PSST: Enabling Blind or Visually Impaired Developers to Author Sonifications of Streaming Sensor Data

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Venkatesh Potluri, John Thompson, James Devine, Bongshin Lee, Nora Morsi, Peli De Halleux, Steve Hodges, and Jennifer Mankoff. 2022. PSST: Enabling Blind or Visually Impaired Developers to Author Sonifications of Streaming Sensor Data. In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (UIST ’22). Association for Computing Machinery, New York, NY, USA, Article 46, 1–13. https://doi.org/10.1145/3526113.3545700

We present the first toolkit that equips blind and visually impaired (BVI) developers with the tools to create accessible data displays. Called PSST (Physical Computing Streaming Sensor data Toolkit), it enables BVI developers to understand the data generated by sensors from a mouse to a micro: bit physical computing platform. By assuming visual abilities, earlier efforts to make physical computing accessible fail to address the need for BVI developers to access sensor data. PSST enables BVI developers to understand real-time, real-world sensor data by providing control over what should be displayed, as well as when to display and how to display sensor data. PSST supports filtering based on raw or calculated values, highlighting, and transformation of data. Output formats include tonal sonification, nonspeech audio files, speech, and SVGs for laser cutting. We validate PSST through a series of demonstrations and a user study with BVI developers.

The demo video can be found here: https://youtu.be/UDIl9krawxg.

Evan Zhao

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Evan is an undergraduate at University of Washington, majoring in Computer Science. He is passionate about computer graphics and the huge potential of combining graphical programming techniques with fabrication such as 3D printing, machine embroidery, and so on. In the meantime, he is also a member of the UW Reality Lab. He learned advanced knowledge on how to design interactive, efficient, and accessible applications that run in virtual reality, but he also wants to make them physically touchable and perceivable and bring those models to real life. Since started discovering the vast potential in computer fabrication, he has decided to become a part of the pioneers in this field and contribute to the goal of making designs for everybody.

Rapid Convergence: The Outcomes of Making PPE during a Healthcare Crisis

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Kelly Avery Mack, Megan Hofmann, Udaya Lakshmi, Jerry Cao, Nayha Auradkar, Rosa I. Arriaga, Scott E. Hudson, Jennifer Mankoff. Rapid Convergence: The Outcomes of Making PPE During a Healthcare Crisis. [Link to the paper]

The U.S. National Institute of Health (NIH) 3D Print Exchange is a public, open-source repository for 3D printable medical device designs with contributions from clinicians, expert-amateur makers, and people from industry and academia. In response to the COVID-19 pandemic, the NIH formed a collection to foster submissions of low-cost, locally-manufacturable personal protective equipment (PPE). We evaluated the 623 submissions in this collection to understand: what makers contributed, how they were made, who made them, and key characteristics of their designs. We found an immediate design convergence to manufacturing-focused remixes of a few initial designs affiliated with NIH partners and major for-profit groups. The NIH worked to review safe, effective designs but was overloaded by manufacturing-focused design adaptations. Our work contributes insights into: the outcomes of distributed, community-based medical making; the features that the community accepted as “safe” making; and how platforms can support regulated maker activities in high-risk domains.

Christina Zhang

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Christina Zhang is a senior at University of Washington, majoring in Computer Science and Informatics, her research interests are mainly HCI, mHealth, behavioral health, accessibility and social computing.
Her current work involves supporting early identification of mental health issues in adolescents, and software-based solutions to accessible communication in higher education.

In the past, she has worked on a research project that studies how online tests could be leveraged to bridge the gap in the support system of people with cognitive and mental disabilities, the paper she co-authored won the Best Paper Award on ASSETS 2021.

https://www.linkedin.com/in/christina-zhang-03215824b/

Claris Winston

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Claris Winston is a third-year undergraduate studying Computer Science at the Paul. G. Allen Center for Computer Science and Engineering at the University of Washington. She is interested in human-computer interaction and accessibility research, and the applications of machine learning and computer vision to improve accessibility in the field of healthcare/sports medicine. She recently participated in and presented a paper that she co-authored at ICSE 2022. Apart from being involved as a teaching assistant in the Computer Science department, she loves graphic design. One of her designs can be found on the cover of the May 2022 ACS SynBio journal. In her spare time, she loves to bake cakes, compose music, and play the piano.

Currently, in the Make4all lab, she is excited to be working on the embroidered tactile graphics project.

Bo Liu

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Bo is a master’s student in technology innovation at the University of Washington. His research has focused on designing and fabricating novel technologies to be more accessible and affordable for the public. In the Make4all lab, he is working on a tactile graphic project.

Website: https://www.linkedin.com/in/boliu-a4406818b/

Yunqi (George) Wang

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Yunqi (George) Wang is a senior at the University of Washington majoring in Computer Science and Mathematics. He is passionate about making technology more inclusive and considers humans as the primary factor when it comes to design practice. He is currently working on an EMG gesture project for people with disability to have better access to electronic devices.

Chronically Under-Addressed: Considerations for HCI Accessibility Practice with Chronically III People

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Accessible design and technology could support the large and growing group of people with chronic illnesses. However, human computer interactions(HCI) has largely approached people with chronic illnesses through a lens of medical tracking or treatment rather than accessibility. We describe and demonstrate a framework for designing technology in ways that center the chronically ill experience. First, we identify guiding tenets: 1) treating chronically ill people not as patients but as people with access needs and expertise, 2) recognizing the way that variable ability shapes accessibility considerations, and 3) adopting a theoretical understanding of chronic illness that attends to the body. We then illustrate these tenets through autoethnographic case studies of two chronically ill authors using technology. Finally, we discuss implications for technology design, including designing for consequence-based accessibility, considering how to engage care communities, and how HCI research can engage chronically ill participants in research.

Kelly Mack*, Emma J. McDonnell*, Leah Findlater, and Heather D. Evans. In The 24th International ACM SIGACCESS Conference on Computers and Accessibility.

Alexandra (Sasha) Portnova

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Sasha is excited about projects where engineering solutions meet medical needs, specifically those that enable individuals with disabilities to interact with the world around them in a more inclusive environment. In the past, she has worked on developing affordable and customizable orthotic devices for individuals with spinal cord injuries and attempted to simplify control methods for complex prosthetic hands. As a postdoc at UW, Sasha hopes to harness the advancements in metamaterials and smart textiles to create custom solutions for assistance and rehabilitation needs of individuals with disabilities.

Momona Yamagami

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Momona Yamagami is a CREATE postdoc at the Paul G. Allen Center for Computer Science & Engineering at the University of Washington. She is advised by Prof. Jennifer Mankoff. She completed her PhD in Electrical Engineering at the University of Washington advised by Profs. Sam Burden and Kat Steele in 2022.

Her research focuses on modeling and enhancing biosignals-based human-machine interaction to support accessibility and health. She is interested in studying how biosignals can be used to support accessible technology input tailored to an individual’s abilities.

Website: http://momona-yamagami.github.io/