Search Results (830)

Compliant mechanisms have contributed to many advances in soft robotics, and there is strong motivation to translate these ideas to assistive devices where adaptive motion at the human interface is required. This work presents novel reconfigurable compliant joints (RCJs) as a parameterized joint element for functional biomimicry in lower-extremity joints for prosthetic knees and ankle–foot orthoses, with concepts that extend to other limb joints. The RCJ uses a rigid hub and outer ring joined by an array of flexible links with centerlines defined by cubic Bézier curves. Link shapes are organized into four Bézier classes (A–D), with base types using 10, 12, or 14 uniformly distributed link slots and variants generated by modifying active-link count and distribution, forming a structured morphology space of 12 configurations for machine design. Dual-extrusion 3D-printed prototypes are characterized by a custom testing apparatus using a 2.2 kN load cell at 25 mm/s over a 0–90° rotation range across six recorded load cycles to measure torque–angle curves and stiffness under large deformations. Angle-dependent stiffness is evaluated over three fixed intervals (0–30°, 30–60°, and 60–90°) to quantify multi-stage behavior. A 2-dimensional corotational frame model and a Simscape Multibody model, including a rolling-contact knee configuration, use the same parameterization to relate geometry, nonlinear mechanics, and system-level motion. Experiments and simulations show multi-stage torque–angle profiles and predictable stiffness modulation across all configurations, with both magnitude and transition angle tunable through Bézier class and active-link distribution, positioning the RCJ as a CAD/CAE-compatible joint architecture for assistive devices or wearable robotic systems and a basis for advancing functional biomimicry in compliant mechanism design. Full article

Poly(lactic acid) (PLA) devices can be functionalized with plant-derived bioactives to introduce antioxidant activity while maintaining manufacturability and cytocompatibility. Here, a polyphenol-rich mango leaf extract (MLE) was obtained by enhanced solvent extraction and incorporated into PLA using supercritical carbon dioxide-assisted impregnation. Two manufacturing sequences were compared: impregnation after three-dimensional (3D) printing of discs and impregnation of filaments prior to printing. Extract yield and radical scavenging capacity were quantified, and impregnation efficiency was assessed as a function of pressure and temperature. Biological performance was evaluated using adipose tissue-derived endothelial colony-forming cells (ECFCs) and adipose tissue-derived mesenchymal stromal cells (MSCs), cultured separately and in co-culture on functionalized substrates. Impregnation after printing provided higher and more reproducible loading while preserving disc geometry, whereas impregnation before printing promoted swelling and printing-associated deformation that compromised structural fidelity. Cell-based analyses supported improved adhesion, spatial distribution, and proliferative status on discs produced by impregnation after printing under low-temperature and high-pressure conditions, without evidence of selective loss of either population in co-culture by flow cytometry. These results support post-print supercritical impregnation as a robust route to generate antioxidant, cell-supportive PLA scaffolds from agricultural by-products with potential relevance for vascular-oriented biomedical applications. Full article

Caring for children with physical disabilities can be a daunting responsibility, often placing significant financial, psychological, social and health-related strains on the primary caregivers. This qualitative study explored the experiences of caregivers caring for children with physical disabilities in the Hardap region of Namibia. Using purposive sampling, twenty caregivers were selected as participants in the study. Data was collected using semi-structured interview schedules. Following the interviews, the data were manually analysed and categorised into distinctive themes and sub-themes and summarised in the final report as verbatim quotations. Study findings reveal that caregivers are motivated and determined to provide optimum care for children with physical disabilities under their care by acquiring assistive devices for them and assisting the children with activities of daily living. However, poverty and the general shortage of assistive devices, mostly wheelchairs, provide adverse conditions that are inimical to the development of children’s functional independence in daily living tasks. The burden of carrying the children was noted to be potentially deleterious to the caregivers’ physical health. The study concluded that providing assistive equipment for the children will ease the caregivers’ burden of care while equalising socioeconomic opportunities for both children with physical disabilities and their caregivers. The study only covered a small sample size in a small geographical area of Namibia. Therefore, interpretation and generalisation of the findings need to account for the specific context in the Hardap region of Namibia. Therefore, there remains scope for conducting further research with a larger sample size and one that is more geographically representative of Namibia. Full article

Background/Objectives: Hearing loss, coupled with the configurations of hearing devices, adds to the complexity of understanding the subjective and personal implications of losing musical fidelity. Hearing music through assistive listening devices significantly impacts music perception and enjoyment, yet research examining music-related quality of life for late-deafened adults is limited. This study aimed to capture late-deafened adults’ experiences related to music and quality of life. Methods: The study administered a cross-sectional survey designed around three established questionnaires: Cochlear Implant Quality of Life, Goldsmiths Musical Sophistication Index, and Music Related Quality of Life. It was completed by 116 late-deafened adults (mean age 65.4 years, with an average of 23.1 years of hearing loss). It was hypothesised that the use of different hearing devices would impact music importance, engagement, enjoyment, and related quality of life in disparate ways. To determine if and how quality of life differed between hearing device users, statistical analyses were stratified across a subgroup of 75 participants with bilateral hearing aids (n = 33; musicians n = 18, and non-musicians n = 15), bilateral cochlear implants (n = 21; musicians n = 5, and non-musicians n = 16), and bimodal configurations (n = 21) musicians n = 8, and non-musicians n = 13). Results: Music remained important for most participants (n = 55, 73%) despite hearing loss. However, regardless of music being valued, only 36 (48%) participants enjoyed music “Always” or “Most of the Time”, while 17 (23%) “Rarely” or “Never” enjoyed it. Bilateral hearing aid users reported the highest, and bilateral cochlear implant users the lowest quality-of-life scores. These effects extended to participation in real-world musical activities: hearing aid users attended more live music events, while bilateral cochlear implant users experienced the greatest reduction in musical activities compared to other hearing device users. Conclusions: Musical quality of life is fundamentally about music enjoyment and engagement and how late-deafened adults integrate music into their everyday life. Hearing loss and hearing devices create a profound disconnect between the capacity to enjoy and engage with music. Musicianship did not guarantee better musical enjoyment or engagement. However, musicians demonstrated greater perseverance when enjoyment was limited, in the hope of improvement. Understanding this allows clinicians to develop effective rehabilitation strategies tailored to different hearing devices and musicianship abilities and set realistic expectations. Full article

The water oxidation reaction represents an essential yet kinetically demanding bottleneck in artificial photosynthesis, requiring a challenging multi-electron/proton transfer process. Remarkably, the native oxygen-evolving complex in photosystem II carries out this reaction with high efficiency in mild conditions. The functionality of the Mn₄CaO₅ cluster that constitutes the active site offers an ideal model for designing active artificial molecular catalysts. In this contribution, we critically summarize the progress of biomimetic Mn-based molecular water oxidation catalysts in terms of three crucial and interrelated aspects: nuclearity-controlled structure design, fine ligand tuning, and novel assistant strategies. Through combining the basic biomimicking methodologies with the rational structural and functional tuning, our work attempts to offer a clear guiding principle for the future design of Mn-based systems toward highly efficient artificial photosynthesis devices and sustainable energy storage. Full article

Background: Auricular keloids and ear helix deformities are undesirable and aesthetically unpleasing deformities that can cause significant patient psychologic and self-esteem problems. Pressure therapy for keloids is well documented to be an effective non-invasive treatment modality. However, current devices lack comfort and aesthetic appeal to deliver the pressure forces required effectively and uniformly. This work aims to highlight some different pressure therapy approaches for the management of keloids and irregularities in the ear helix morphology. Methods: A case series of four patients presenting with auricle keloids of various sizes and at different locations secondary to ear piercing and one case of congenital helix deformity were treated successfully with pressure therapy devices. The device designs varied based on the keloids’ characteristics and patients’ preferences and involved wire-based spring-activated appliances resembling ear rings for moderate keloid lesions, modified double-spring systems for large or elongated lesions, and magnet-based devices. A pair of inert magnetic discs of different diameters was positioned on the anterior and posterior aspects of the keloid lesion. The magnets were then encapsulated in acrylic resin to improve retention and adaptation, and the external surface was masked with gold glitter to enhance aesthetics and patient acceptance. The helix-deformity case was treated following a complete digital workflow integration where the sound contralateral ear was digitally scanned, mirror-imaged and then 3D-printed in resin to produce an ear model based on which an anatomically symmetrical pressure device was constructed. Results: All devices were successfully fitted and well tolerated, with no reported discomfort or adverse reactions. The wire spring devices were effective in reducing a large keloids volume; however, frequent reactivation every two weeks was required to ensure continuous pressure application. Incorporating magnets in the customised design allowed controlled and uniform pressure application to small keloid-lesion morphology, with enhanced aesthetics and improved patient acceptance and compliance. The digitally assisted case achieved near-perfect anatomical symmetry with the contralateral ear, reducing operator dependency and fabrication guesswork. Conclusions: Customised pressure therapy devices, of magnetic and spring-based systems, alongside utilising digital technologies, offer effective, non-invasive management for auricular keloids and irregular ear helices as long as the patient is committed to wearing the device. Full article

The closed kinetic chain is an essential movement method for humans in daily life, and is also important as a training method. However, there have been few studies focusing on the hip adductor muscles. We used electromyography to measure the muscle activity of the hip adductor muscles during walking and standing movements as part of daily living activities, as well as bicycle ergometer exercise and squats. Concerning the role of the adductor muscles, they are thought to stabilize the pelvis during the unilateral support phase when walking, and to act as hip extension and hip alignment adjustment during cycle ergometer exercise. By using electromyography and inertial sensors, the results of this study showed that wearable technologies can be used to quantify neuromuscular function during closed kinetic chain movements. The results serve as a reference for the development of rehabilitation devices, assistive technologies, and computational models that need the simulation of hip joint mechanics. Linking muscle activity data to engineering-based strategies enables precise musculoskeletal assessment and intervention beyond biological observation. Full article

We investigated the effects of manipulating visual information on motor control indicators during the Waiter’s Bow Test. The results suggested that visual information occlusion reduced the maximum flexion angles of the lumbar spine and upper lumbar region. Furthermore, subjects who tested negative under the open-eye condition tested positive under the closed-eye condition. Regarding muscle activity in the rectus abdominis and erector spinae muscles, it was suggested that this activity was not affected by visual information. These findings indicate that visual sensory feedback is one factor influencing lumbar motor control. The integration of electromyography and accelerometer systems in this study highlights the role of wearable sensor technologies in quantifying neuromuscular function in Bioengineering. By restricting visual information, a model for sensory reweighting can be established for the design of biofeedback systems, rehabilitation robotics, and assistive devices. The results of this study demonstrate how sensor-based evaluation and sensory manipulation can inform the engineering of diagnostic and therapeutic technologies for motor control assessment. Full article

Assistive mobility devices for small animals require reliable monitoring to ensure safe and comfortable operation without increasing system complexity or invasiveness. This study presents a low-cost monitoring platform that integrates a laser-induced graphene (LIG) contact-temperature sensor into a passive mobility device for small dogs, supported by a lightweight Internet of Things (IoT) architecture. The system combines contact temperature, ambient temperature, speed, and obstacle distance using an energy-aware acquisition strategy and prioritized wireless transmission for near-real-time monitoring. An unsupervised anomaly detection framework based on Isolation Forest identifies potentially unsafe operating conditions without labeled pathological data by leveraging absolute temperature and the differential feature $\Delta T$ between contact and ambient measurements. Experimental validation was conducted under controlled indoor conditions across six independent sessions with a small-breed dog, including static and dynamic phases to ensure repeatability. The system achieved packet delivery ratios of approximately 95%, with typical end-to-end latencies below 500 ms and worst-case delays below 850 ms. The proposed approach detected localized thermal deviations associated with friction or prolonged contact while remaining robust to normal activity- and environment-driven variations. These results demonstrate the feasibility of integrating LIG-based sensing and unsupervised analytics into assistive animal mobility platforms to enhance safety through continuous, non-invasive monitoring. Full article

Electrochemical sensors for oxyanion detection are widely reported across environmental, industrial, and biological contexts, with recent literature often emphasising material innovation and increasingly low detection limits. Despite this activity, translation beyond laboratory demonstrations remains limited, raising questions about how electrochemical signals are interpreted and validated. In this review, recent electrochemical oxyanion sensors are examined from a measurement-centred perspective, focusing on how signals are generated, conditioned, and calibrated across major sensing strategies, including direct faradaic detection, modified-electrode and electrocatalytic systems, accumulation-based approaches, and enzyme- or mediator-assisted architectures. Rather than cataloguing sensor materials or device configurations, the analysis examines the assumptions underlying commonly reported performance metrics. Across sensing strategies, signal behaviour is frequently governed by interfacial chemistry, surface history, and experimental constraints rather than by invariant properties of the target oxyanion. Consequently, sensitivity, selectivity, and detection limits often reflect context-dependent behaviour within narrowly defined laboratory regimes. By synthesising these patterns, the review identifies recurring interpretive limitations in how electrochemical responses are linked to analyte determination. The resulting framework clarifies the analytical basis of the existing literature and highlights design-relevant constraints and validation practices that must be addressed for electrochemical oxyanion sensors to progress from feasibility demonstrations to robust analytical tools. Full article

In this study, the dyeing kinetics of polyamide fabrics with acid dyes, such as Telon Blue M2R, under both conventional and microwave-assisted heating conditions were comprehensively investigated. While the conventional dyeing reaction was completed in 30 min, microwave-assisted dyeing was performed in the microwave device for 10 min. Dyeing kinetics were investigated as a function of reaction time, reaction concentration and dyeing temperatures. The K/S values (color depth) of the dyed fabrics were correlated with the concentration. A significant reduction in the dyeing process time for polyamide fabric was observed with microwave heating compared to the conventional method. Kinetic analysis revealed that the Pseudo-Second-Order (PSO) kinetic model provides a better fit to the experimental data on the diffusion process of acid dye in polyamide fabrics, as evidenced by higher correlation coefficients (R²) compared to the Pseudo-First-Order (PFO) model. The activation energy of the reaction in dyeing was found to be 63.27 kJ/mol, and the Arrhenius constant was determined as 7.20 × 10¹⁰ L/g·min in conventional media and 18.70 × 10¹⁰ L/g·min in microwave media. The Arrhenius factor in the microwave medium was more than two times higher than in the conventional media. Full article

BCI biosensors enable continuous monitoring of neural activity, but existing systems face challenges in scalability, latency, and reliable integration with cloud infrastructure. This work presents a cloud-aware, real-time cognitive grid architecture for multimodal BCI biosensors, validated at the system level through a full physical prototype. The system integrates the BioAmp EXG Pill for signal acquisition with an RP2040 microcontroller for local preprocessing using edge-resident TinyML deployment for on-device feature/inference feasibility coupled with environmental context sensors to augment signal context for downstream analytics talking to the external world via Wi-Fi/4G connectivity. A tiered data pipeline was implemented: SD card buffering for raw signals, Redis for near-real-time streaming, PostgreSQL for structured analytics, and AWS S3 with Glacier for long-term archival. End-to-end validation demonstrated consistent edge-level inference with bounded latency, while cloud-assisted telemetry and analytics exhibited variable transmission and processing delays consistent with cellular connectivity and serverless execution characteristics; packet loss remained below 5%. Visualization was achieved through Python 3.10 using Matplotlib GUI, Grafana 10.2.3 dashboards, and on-device LCD displays. Hybrid deployment strategies—local development, simulated cloud testing, and limited cloud usage for benchmark capture—enabled cost-efficient validation while preserving architectural fidelity and latency observability. The results establish a scalable, modular, and energy-efficient biosensor framework, providing a foundation for advanced analytics and translational BCI applications to be explored in subsequent work, with explicit consideration of both edge-resident TinyML inference and cloud-based machine learning workflows. Full article

Brain–computer interfaces (BCIs) have great potential for consumer electronics, as they enable the decoding of brain activity to control external devices and assist human–computer interaction. However, current decoding methods for BCIs face several challenges, such as low accuracy, poor stability under electrode shift, and slow processing for real-time use. In this paper, we propose a hybrid decoding framework designed to address the challenges of current EEG decoding methods. Our method combines manifold learning with contrastive learning. The core of our method lies in a dual-manifold model that uses non-negative matrix factorization (NMF) and a contrastive manifold learning framework to extract clear and useful features from brain signals. To improve decoding stability, we introduce a joint training strategy that enhances feature learning. Furthermore, the system is optimized for real-time interaction, reducing the system latency to 100 ms. We collect EEG signals from 15 subjects performing motor execution tasks and 10 subjects performing motor imagery tasks to construct a motor EEG dataset. On this dataset, the proposed method achieves superior decoding performance, reaching F1-scores of 0.7382 for the motor imagery tasks and 0.8361 for the motor execution tasks. Furthermore, the method maintains robustness even with reduced electrode counts and altered spatial distributions, highlighting its potential as a decoding solution for reliable and portable BCI systems. Full article

Arteriosclerosis obliterans (ASO) is associated with impaired walking function and claudication. However, the effects of information and communication technology (ICT)-based wearable interventions on objectively measured gait outcomes in this population have not been determined. In this 12-week intervention, 52 patients with ASO were randomly assigned to an ICT-based wearable-assisted exercise intervention (n = 30) or a control (n = 22) group. All participants wore a triaxial accelerometer–based device on the non-dominant wrist to monitor moderate-to-vigorous physical activity (MVPA), expressed as average min/day. The intervention group received structured exercise guidance, including walking and lower-limb strengthening exercises, and weekly feedback based on device data; the control group received no exercise instruction or feedback. Primary outcomes were gait speed and 6 min walk test (6MWT) distance; secondary outcomes included MVPA and cognitive function. The intervention group showed significant improvements in gait speed and 6MWT distance compared with those in the control group (p < 0.05), indicating enhanced ambulatory function. An exploratory machine learning analysis suggested that gait speed and 6MWT distance are informative variables for functional-status characterization. ICT-based wearable interventions may serve as scalable approaches for functional rehabilitation in ASO; larger, longer-term studies should confirm these effects and clarify the underlying mechanisms. Full article

The increasing use of digital devices by young learners often results in passive content consumption rather than active skill development. This exploratory study examines whether a peer-like Artificial Intelligence (AI) agent can improve the quality of computer-supported collaborative learning. The aim was to assess the impact of a hidden AI-based chatbot on the dynamics and outcomes of group problem-solving in a school setting. A gamified application was developed in which student groups collaborated on challenging tasks. In a controlled experiment, some groups included a hidden AI-based chatbot acting as a peer, programmed to provide Socratic prompts and motivational scaffolding without giving direct answers, while control groups consisted only of human participants. Quantitative and qualitative data, including time to solution, answer correctness, and chat logs, were collected to compare performance and interaction patterns between the two conditions. Given the limited sample size and primarily descriptive analyses, the findings should be interpreted as preliminary. The results suggest differences in collaborative dynamics and problem-solving efficiency between groups assisted by the AI agent and the unassisted control groups. The findings suggest that integrating a hidden, peer-like pedagogical agent may represent a promising approach for supporting collaborative learning processes, enhancing group engagement by subtly guiding discussion without disrupting the natural peer-to-peer dynamic. These results highlight the potential of hidden AI to enhance collaborative learning environments through non-intrusive support. Further research with larger samples is needed to validate these initial observations. Full article