Publications

ASB 2024 Recap

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Steele Lab members, Charlotte Caskey, Victoria (Tori) Landrum, and Megan Ebers, attended the American Society of Biomechanics Annual Meeting (ASB) in Madison, WI from August 5-8, 2024.

Charlotte gave a poster presentation on the “Effect of spinal stimulation and interval treadmill training on gait mechanics in children with cerebral palsy”

Tori also gave a poster presentation on the “Impact of a Resistive Exoskeleton on Fatigue in Children with Cerebral Palsy”

Megan co-hosted a Symposia Session titled, “Can machine learning reveal the next generation of neural and biomechanical processes governing human movement?” with Steele Lab Alumni, Michael Rosenberg. In Megan’s talk, “A machine learning approach to quantify individual gait responses to ankle exoskeletons,” she discussed how neural network-based discrepancy modeling can be used to isolate the dynamics governing changes in gait with ankle exoskeletons.

KM Steele (2023) After Universal Design Book Chapter – “Shaping Inclusive and Equitable Makerspaces”

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Book Chapter in After Universal Design: The Disability Design Revolution, Edited by Elizabeth Guffey

“Makerspaces are often used to help build new assistive technology and increase accessibility; however, many of these spaces and tools remain inaccessible. We need to make sure disabled people can access these spaces and create the products and designs that they actually want.”
– DO-IT Scholar

Dr. Steele was asked to contribute a case study focused on her work with AccessEngineering into Shaping Inclusive and Equitable Makerspaces.

Description: How might we develop products made with and by disabled users rather than for them? Could we change living and working spaces to make them accessible rather than designing products that “fix” disabilities? How can we grow our capabilities to make designs more “bespoke” to each individual? After Universal Design brings together scholars, practitioners, and disabled users and makers to consider these questions and to argue for the necessity of a new user-centered design.

As many YouTube videos demonstrate, disabled designers are not only fulfilling the grand promises of DIY design but are also questioning what constitutes meaningful design itself. By forcing a rethink of the top-down professionalized practice of Universal Design, which has dominated thinking and practice around design for disability for decades, this book models what inclusive design and social justice can look like as activism, academic research, and everyday life practices today.

With chapters, case studies, and interviews exploring questions of design and personal agency, hardware and spaces, the experiences of prosthetics’ users, conventional hearing aid devices designed to suit personal style, and ways of facilitating pain self-reporting, these essays expand our understanding of what counts as design by offering alternative narratives about creativity and making. Using critical perspectives on disability, race, and gender, this book allow us to understand how design often works in the real world and challenges us to rethink ideas of “inclusion” in design.

CMBBE 2024 Recap

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Members of the Steele Lab traveled to Vancouver, BC for the 19th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE) hosted by the University of British Columbia.

PhD candidate, Mackenzie Pitts, gave a poster presentation on “Inferring Unmeasured Inertial Data from Sparse Sensing for Treadmill Running”. Steele Lab Alumni and Post-Doctoral Research Fellow at Emory University, Michael Rosenberg, gave a podium presentation titled “Recurrent Neural Network Gait Signatures Encode Speed-Induced Changes in Post-Stroke Gait Quality.”

In addition to sharing their research at the conference, the Steele Lab enjoyed connecting with fellow biomechanics and biomedical engineering researchers as well as exploring the beautiful campus at UBC.

Spring 2024 CREATE Research Showcase

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The Center for Research and Education on Accessible Technology and Experiences (CREATE) hosted a Research Showcase and Community Day 2024 on May 20th. These events brought industry and community partners — leaders working and living in the disability and accessibility space — together with faculty and student researchers. Co-sponsored by HuskyADAPT. CREATE’s mission is to make technology accessible and to make the world accessible through technology.

Steele Lab members, Alexandra (Sasha), Mia, Kate, and Alisha,  presented posters at the CREATE Research Showcase to highlight design, development & research of technology to support individuals with disabilities.

Mia, Kate, and Alisha presented a poster on “The Switch Kit: bridging the gap in therapeutic toys for children with medical complexities“. This research involved the creation and evaluation of a therapeutic toy named the “Switch Kit,” designed for young children with medical complexities. The kit allows family members and clinicians to customize switches tailored to the unique needs of each child.

Alexandra presented a poster on “Camera-Based Interface for Hand Function Assessment”. Currently, hand function assessment (e.g., joint range of motion) in a clinical setting is done with low-resolution tools and oftentimes in a subjective manner that is time-consuming. With a camera-based interface, we wanted to improve the speed of collecting information about patient’s hand function, improve repeatability and objectivity, and enhance result presentation for both patients and clinicians.

MR Ebers, JP Williams, KM Steele, JN Kutz (2024) “Leveraging arbitrary mobile sensor trajectories with shallow recurrent decoder networks for full-state reconstruction,”

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Journal Article in IEEE Access

Sensing is a fundamental task for the monitoring, forecasting, and control of complex systems. In many applications, a limited number of sensors are available and must move with the dynamics. Currently, optimal path planning, like Kalman filter estimation, is required to enable sparse mobile sensing for state estimation. However, we show that arbitrary mobile sensor trajectories can be used. By adapting the Shallow REcurrent Decoder (SHRED) network with mobile sensors, their time-history can be used to encode global information of the measured high-dimensional state space.

Summary figure of a shallow recurrent decoder network (SHRED) leveraging mobile sensors to reconstruct full state-space estimates from sparse dynamical trajectories. (Left) Sensor trajectory history encodes global information of the spatio-temporal dynamics of the sparsely measured system. In this work, we evaluate three challenging datasets, including forced isotropic turbulence, global sea-surface temperature, and human biomechanics. (Middle) The mobile SHRED architecture can (i) embed the multiscale physics of a system into a compact and low-dimensional latent space, and (ii) provide a mapping from the sparse mobile sensors to a full state estimate. (Right) The high-dimensional and complex system states can be reconstructed, provided training data for the dynamical trajectory of the sensor(s) is available.Aim: We leverage sparse mobile sensor trajectories for full-state estimation, agnostic to sensor path.

Methods: Using modern deep learning architectures, we show that a sequence-to-vector model, such as an LSTM (long, short-term memory) network, with a decoder network, dynamic trajectory information can be mapped to full state-space estimates.

Results: We demonstrate that by leveraging mobile sensor trajectories with shallow recurrent decoder networks, we can train the network (i) to accurately reconstruct the full state space using arbitrary dynamical trajectories of the sensors, (ii) the architecture reduces the variance of the mean-squared error of the reconstruction error in comparison with immobile sensors, and (iii) the architecture also allows for rapid generalization (parameterization of dynamics) for data outside the training set. Moreover, the path of the sensor can be chosen arbitrarily, provided training data for the spatial trajectory of the sensor is available.

Interpretation: The time-history of mobile sensors can be used to encode global information of the measured high-dimensional state space.