Purpose: This paper reports on research aimed at advancing understanding haptic capability and needs of users with low vision. The objective is to apply this understanding to the design of haptic-incorporated user interfaces.
Method: Study 1 investigated the haptic perception between sighted participants and those with low vision through the magnitude estimation technique, and Study 2 explored the degree to which similar user interface needs were observed among the two vision groups.
Results: Overall, our findings indicate there was no significant difference between the two vision groups in terms of haptic perception and user interface needs. A few differences in user interface preference did exist, however, and designers should take these into account.
Conclusions: Participants with low vision were a group who relied on their vision in everyday life instead of touch. Thus, their haptic capability was less likely to be enhanced via brain plasticity, which probably contributed to no significant difference in haptic-incorporated user interface needs.
Implications For Rehabilitation: No significant different haptic capability and haptic user interface (UI) needs exists between cited participants and those with low vision. UI designers should take into consideration that a certain range of magnitude/type of haptic feedback is available to accommodate preferences of both vision groups, which would ultimately increase the likelihood of successfully developing universal designs.
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http://dx.doi.org/10.3109/17483107.2013.769121 | DOI Listing |
Viruses
December 2024
Beijing Youcare Kechuang Pharmaceutical Technology Co., Ltd., Beijing 100176, China.
Human respiratory syncytial virus (RSV) remains a significant global health threat, particularly for vulnerable populations. Despite extensive research, effective antiviral therapies are still limited. To address this urgent need, we present AVP-GPT2, a deep-learning model that significantly outperforms its predecessor, AVP-GPT, in designing and screening antiviral peptides.
View Article and Find Full Text PDFPharmaceutics
January 2025
Centre for Public Health, Institute of Clinical Sciences, School of Medicine, Queen's University Belfast, Belfast BT7 1NN, UK.
Background/objectives: The visual acuity (VA) outcomes after the first and second years of anti-vascular endothelial growth factor (anti-VEGF) treatment in patients with diabetic macular oedema (DMO) were evaluated, and the factors associated with treatment success were investigated.
Methods: Using Medisoft electronic medical records (UK), this retrospective cohort study analysed VA outcomes, changes, and determinants in DMO patients at year 1 and year 2 after initial anti-VEGF injection. Descriptive analysis examined baseline demographics and clinical characteristics, while regression models were used to assess associations between these factors and changes in VA.
Sensors (Basel)
January 2025
Key Laboratory of Modern Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Nanjing Institute of Agricultural Mechanization, Nanjing 210014, China.
To address several challenges, including low efficiency, significant damage, and high costs, associated with the manual harvesting of , in this study, a machine vision-based intelligent harvesting device was designed according to its agronomic characteristics and morphological features. This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate .
View Article and Find Full Text PDFSensors (Basel)
January 2025
Space Robotics Research Group (SpaceR), Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, L-1855 Luxembourg, Luxembourg.
Malaria remains a global health concern, with 249 million cases and 608,000 deaths being reported by the WHO in 2022. Traditional diagnostic methods often struggle with inconsistent stain quality, lighting variations, and limited resources in endemic regions, making manual detection time-intensive and error-prone. This study introduces an automated system for analyzing Romanowsky-stained thick blood smears, focusing on image quality evaluation, leukocyte detection, and malaria parasite classification.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Electronics, Telecommunications and Information Technologies, Polytechnic University Timisoara, 300223 Timisoara, Romania.
Low-light image enhancement (LLIE) techniques improve the performance of image sensors by enhancing visibility and details in poorly lit environments and have significantly benefited from recent research into Transformer models. This work presents a novel Transformer attention mechanism inspired by the Kolmogorov-Arnold representation theorem, incorporating learnable non-linearity and multivariate function decomposition. This innovative mechanism is the foundation of KAN-T, our proposed Transformer network.
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