Portable Device Research Articles (Page 1)

Trace detection of copper ions with high specificity is critical for early warning indicators and public health governance due to its involvement in multiple physiological processes within the human body. Unlike previous research that was only based on the localized surface plasmon resonance (LSPR) properties of MoO3-x, this work presents a novel colorimetric sensing platform exploiting the peroxidase-like activity for sensitive copper detection. This mechanism provides higher specificity than conventional methods through the specific coordination of Cu2+ with MoO3, which forms a bond that facilitates electron transfer. Furthermore, Cu and Mo exhibit a synergistic catalytic effect. The strong substrate adsorption affinity of Cu, combined with the stable redox-active sites provided by Mo, results in an optimized electronic configuration and an accelerated catalytic process. This process enhances the generation of reactive oxygen species in the presence of H2O2, thereby catalyzing the oxidation of the 3,3',5,5'-tetramethylbenzidine (TMB) substrate with a colorimetric response. To enhance the analytical reliability and practical applicability, we employed a portable optical device for colorimetric signal analysis and a smartphone-based red-green-blue (RGB) colorimetric analysis platform. These methods show high sensitivity, with detection limits of 4.61 nM (colorimetry), 6.35 nM (portable device), and 9.91 nM (RGB analysis), significantly below the U.S. EPA regulatory limit (20 μM). Validation using real samples (wheat and corn) confirms the platform's robustness in environmental monitoring and food safety applications, offering a cost-effective, rapid and simple method for copper detection.

To investigate the effectiveness of a virtual reality-based rehabilitation (VRBR) program in individuals with Adolescent Idiopathic Scoliosis (AIS) who have undergone posterior fusion surgery (PSF). A total of 28 AIS patients who had undergone PSF surgery were included in the study. Participants were randomly assigned to either the VRBR group (n = 14) or the Control group (n = 14). The VRBR group received a rehabilitation program using the Kinect Xbox 360 for 30min, twice a week, over a period of 6 weeks. The Control group was prescribed a comparable set of exercises to be performed as a home-based program over the same duration. Spinal mobility was assessed using the Modified Schober Test, and respiratory muscle strength was measured with a portable Micro RPM device. Physical activity levels were monitored using a pedometer, kinesiophobia was evaluated using the Tampa Scale for Kinesiophobia (TSK), quality of life was assessed via the Scoliosis Research Society-22 Questionnaire (SRS-22), and spinal balance was evaluated using full-spine radiographs (orthoroentgenograms). In the VRBR group, statistically significant improvements were observed in spinal mobility, MIP, MEP, physical activity level, TSK, and SRS-22 scores (p < 0.0001), as well as in coronal balance parameters including CSVL-C7PL (p = 0.041), sagittal vertical axis (SVA) (p = 0.01), and pelvic tilt (p < 0.0001) when compared to baseline. In contrast, no statistically significant improvements were found in any of the assessed parameters within the Control group (p > 0.05). Between-group comparisons revealed statistically significant improvements in favor of the VRBR group in spinal mobility (p = 0.048), MIP (p = 0.029), and physical activity levels (p < 0.01). The findings suggest that VR-based rehabilitation contributes positively to postoperative outcomes in AIS, with notable advantages in terms of spinal mobility, respiratory function, and physical activity.

Background: Tropical estuaries are vital ecosystems that, despite being affected by human activities, remain under-researched. Aims: This study evaluated the phytoplankton diversity and trophic pollution status of the Bandama Estuary in Côte d'Ivoire and the Volta Estuary in Ghana, both connected to significant rivers. Methodology: A total of fifteen sampling sites were chosen, with six in the Bandama Estuary and nine in the Volta Estuary. Physico-chemical parameters were measured using a Hanna HI9829 portable multiparameter device, while microalgae were collected using a 20 μm mesh plankton net and a 1.5 L Niskin bottle. Phytoplankton identification and counting were performed with a Nikon Eclipse 0.90 Dry photonic microscope. The collection was carried out from February to July 2023 in the estuaries of the Volta and Bandama. Results: In the Volta Estuary, 30 phytoplankton taxa were identified, primarily from three phyla: 20 Chlorophyta (67%), 7 Bacillariophyta (23%), and 3 Euglenophyta (10%). The Chlorophyceae class was the most abundant, with 2,400,000 cells/L (35%). Conversely, the Bandama Estuary revealed 52 phytoplankton taxa across five phyla, with Cyanophyta dominating at 92%. The Bandama Estuary showed hypoxic dissolved oxygen levels (0.72 mg/L), while the Volta Estuary was well-oxygenated (6.23 mg/L). The trophic index calculated for both estuaries indicates a eutrophic environment. In contrast, the Volta Estuary shows a score of 15, indicating moderate organic pollution, providing a foundation for future biomonitoring of anthropogenic pollution in the region. Conclusion: This research highlights the ecological significance of these estuaries and the need for ongoing studies to understand their health and resilience.

Background: Portable devices that capture 1-lead ECG, coupled with AI tools, hold the potential to scale screening for structural heart disease (SHD) in communities. We previously developed ADAPT-HEART, a noise-adapted, 1-lead AI-ECG algorithm to detect SHD that could be scaled to portable devices. Aim: In this investigator-initiated and independent ACCESS-SHD Study, we prospectively evaluated ADAPT-HEART in detecting SHD from 1-lead ECGs obtained with a real-world portable device, the AliveCor KardiaMobile 6L device. Methods: We prospectively enrolled 600 participants receiving a transthoracic echocardiogram (TTE) as part of their clinical care at Yale New Haven Hospital. Consenting participants captured a 30-second, 1-lead ECG using the KardiaMobile 6L device in the echo laboratory. We accessed the 1-lead data via an automated application programming interface (API) and deployed ADAPT-HEART. The model's output probability represented the risk of SHD, defined as a composite of LVEF &lt;40%, severe left-sided valvular disease, or severe LVH (IVSd &gt;15 mm + moderate or severe LV diastolic dysfunction) on TTE. The output probability of SHD was used to calculate the model’s AUROC for detecting SHD. Results: Of 600 participants, 597 (99.5%) successfully recorded a portable ECG and were included in the analysis. The median age was 62 years [IQR, 46–71], and 309 (51.8%) were women. There were 21 (5.3%) participants with SHD, including 15 (2.6%) with LVEF &lt;40%, 5 (1.0%) with severe valvular disease, and 1 (0.2%) with severe LVH. ADAPT-HEART demonstrated an AUROC of 0.913 (95% CI, 0.837–0.989) for detecting SHD from 1-lead ECGs obtained with the KardiaMobile 6L. The AI-ECG model had a sensitivity of 85.7% and a specificity of 88.4% in detecting SHD. With a SHD prevalence of 5.3% in the study population, the model demonstrated a PPV of 29.0%, thereby enhancing the yield of TTE in identifying individuals with SHD by more than 5-fold. Conclusions: ADAPT-HEART, a noise-adapted AI model for 1-lead ECGs, can detect a broad range of SHDs using a 30-second, 1-lead ECG obtained with the KardiaMobile 6L portable device. The portability of these devices, coupled with a validated and accurate SHD detection algorithm, can enable large-scale screening for SHDs in the community.

Sensitive detection of multiplex bacteria based on finger driven microfluidics and recombinase aided amplification.

Sensing strips for on-site determination of ochratoxin A in milk and wine.

Plasmonic sensors for point of care diagnostics.

One fell swoop strategy to detect and degrade malathion by an ALP-sensitive and Pt-Co-N-C nanozyme-enhanced chemiluminescent 3D μPAD.

A portable oral positive expiratory pressure device effectively improves lung aeration and oxygenation in post-operative atelectasis.

A portable microfluidic chip device integrated with a real-time CTCs detection model for point-of-care testing of early-stage lung cancer

A portable smartphone-based electrochemiluminescence device integrated with bipolar electrode detection chip for multi-target respiratory pathogen detection.

Portable semisolid extrusion device for the production of personalized medicines in diverse settings.

Ultra compact multi-channel particle sampler for personal exposure of particle chemical composition at hourly resolution.

A portable device for real-time continuous drug monitoring in freely moving small animals.

The Bafing River, the main right-bank tributary of the Sassandra River, was investigated to characterize its physicochemical parameters and phytoplankton community. Located in northwestern Côte d’Ivoire, this study aimed to assess the diversity, composition, and spatial distribution of phytoplankton in the Sassandra River basin. Physicochemical parameters (pH, temperature, conductivity, and dissolved oxygen) were measured in situ using a HANNA portable multiparameter device (model HI9828), while phytoplankton samples were collected with a 20 µm mesh plankton net from April to December 2022. Qualitative analysis identified 82 taxa distributed across 35 genera, 17 families, 12 orders, 9 classes, and 5 phyla. Chlorophyta (56.09%) and Euglenophyta (17.07%) were the most diverse groups, followed by Heterokontophyta (14.63%), Cyanoprokaryota (9.75%), and Dinophyta (3.65%). Spatially, the highest algal densities were observed at the Gorlo station and Lac Ranch (downstream), while the lowest densities were recorded upstream, notably at the Min, Bafing, and Godigui stations. Physicochemical analysis indicated relatively cool, acidic, and relatively oxygenated waters. These results provide an essential reference for ecological monitoring and water quality assessment of the Bafing River, particularly under anthropogenic pressures such as artisanal gold mining.

To develop a training model for contrast-enhanced ultrasound (CEUS)-guided biopsy during the learning phase.An in-vitro model using porcine liver with olive-shaped lesions marked by pepper seeds was employed to simulate tumor biopsies. After targeted injection of sulfur-hexafluoride microbubbles as contrast agent, both native and CEUS-guided biopsies were performed using 18G core needles. Linear transducers of a high-end ultrasound device (3-15 MHz) and of a portable handheld ultrasound device (3-12 MHz) were utilized. Freehand biopsies were conducted both in-plane and out-of-plane. Twelve procedures each were performed by experienced and novice examiners on lesions located at depths of 2-4 cm, with comparisons made regarding procedure duration and image quality. Image and procedure quality were assessed by two independent readers using a scale from 0 (insufficient) to 5 (excellent).CEUS enabled more precise localization and marking of poorly delineated lesions, thereby facilitating targeted biopsy, even in deeper tissue layers. Particularly under challenging acoustic conditions, CEUS improved the planning and execution of interventions for both experienced and novice users when using handheld ultrasound devices. In this in-vitro study, CEUS provided a significant advantage for experienced users working with handheld systems (p < 0.05), whereas its integration into high-end systems did not lead to a significant difference in procedure time (p > 0.05). Novice users, however, benefited significantly from CEUS when using high-end systems (p < 0.01).CEUS-marked lesions in the in-vitro model allow for realistic training of targeted punctures and biopsies - even for lesions not clearly visible in B-mode imaging. Despite the absence of circulation, the contrast effect remains sufficiently stable to practice CEUS techniques under conditions closely resembling clinical practice. This supports the safe application of portable ultrasound systems in interventional procedures. · In-vitro model realistically simulates CEUS-guided liver biopsy procedures. · CEUS enhances delineation of target lesions in inhomogeneous liver parenchyma. · CEUS improves lesion visibility for inexperienced examiners. · Model is suitable for teaching CEUS-guided biopsy techniques. · Brandenstein MK, Becker C, Kupke LS et al. In Vitro Model Employing Contrast-enhanced Ultrasound (CEUS) for the Simulation of Radiologic Intraoperative Liver Punctures and Biopsies. Rofo 2025; DOI 10.1055/a-2719-5885.

Given the high toxicity of ochratoxin A (OTA) and its consequent threat to human health, the development of a portable OTA detection device is of great significance. Enzymatic biofuel cells (EBFCs) have been extensively demonstrated as portable self-powered devices without any external power supply, but self-powered detection of OTA by EBFCs has not been reported. Herein, we report a sensitive self-powered OTA sensor by integrating a target-triggered hybridization chain reaction (HCR) with a glucose/oxygen biofuel cell. OTA binding to a hairpin-locked aptamer opens the hairpin structure, exposing an HCR initiator strand. This initiator triggers HCR amplification, generating long double-stranded DNA products with numerous side strands. Subsequent strand displacement between these HCR side strands and glucose oxidase (GOD)-tagged double-stranded DNA releases GOD-tagged single-stranded DNA probes. These DNA probes hybridize with complementary DNA strands immobilized on the electrode surface, facilitating efficient immobilization of GOD molecules on the anode. With increasing OTA concentration, the GOD loading at the bioanode increases, enabling sensitive self-powered OTA detection. The self-powered sensor achieves a linear detection range from 1 pg mL-1 to 5 ng mL-1 and a detection limit of 0.7 pg mL-1. This study provides a promising portable platform for OTA detection.

ABSTRACT Characterizing the subsurface structure of the railway subgrade is essential for addressing irregularities and settlements effectively. This study introduces a two-dimensional nonlinear inversion method to reconstruct the material properties of ballasted railway subgrades using velocity response measurements obtained from the railway surface. Elastic waves are generated using a light-falling weight deflectometer (LFWD), a portable ground-impact device, and the responses are captured by geophones for full-waveform inversion (FWI). The FWI process employs perfectly matched layers (PML) to truncate the semi-infinite subgrade domain, minimizing artificial boundary reflections during wave simulation. The inversion is formulated as a partial differential equation-constrained optimization problem, where the elastic moduli within the PML-truncated domain are iteratively refined by minimizing a Lagrangian functional. The Lagrangian integrates a least-squares objective and regularization terms, combined with the weak enforcement of PML-augmented elastic wave equations via Lagrange multipliers. A total variation regularization scheme is used to alleviate the ill-posedness of the inverse problem. The resulting Karush–Kuhn–Tucker (KKT) optimality conditions are solved to update the Lamé parameters in the reduced space of control variables. The methodology is demonstrated with detailed data acquisition setups and layouts involving the LFWD and geophones. The reconstructed profiles of Lamé parameters and shear wave velocities are shown to align closely with results from conventional lightweight deflectometer tests and spectral analysis of surface wave implementations, underscoring the method’s feasibility and accuracy.

Tomato leaf diseases pose a significant threat to global food security, necessitating accurate and efficient detection methods. This paper introduces the Tomato Leaf Disease Visual Language Model (TLDVLM), a novel approach based on the BLIP-2 architecture enhanced with Low-Rank Adaptation (LoRA), for precise classification of 10 distinct tomato leaf diseases. Our methodology integrates a sophisticated image preprocessing pipeline, utilizing GroundingDINO for robust leaf detection and SAM-2 for pixel-level segmentation, ensuring that the model focuses solely on relevant plant tissue. The TLDVLM leverages the powerful multimodal understanding of BLIP-2, with LoRA applied to its Q-Former module, enabling parameter-efficient fine-tuning without compromising performance. Comparative experiments demonstrate that the TLDVLM significantly outperforms baseline models, including CLIP-LoRA and ConvNeXT-tiny, achieving an accuracy of 97.27%, a precision of 0.9587, a recall of 0.9789, and an F1-score of 0.9681. Beyond classification, the finetuned TLDVLM checkpoints are integrated into a practical application for new image inference. This application displays the raw and segmented images, the predicted disease, and offers functionalities to fetch comprehensive information on disease causes and remedies using external APIs (e.g., OpenAI), with an option to download a PDF summary for offline access on a portable device. This research highlights the potential of LoRA-adapted Vision-Language Models in developing highly accurate, efficient, and user-friendly agricultural diagnostic tools.

This paper presents the design and performance of Table ASSIST-EW, a portable adaptable user-friendly cable-driven device that can be used on a table to support elbow and wrist exercises. This device is intended for older adults who experience arm weakness due to aging. Table ASSIST-EW has been developed based on results from testing and practical insights from biomechanics and robotics to address challenges in human–robot interaction that limit the use of assistive technologies. Table ASSIST-EW is designed to assist natural arm movements during motion exercise and rehabilitation, making the motion assistance easy and easily engaged for users. The design process is explained starting from identifying user needs up to the creation of a prototype. A key feature of Table ASSIST-EW is its cable-driven actuation system. The design is inspired by a previous device, L-CADEL, which went through several design revisions. The lessons learned from L-CADEL’s development and test experiences suggested design solutions for Table ASSIST-EW’s structure, function, and use. This paper discusses the background, design requirements, system development, and performance evaluation. The results show that the Table ASSIST-EW device meets important goals in usability and functionality, making it a promising solution for robotic rehabilitation and motion exercise for the elderly.