0.001, ηp 2 = 0.666). Swimming performance showed associations with in-water force, stroke efficiency and anthropometric features in all time points of the season. Thus, the natural anthropometric growth experienced over the season may translate into a more efficient swimming pattern with greater in-water forces that can enhance performance.

Conductive hydrogels, known for their flexibility, biocompatibility, and conductivity, have found extensive applications in fields such as healthcare, environmental monitoring, and soft robotics. Recent advancements in 3D printing technologies have transformed the fabrication of conductive hydrogels, creating new opportunities for sensing applications. This review provides a comprehensive overview of the advancements in the fabrication and application of 3D-printed conductive hydrogel sensors. First, the basic principles and fabrication techniques of conductive hydrogels are briefly reviewed. We then explore various 3D printing methods for conductive hydrogels, discussing their respective strengths and limitations. The review also summarizes the applications of 3D-printed conductive hydrogel-based sensors. In addition, perspectives on 3D-printed conductive hydrogel sensors are highlighted. This review aims to equip researchers and engineers with insights into the current landscape of 3D-printed conductive hydrogel sensors and to inspire future innovations in this promising field.

The solvothermal synthesis of LnCl3.nH2O with terephthalic acid (benzene-1,4-dicarboxylic acid, H2BDC) produced metal-organic frameworks (LnBDC), [Ln2(BDC)3(H2O)4]∞, where Ln = Sm, Eu, Tb, and Dy. The materials obtained were characterized by a number of physico-chemical techniques. The influence of the ionic radius of the lanthanides on the microstructural characteristics of the Ln-MOFs was evaluated by performing Rietveld refinement. The MOFs obtained were tested as fluorescent sensors for numerous cations and anions in water. The highly luminescent EuBDC and TbBDC demonstrated multi-responsive luminescence sensing functions to detect Ag(I), Fe(III), Cr(III), and Cr(VI), which are essential for their environmental applications. By applying the non-linear Stern-Volmer equation, the fluorescent quenching mechanism was determined. The stability of the obtained materials in water in a wide pH range (acidity pH = 4 and alkalinity pH = 9 solutions) was confirmed.

Door access control systems are important to protect the security and integrity of physical spaces. Accuracy and speed are important factors that govern their performance. In this paper, we investigate a novel approach to identify users by measuring patterns of their interactions with a doorknob via an embedded accelerometer and gyroscope and by applying deep-learning-based algorithms to these measurements. Our identification results obtained from 47 users show an accuracy of 90.2%. When the sex of the user is used as an input feature, the accuracy is 89.8% in the case of male individuals and 97.0% in the case of female individuals. We study how the accuracy is affected by the sample duration, finding that is its possible to identify users using a sample of 0.5 s with an accuracy of 68.5%. Our results demonstrate the feasibility of using patterns of motor activity to provide access control, thus extending with it the set of alternatives to be considered for behavioral biometrics.

Wireless sensor networks (WSNs) are essential for a wide range of applications, including environmental monitoring and smart city developments, thanks to their ability to collect and transmit diverse physical and environmental data. The nature of WSNs, coupled with the variability and noise sensitivity of cost-effective sensors, presents significant challenges in achieving accurate data analysis and anomaly detection. To address these issues, this paper presents a new framework, called Online Adaptive Kalman Filtering (OAKF), specifically designed for real-time anomaly detection within WSNs. This framework stands out by dynamically adjusting the filtering parameters and anomaly detection threshold in response to live data, ensuring accurate and reliable anomaly identification amidst sensor noise and environmental changes. By highlighting computational efficiency and scalability, the OAKF framework is optimized for use in resource-constrained sensor nodes. Validation on different WSN dataset sizes confirmed its effectiveness, showing 95.4% accuracy in reducing false positives and negatives as well as achieving a processing time of 0.008 s per sample.