Search Results (62)

Background: The rapid expansion of the brain–computer interface for patients with neurological deficits has garnered significant interest, and for patients, it provides an additional route where conventional rehabilitation has its limits. This has particularly been the case for patients who lose the ability to communicate. Circumventing neural injuries by recording from the intact cortex and subcortex has the potential to allow patients to communicate and restore self-expression. Discoveries over the last 10–15 years have been possible through advancements in technology, neuroscience, and computing. By examining studies involving intracranial brain–computer interfaces that aim to restore communication, we aimed to explore the advances made and explore where the technology is heading. Methods: For this scoping review, we systematically searched PubMed and OVID Embase. After processing the articles, the search yielded 41 articles that we included in this review. Results: The articles predominantly assessed patients who had either suffered from amyotrophic lateral sclerosis, cervical cord injury, or brainstem stroke, resulting in tetraplegia and, in some cases, difficulty speaking. Of the intracranial implants, ten had ALS, six had brainstem stroke, and thirteen had a spinal cord injury. Stereoelectroencephalography was also used, but the results, whilst promising, are still in their infancy. Studies involving patients who were moving cursors on a screen could improve the speed of movement by optimising the interface and utilising better decoding methods. In recent years, intracortical devices have been successfully used for accurate speech-to-text and speech-to-audio decoding in patients who are unable to speak. Conclusions: Here, we summarise the progress made by BCIs used for communication. Speech decoding directly from the cortex can provide a novel therapeutic method to restore full, embodied communication to patients suffering from tetraplegia who otherwise cannot communicate. Full article

Recent AI-assisted coding tools, such as GitHub Copilot and Cursor, have enhanced developer productivity through real-time snippet suggestions. However, these tools primarily assist with isolated coding tasks and lack a structured approach to automating complex, multi-step software development workflows. This paper introduces a workflow-centric AI framework for end-to-end automation, from requirements gathering to code generation, validation, and integration, while maintaining developer oversight. Key innovations include automatic context discovery, which selects relevant codebase elements to improve LLM accuracy; a structured execution pipeline using Prompt Pipeline Language (PPL) for iterative code refinement; self-healing mechanisms that generate tests, detect errors, trigger rollbacks, and regenerate faulty code; and AI-assisted code merging, which preserves manual modifications while integrating AI-generated updates. These capabilities enable efficient automation of repetitive tasks, enforcement of coding standards, and streamlined development workflows. This approach lays the groundwork for AI-driven development that remains adaptable as LLM models advance, progressively reducing the need for human intervention while ensuring code reliability. Full article

This study investigates disparities in upper limb motor skills between children with and without Attention Deficit Hyperactivity Disorder (ADHD), employing one-dimensional (1D) and two-dimensional (2D) point-and-click experiments using a mouse and a joystick and introducing one new metric for mouse cursor trajectory analysis. The participant pool comprised 46 children with combined type ADHD and an equivalent number of children without ADHD. The Input Device Evaluation Application (IDEA) system monitored the mouse pointer’s trajectory. Ten trajectory parameters were computed, including Index of Difficulty, Movement Time, Throughput, Missed Clicks, Target Re-Entry, Task Axis Crossing, Movement Direction Change, Movement Variability, Movement Error, Movement Offset, and Sample Entropy. The 2D joystick experiment trajectory parameters analysis conducted using a hierarchical logistic regression model achieved a 78% success rate in identifying children with ADHD. This research sheds light on the motor skill differences associated with ADHD in the context of computer-based tasks, providing valuable insights into potential diagnostic applications and intervention strategies and introducing one new metric makes for a deeper cursor trajectory analysis. Full article

We present TapFix, a cursorless mobile text correction method for touch-sensor displays. Unlike traditional methods, TapFix eliminates the need to position a cursor to make corrections. Instead, the method allows for direct, character-level access, offering easy-to-use swipe gestures on a zoomed-in target word for corrective actions. A user study with 15 participants compared TapFix to two traditional text correction methods on Apple iOS. For each of the three methods, participants completed 100 text correction tasks of four different error types on an Apple iPhone 14 Pro. The TapFix method was on average between $43.0\%$ and $44.1\%$ faster than the existing methods in completing the tasks. Participants also reported experiencing $5.6\%$ to $21.1\%$ lower levels of frustration with TapFix, as indicated by post-experiment NASA TLX and SUS questionnaires, compared to the traditional methods. Additionally, they attributed a level of usability to TapFix that was comparable to the well-established TextMagnifier method. Full article

Maintaining optimal levels of engagement during rehabilitation training is crucial for inducing neuroplasticity in the motor cortex, which directly influences positive rehabilitation outcomes. In this research article, we propose a virtual reality (VR) rehabilitation system that incorporates a steady-state visual evoked potential (SSVEP) paradigm to provide engagement feedback. The system utilizes a flickering target and cursor to detect the user’s engagement levels during a target-tracking task. Eighteen healthy participants were recruited to experience three experimental conditions: no feedback (NoF), performance feedback (PF), and neurofeedback (NF). Our results reveal significantly greater Mu suppression in the NF condition compared to the other conditions. However, no significant differences were observed in performance metrics, such as tracking error, among the three conditions. The amount of feedback between the PF and NF conditions also showed no substantial difference. These findings suggest the efficacy of our SSVEP-based engagement feedback paradigm in stimulating motor cortex activity during rehabilitation. Consequently, we conclude that neurofeedback, based on the user’s attentional state, proves to be more effective in promoting motor cortex activation and facilitating neuroplastic changes. This research highlights the potential of integrating VR rehabilitation with an engagement feedback system for successful rehabilitation training. Full article

In online services, password-based authentication, a prevalent method for user verification, is inherently vulnerable to keyboard input data attacks. To mitigate these vulnerabilities, image-based authentication methods have been introduced. However, these approaches also face significant security challenges due to the potential exposure of mouse input data. To address these threats, a protective technique that leverages the SetCursorPos() function to generate artificial mouse input data has been developed, thereby concealing genuine user inputs. Nevertheless, adversaries employing advanced machine learning techniques can distinguish between authentic and synthetic mouse data, leaving the security of mouse input data insufficiently robust. This study proposes an enhanced countermeasure utilizing Generative Adversarial Networks (GANs) to produce synthetic mouse data that closely emulate real user input. This approach effectively reduces the efficacy of machine learning-based adversarial attacks. Furthermore, to counteract real-time threats, the proposed method dynamically generates synthetic data based on historical user mouse sequences and integrates it with real-time inputs. Experimental evaluations demonstrate that the proposed method reduces the classification accuracy of mouse input data by adversaries to approximately 62%, thereby validating its efficacy in strengthening the security of mouse data. Full article

In physical spaces, pointing interactions cannot rely on cursors, rays, or virtual hands for feedback as in virtual environments; users must rely solely on their perception and experience to capture targets. Currently, research on modeling target distribution for pointing interactions in physical space is relatively sparse. Area division is typically simplistic, and theoretical models are lacking. To address this issue, we propose two models for target distribution in physical space-pointing interactions: the single-target pointing endpoint distribution model (ST-PEDM) and the multi-target pointing endpoint distribution model (MT-PEDM). Based on these models, we have developed a basic region partitioning algorithm (BRPA) and an enhanced region partitioning algorithm (ERPA). We conducted experiments with 15 participants (11 males, and four females) to validate the proposed distribution models and region partitioning algorithm. The results indicate that these target distribution models accurately describe the distribution areas of targets, and the region partitioning algorithm demonstrates high precision and efficiency in determining user intentions during pointing interactions. At target distances of 200 cm and 300 cm, the accuracy without any algorithm is 60.54% and 42.39%, respectively. Using the BRPA algorithm, the accuracy is 72.94% and 68.57%, while, with the ERPA algorithm, the accuracy reaches 84.11% and 82.74%, respectively. This technology can be utilized in interaction scenarios involving handheld pointing devices, such as handheld remote controls. Additionally, it can be applied to the rapid capture control and trajectory planning of drone swarms. Users can quickly and accurately capture and control target drones using pointing interaction technology, issue commands, and transmit data through smart glasses, thereby achieving effective drone control and trajectory planning. Full article

Introduction: Opening the incubator side wall to insert a non-sterile length-measuring device carries the risk of microbial contamination and thermal instability for preterm infants. To reduce this inconvenience, a laser-based length-measuring board is proposed to measure body length from outside the incubator. Methods: This device has two laser-line-shaped cursors which can be pointed to opposite ends of a segment to be measured. It is attached to the outer side of one of the incubator’s side walls in such a manner as to ensure that its axis is parallel to the longitudinal axis of the segment. To validate the measurements made with this model, a calibrated caliper consisting of a conventional rigid length-measuring board with a resolution of 0.05 mm was constructed to serve as a reference. Crown–heel length was measured in a sample of 45 infants, including 32 preterm and 13 term infants of corrected gestational age at the time of measurement. Results: Good intra-observer variability was obtained. Near-perfect statistical agreement was found between measurements with both devices, with concordance correlation coefficients of 0.994 (95% CI: 0.990; 0.996) in preterm infants and 0.994 (95% CI: 0.988, 0.998) in infants at term. The clinical relevance of the agreement between measurements was assessed by a Bland–Altman plot, and the difference may reach clinical relevance (up to 1 cm) but without evidence of proportional bias. Conclusion: The proposed validated laser-based length-measuring board offers a suitable alternative to conventional length-measuring boards for contactless measurement of infant body length. Full article

Background: Many daily activities depend on visual inputs to improve motor accuracy and minimize errors. Reaching tasks present an ecological framework for examining these visuomotor interactions, but our comprehension of how different amounts of visual input affect motor outputs is still limited. The present study fills this gap, exploring how hand-related visual bias affects motor performance in a reaching task (to draw a line between two dots). Methods: Our setup allowed us to show and hide the visual feedback related to the hand position (cursor of a computer mouse), which was further disentangled from the visual input related to the task (tip of the line). Results: Data from 53 neurotypical participants indicated that, when the hand-related visual cue was visible and disentangled from the task-related visual cue, accommodating movements in response to spatial distortions were less accurate than when the visual cue was absent. Conclusions: We interpret these findings with reference to the concepts of motor affordance of visual cues, shifts between internally- and externally-oriented cognitive strategies to perform movements, and body-related reference frames. Full article

Background: Electroencephalogram (EEG) biomarkers with adequate sensitivity and specificity to reflect the brain’s health status can become indispensable for health monitoring during prolonged missions in space. The objective of our study was to assess whether the basic features of the posterior dominant rhythm (PDR) change under microgravity conditions compared to earth-based scalp EEG recordings. Methods: Three crew members during the 16-day AXIOM-1 mission to the International Space Station (ISS), underwent scalp EEG recordings before, during, and after the mission by means of a dry-electrode self-donning headgear designed to support long-term EEG recordings in space. Resting-state recordings were performed with eyes open and closed during relaxed wakefulness. The electrodes representative of EEG activity in each occipital lobe were used, and consecutive PDR oscillations were identified during periods of eye closure. In turn, cursor-based markers were placed at the negative peak of each sinusoidal wave of the PDR. Waveform averaging and time-frequency analysis were performed for all PDR samples for the respective pre-mission, mission, and post-mission EEGs. Results: No significant differences were found in the mean frequency of the PDR in any of the crew subjects between their EEG on the ISS and their pre- or post-mission EEG on ground level. The PDR oscillations varied over a ±1Hz standard deviation range. Similarly, no significant differences were found in PDR’s power spectral density. Conclusions: Our study shows that the spectral features of the PDR remain within normal limits in a short exposure to the microgravity environment, with its frequency manifesting within an acceptable ±1 Hz variation from the pre-mission mean. Further investigations for EEG features and markers reflecting the human brain neurophysiology during space missions are required. Full article

This paper advances real-time cursor control for individuals with motor impairments through a novel brain–computer interface (BCI) system based solely on motor imagery. We introduce an enhanced deep neural network (DNN) classifier integrated with a Four-Class Iterative Filtering (FCIF) technique for efficient preprocessing of neural signals. The underlying approach is the Four-Class Filter Bank Common Spatial Pattern (FCFBCSP) and it utilizes a customized filter bank for robust feature extraction, thereby significantly improving signal quality and cursor control responsiveness. Extensive testing under varied conditions demonstrates that our system achieves an average classification accuracy of 89.1% and response times of 663 milliseconds, illustrating high precision in feature discrimination. Evaluations using metrics such as Recall, Precision, and F1-Score confirm the system’s effectiveness and accuracy in practical applications, making it a valuable tool for enhancing accessibility for individuals with motor disabilities. Full article

(1) Background: Considering the increasing workload of pathologists, computer-assisted methods have the potential to come to their aid. Considering the prognostic role of myocardial fibrosis, its precise quantification is essential. Currently, the evaluation is performed semi-quantitatively by the pathologist, a method exposed to the issues of subjectivity. The present research proposes validating a semi-automatic algorithm that aims to quantify myocardial fibrosis on microscopic images. (2) Methods: Forty digital images were selected from the slide collection of The Iowa Virtual Slidebox, from which the collagen volume fraction (CVF) was calculated using two semi-automatic methods: CIELAB-MATLAB^® and CIELAB-Python. These involve the use of color difference analysis, using Delta E, in a rectangular region for CIELAB-Python and a region with a random geometric shape, determined by the user’s cursor movement, for CIELAB-MATLAB^®. The comparison was made between the stereological evaluation and ImageJ. (3) Results: A total of 36 images were included in the study (n = 36), demonstrating a high, statistically significant correlation between stereology and ImageJ on the one hand, and the proposed methods on the other (p < 0.001). The mean CVF determined by the two methods shows a mean bias of 1.5% compared with stereology and 0.9% compared with ImageJ. Conclusions: The combined algorithm has a superior performance compared to the proposed methods, considered individually. Despite the relatively small mean bias, the limits of agreement are quite wide, reflecting the variability of the images included in the study. Full article

Binary As_xSe_100−x alloys from the border of a glass-forming region (65 < x < 70) subjected to nanomilling in dry and dry–wet modes are characterized by the XRPD, micro-Raman scattering (micro-RS) and revised positron annihilation lifetime (PAL) methods complemented by a disproportionality analysis using the quantum–chemical cluster modeling approach. These alloys are examined with respect to tetra-arsenic biselenide As₄Se₂ stoichiometry, realized in glassy g-As₆₅Se₃₅, glassy–crystalline g/c-As₆₇Se₃₃ and glassy–crystalline g/c-As₇₀Se₃₀. From the XRPD results, the number of rhombohedral As and cubic arsenolite As₂O₃ phases in As-Se alloys increases after nanomilling, especially in the wet mode realized in a PVP water solution. Nanomilling-driven amorphization and reamorphization transformations in these alloys are identified by an analysis of diffuse peak halos in their XRPD patterning, showing the interplay between the levels of a medium-range structure (disruption of the intermediate-range ordering at the cost of an extended-range one). From the micro-RS spectroscopy results, these alloys are stabilized by molecular thioarsenides As₄Se_n (n = 3, 4), regardless of their phase composition, remnants of thioarsenide molecules destructed under nanomilling being reincorporated into a glass network undergoing a polyamorphic transition. From the PAL spectroscopy results, volumetric changes in the wet-milled alloys with respect to the dry-milled ones are identified as resulting from a direct conversion of the bound positron–electron (Ps, positronium) states in the positron traps. Ps-hosting holes in the PVP medium appear instead of positron traps, with ~0.36–0.38 ns lifetimes ascribed to multivacancies in the As-Se matrix. The superposition of PAL spectrum peaks and tails for pelletized PVP, unmilled, dry-milled, and dry–wet-milled As-Se samples shows a spectacular smoothly decaying trend. The microstructure scenarios of the spontaneous (under quenching) and activated (under nanomilling) decomposition of principal network clusters in As₄Se₂-bearing arsenoselenides are recognized. Over-constrained As_6·(2/3) ring-like network clusters acting as pre-cursors of the rhombohedral As phase are the main products of this decomposition. Two spontaneous processes for creating thioarsenides with crystalline counterparts explain the location of the glass-forming border in an As-Se system near the As₄Se₂ composition, while an activated decomposition process for creating layered As₂Se₃ structures is responsible for the nanomilling-driven molecular-to-network transition. Full article

The First-Person Shooter is a very popular genre in electronic sports (esports), where there are different aiming techniques such as Aim Flicking and Aim Tracking. Although the mouse grip is suggested as one of the most important factors in gaming performance, there is a lack of evidence on this topic. Therefore, the purpose of the present study was to determine the performances of three types of mouse grips (palm grip, claw grip, and fingertip grip) in two different tasks (flicking and tracking tasks) by analyzing kinematic and scoring variables. Twenty-two participants performed the tasks on a computer with the same monitor and mouse, each using their preferred grip: palm grip, claw grip, and fingertip grip. The aim400kg was used to perform the tasks, and a camera system (Optitrack’s Flex 3) was used to capture the mouse movement. The results from the flicking task indicated significant differences in the minimum cursor trajectory, with higher values observed in the claw grip compared to both the palm and fingertip grips. However, no significant differences were observed in the tracking task in terms of velocity, acceleration, or hand movement. Moreover, only high correlations were observed in the flicking task between Score and Reaction Time (r = −0.911) and between Score and Total Distance (r = 0.724). In conclusion, the mouse grip does not affect the Aim Flicking or Aim Tracking task performance. This study has revealed interesting results related to performance, including correlations between the Score, Reaction Time, and Total Distance in flicking tasks. Full article

Background: Epigenetic biomarkers in cancer have emerged as promising tools for early detection, prognosis, and treatment response prediction. In cervical cells, hypermethylation of the host and viral HPV-genome increases with the severity of lesions, providing a useful biomarker in the triage of hr-HPV-positive women and during treatment. The present study focuses on evaluating the clinical performance of the FAM19A4/miR124-2 methylation test in a population-based cervical screening program. Methods: Previously collected cervical samples, after bisulfite-converted DNA, were analyzed by PreCursor-M+ kit (distributed by Fujirebio Europe), for DNA methylation. The sensitivity, specificity, and negative/positive predictive values of DNA methylation were compared to histology, colposcopy, the HPV-DNA test, and cytology results. Results: Among the 61-sample set, the specificity of methylation vs. positive histology (≥CIN2) and colposcopy (≥G2) were 87% and 90%, whereas the sensitivity was 50% and 33.3%, respectively. The combination of methylation analysis with standard methods increases diagnostic accuracy. Conclusions: Overall, we found a good specificity of DNA methylation in comparison to currently used techniques. Further larger studies could support the use of FAM19A4/miR124-2 as reliable biomarkers in the prevention of cervical cancer as triage in the screening protocol. Full article