ASSETS. Annual ACM Conference on Assistive Technologies最新文献

Hevelius Report: Visualizing Web-Based Mobility Test Data For Clinical Decision and Learning Support. Hevelius报告：可视化基于网络的移动测试数据，用于临床决策和学习支持。

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2024-10-01 Epub Date: 2024-10-27 DOI: 10.1145/3663548.3688490

Hongjin Lin, Tessa Han, Krzysztof Z Gajos, Anoopum S Gupta

{"title":"Hevelius Report: Visualizing Web-Based Mobility Test Data For Clinical Decision and Learning Support.","authors":"Hongjin Lin, Tessa Han, Krzysztof Z Gajos, Anoopum S Gupta","doi":"10.1145/3663548.3688490","DOIUrl":"10.1145/3663548.3688490","url":null,"abstract":"Hevelius, a web-based computer mouse test, measures arm movement and has been shown to accurately evaluate severity for patients with Parkinson's disease and ataxias. A Hevelius session produces 32 numeric features, which may be hard to interpret, especially in time-constrained clinical settings. This work aims to support clinicians (and other stakeholders) in interpreting and connecting Hevelius features to clinical concepts. Through an iterative design process, we developed a visualization tool (Hevelius Report) that (1) abstracts six clinically relevant concepts from 32 features, (2) visualizes patient test results, and compares them to results from healthy controls and other patients, and (3) is an interactive app to meet the specific needs in different usage scenarios. Then, we conducted a preliminary user study through an online interview with three clinicians who were not involved in the project. They expressed interest in using Hevelius Report, especially for identifying subtle changes in their patients' mobility that are hard to capture with existing clinical tests. Future work will integrate the visualization tool into the current clinical workflow of a neurology team and conduct systematic evaluations of the tool's usefulness, usability, and effectiveness. Hevelius Report represents a promising solution for analyzing fine-motor test results and monitoring patients' conditions and progressions.","PeriodicalId":72321,"journal":{"name":"ASSETS. Annual ACM Conference on Assistive Technologies","volume":"2024 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12239997/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144602405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring Videoconferencing for Older Adults with Cognitive Concerns Using a Dramaturgical Lens. 用戏剧镜头探索有认知问题的老年人视频会议。

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2024-01-01 DOI: 10.1145/3663548.3675647

Ruipu Hu, Ge Gao, Amanda Lazar

引用次数: 0

Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challenges. 理解盲人用户如何处理对象识别错误：策略和挑战。

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2024-01-01 DOI: 10.1145/3663548.3675635

Jonggi Hong, Hernisa Kacorri

{"title":"Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challenges.","authors":"Jonggi Hong, Hernisa Kacorri","doi":"10.1145/3663548.3675635","DOIUrl":"10.1145/3663548.3675635","url":null,"abstract":"Object recognition technologies hold the potential to support blind and low-vision people in navigating the world around them. However, the gap between benchmark performances and practical usability remains a significant challenge. This paper presents a study aimed at understanding blind users' interaction with object recognition systems for identifying and avoiding errors. Leveraging a pre-existing object recognition system, URCam, fine-tuned for our experiment, we conducted a user study involving 12 blind and low-vision participants. Through in-depth interviews and hands-on error identification tasks, we gained insights into users' experiences, challenges, and strategies for identifying errors in camera-based assistive technologies and object recognition systems. During interviews, many participants preferred independent error review, while expressing apprehension toward misrecognitions. In the error identification task, participants varied viewpoints, backgrounds, and object sizes in their images to avoid and overcome errors. Even after repeating the task, participants identified only half of the errors, and the proportion of errors identified did not significantly differ from their first attempts. Based on these insights, we offer implications for designing accessible interfaces tailored to the needs of blind and low-vision users in identifying object recognition errors.","PeriodicalId":72321,"journal":{"name":"ASSETS. Annual ACM Conference on Assistive Technologies","volume":"2024 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11872236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AccessShare: Co-designing Data Access and Sharing with Blind People. AccessShare：与盲人共同设计数据访问和共享。

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2024-01-01 DOI: 10.1145/3663548.3675612

Rie Kamikubo, Farnaz Zamiri Zeraati, Kyungjun Lee, Hernisa Kacorri

引用次数: 0

Enabling Uniform Computer Interaction Experience for Blind Users through Large Language Models. 通过大型语言模型实现盲人用户统一的计算机交互体验。

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2024-01-01 Epub Date: 2024-10-27 DOI: 10.1145/3663548.3675605

Satwik Ram Kodandaram, Utku Uckun, Xiaojun Bi, I V Ramakrishnan, Vikas Ashok

{"title":"Enabling Uniform Computer Interaction Experience for Blind Users through Large Language Models.","authors":"Satwik Ram Kodandaram, Utku Uckun, Xiaojun Bi, I V Ramakrishnan, Vikas Ashok","doi":"10.1145/3663548.3675605","DOIUrl":"10.1145/3663548.3675605","url":null,"abstract":"Blind individuals, who by necessity depend on screen readers to interact with computers, face considerable challenges in navigating the diverse and complex graphical user interfaces of different computer applications. The heterogeneity of various application interfaces often requires blind users to remember different keyboard combinations and navigation methods to use each application effectively. To alleviate this significant interaction burden imposed by heterogeneous application interfaces, we present Savant, a novel assistive technology powered by large language models (LLMs) that allows blind screen reader users to interact uniformly with any application interface through natural language. Novelly, Savant can automate a series of tedious screen reader actions on the control elements of the application when prompted by a natural language command from the user. These commands can be flexible in the sense that the user is not strictly required to specify the exact names of the control elements in the command. A user study evaluation of Savant with 11 blind participants demonstrated significant improvements in interaction efficiency and usability compared to current practices.","PeriodicalId":72321,"journal":{"name":"ASSETS. Annual ACM Conference on Assistive Technologies","volume":"2024 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11707650/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Information Wayfinding of Screen Reader Users: Five Personas to Expand Conceptualizations of User Experiences. 屏幕阅读器用户的信息寻路：扩展用户体验概念的五个角色。

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2024-01-01

J Bern Jordan, Victoria Van Hyning, Mason A Jones, Rachael Bradley Montgomery, Elizabeth Bottner, Evan Tansil

引用次数: 0

Screen Magnification for Readers with Low Vision: A Study on Usability and Performance. 低视力读者的屏幕放大功能：可用性和性能研究

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2023-10-01 Epub Date: 2023-10-22

Meini Tang, Roberto Manduchi, Susana Chung, Raquel Prado

引用次数: 0

Blind Users Accessing Their Training Images in Teachable Object Recognizers. 盲人用户在可教物体识别器中访问自己的训练图像

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2022-10-01 Epub Date: 2022-10-22 DOI: 10.1145/3517428.3544824

Jonggi Hong, Jaina Gandhi, Ernest Essuah Mensah, Farnaz Zamiri Zeraati, Ebrima Haddy Jarjue, Kyungjun Lee, Hernisa Kacorri

{"title":"Blind Users Accessing Their Training Images in Teachable Object Recognizers.","authors":"Jonggi Hong, Jaina Gandhi, Ernest Essuah Mensah, Farnaz Zamiri Zeraati, Ebrima Haddy Jarjue, Kyungjun Lee, Hernisa Kacorri","doi":"10.1145/3517428.3544824","DOIUrl":"10.1145/3517428.3544824","url":null,"abstract":"Teachable object recognizers provide a solution for a very practical need for blind people - instance level object recognition. They assume one can visually inspect the photos they provide for training, a critical and inaccessible step for those who are blind. In this work, we engineer data descriptors that address this challenge. They indicate in real time whether the object in the photo is cropped or too small, a hand is included, the photos is blurred, and how much photos vary from each other. Our descriptors are built into open source testbed iOS app, called MYCam. In a remote user study in (N = 12) blind participants' homes, we show how descriptors, even when error-prone, support experimentation and have a positive impact in the quality of training set that can translate to model performance though this gain is not uniform. Participants found the app simple to use indicating that they could effectively train it and that the descriptors were useful. However, many found the training being tedious, opening discussions around the need for balance between information, time, and cognitive load.","PeriodicalId":72321,"journal":{"name":"ASSETS. Annual ACM Conference on Assistive Technologies","volume":"2022 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008526/pdf/nihms-1869981.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9111608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mobile Phone Use by People with Mild to Moderate Dementia: Uncovering Challenges and Identifying Opportunities: Mobile Phone Use by People with Mild to Moderate Dementia. 轻至中度痴呆患者的手机使用：发现挑战和识别机会：轻至中度痴呆患者的手机使用。

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2022-10-01 Epub Date: 2022-10-22 DOI: 10.1145/3517428.3544809

Emma Dixon, Rain Michaels, Xiang Xiao, Yu Zhong, Patrick Clary, Ajit Narayanan, Robin Brewer, Amanda Lazar

引用次数: 0

Data Representativeness in Accessibility Datasets: A Meta-Analysis. 可访问性数据集的数据代表性：一个元分析。

ASSETS. Annual ACM Conference on Assistive Technologies Pub Date : 2022-10-01 Epub Date: 2022-10-22 DOI: 10.1145/3517428.3544826

Rie Kamikubo, Lining Wang, Crystal Marte, Amnah Mahmood, Hernisa Kacorri

{"title":"Data Representativeness in Accessibility Datasets: A Meta-Analysis.","authors":"Rie Kamikubo, Lining Wang, Crystal Marte, Amnah Mahmood, Hernisa Kacorri","doi":"10.1145/3517428.3544826","DOIUrl":"10.1145/3517428.3544826","url":null,"abstract":"As data-driven systems are increasingly deployed at scale, ethical concerns have arisen around unfair and discriminatory outcomes for historically marginalized groups that are underrepresented in training data. In response, work around AI fairness and inclusion has called for datasets that are representative of various demographic groups. In this paper, we contribute an analysis of the representativeness of age, gender, and race & ethnicity in accessibility datasets-datasets sourced from people with disabilities and older adults-that can potentially play an important role in mitigating bias for inclusive AI-infused applications. We examine the current state of representation within datasets sourced by people with disabilities by reviewing publicly-available information of 190 datasets, we call these accessibility datasets. We find that accessibility datasets represent diverse ages, but have gender and race representation gaps. Additionally, we investigate how the sensitive and complex nature of demographic variables makes classification difficult and inconsistent (e.g., gender, race & ethnicity), with the source of labeling often unknown. By reflecting on the current challenges and opportunities for representation of disabled data contributors, we hope our effort expands the space of possibility for greater inclusion of marginalized communities in AI-infused systems.","PeriodicalId":72321,"journal":{"name":"ASSETS. Annual ACM Conference on Assistive Technologies","volume":"2022 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024595/pdf/nihms-1869788.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9153813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0