Projects

Upcoming Webinar – Making Engineering Welcoming and Accessible for Students with Disabilities

Keshia AccessEngineering, News, Outreach, Projects
Upcoming Webinar – Making Engineering Welcoming and Accessible for Students with Disabilities

Making Engineering Welcoming and Accessible for Students with Disabilities

Check out this upcoming webinar featuring some of our AccessEngineering team!

Date and Time
Wednesday, January 18, 2017
Complimentary 1-hour session! 1-2 pm ET, 12-1 pm CT, 11 am-12 pm MT, 10-11 am PTSponsored by NAPE, STEM Equity Pipeline, and the National Science Foundation

Description

This webinar focuses on strategies for making engineering welcoming and accessible for students with disabilities. The University of Washington presenters run the AccessEngineering program, a nationwide program that works to increase the participation of people with disabilities in engineering academic programs and careers and improve engineering with their expertise. Project staffs engage faculty and students nationwide in efforts to (1) better serve a diverse student body, including students with a broad range of disabilities, in engineering courses and programs, and (2) integrate relevant accessibility-related and universal design content into engineering courses.

Intended Audience Community college, high school and university faculty, counselors, CTE and STEM staff

Objectives Participants will

  1. Gain an understanding of AccessEngineering and strategies to better serve a diverse student body.
  2. Learn methods to integrate disability-related and universal design content into engineering courses.
  3. Become familiar with strategies to make engineering labs and maker spaces accessible.

jan17_webinarpresenters

Registration
Register for this 1-hour complimentary webinar on Wednesday, January 18, 2017. Once you register for the complimentary event, information and instructions about accessing the event will be sent to your email address

 

 

December Toy Hack – Featured on Local News and UW Media

Keshia AccessEngineering, Media, News, Projects

The University of Washington’s new program Husky ADAPT was featured on King 5 news during a toy adaptation workshop.

We adapted toys to allow for a variation of accessible switches to be used by children with diverse abilities. This way, instead of having to use a large degree of force to activate a typical hard to reach ON/OFF switch, children and adults alike can use a switch that works best for them to interact, learn, and most importantly play. This workshop also served to educate engineers about universal design.

What if we didn’t have to adapt toys? What if more toys were accessible off-the-shelf to individuals with diverse abilities? Hopefully all the students will remember these small lessons as they design products and environments in the future.” -Kat Steele

To read about the toy adaptation as posted on the ME Departmental website, follow this LINK or CLICK HERE if on campus.

http://www.king5.com/news/local/seattle/toy-hackers-help-kids-with-disabilities/367898045

 

A daughter, who normally would not be able to activate this toy train, uses her own switch to activate a toy train.

B Soran, L Lowes, KM Steele (2016) “Evaluation of infants with spinal muscular atrophy using convolutional neural networks.” European Conference on Computer Vision

Dr. Steele JournalArticle, UbiquitousRehabilitation , , ,
Experimental set-up with infant positioned below Kinect depth camera.

Peer-reviewed paper at European Conference on Computer Vision:

30-second videos from a depth camera can be used in the evaluation of infants with spinal muscular atrophy.

Experimental set-up with infant positioned below Kinect depth camera.Abstract: Spinal Muscular Atrophy is the most common genetic cause of infant death. Due to its severity, there is a need for methods for automated estimation of disease progression. In this paper we propose a Convolutional-Neural-Network (CNN) model to estimate disease progression during infants’ natural behavior. With the proposed methodology, we were able to predict each child’s score on current behavior-based clinical exams with an average per-subject error of 6.96 out of 72 points (<10 % difference), using 30-second videos in leave-one-subject-out-cross-validation setting. When simple statistics were used over 30-second video-segments to estimate a score for longer videos, we obtained an average error of 5.95 (∼8 % error rate). By showing promising results on a small dataset (N = 70, 2-minute samples, which were handled as 1487, 30-second video segments), our methodology demonstrates that it is possible to benefit from CNNs on small datasets by proper design and data handling choices.

Jessica Zistatsis awarded Mechanical Engineering Fellowship

Keshia Awards, News, Orthoses, Projects

jessicazCongratulations to Jessica for being acknowledged by the Department of Mechanical Engineering for her academic achievements and potential for success within her masters studies.

Jessica is dedicated to creating a pediatric exoskeleton which promotes improved walking patterns during daily life, outside of therapy sessions. This fellowship will allow Jessica to devote more time towards her research and studies. Congrats!