UW Together – Featured Project

Here at the Ability & Innovation Lab we are fortunate to partner with amazing families and people who are our user experts for feedback and ideas when creating new devices and designs. Jayna and her family are fantastic partners in the design project for Jayna, alongside our undergraduate students. The second prototype is now underway to improve the comfort, donning and doffing, and applicability of Jayna’s elbow-driven device to enable the use of her left arm during two handed tasks.

UW Together presents Jayna’s story HERE.

Jayna and Bradley work on bi-manual tasks (two-handed) during Jayna's visit to the Ability and Innovation Lab

Can Technology Make a Difference in Pediatric Rehabilitation? – A NCMRR Webcast

Interested in how technology can be used to make a difference in pediatric rehabilitation? A video cast from the National Center for Medical Rehabilitation Research (NCMRR) discusses the topic in Bethesda MD. The workshop is organized by the Motion Analysis Laboratory and supported by the National Science Foundation and the National Institutes of Health.

The workshop on August 9th, 2016 brought together a group of experts in rehabilitation to discuss how technology can help us to address pressing needs in pediatric rehabilitation. To follow all of the talks this past week and listen to “Can Technology Make a Difference in Pediatric Rehabilitation?”, follow this link, CLICK HERE.

J Wu, BR Shuman, BW Brunton, KM Steele, JD Olson, RPN Rao (2016) “Multistep model for predicting upper-limb 3D isometric force application from pre-movement electrocorticographic features.” IEEE Engineering Medicine & Biology

Example of ECoG recording during upper-extremity force production.

Peer-reviewed paper at IEEE Engineering in Medicine & Biology Annual Conference:

Can we estimate upper-extremity force production from electrocorticographic recordings?

Example of ECoG recording during upper-extremity force production.Abstract: Neural correlates of movement planning onset and direction may be present in human electrocorticography in the signal dynamics of both motor and non-motor cortical regions. We use a three-stage model of jPCA reduced-rank hidden Markov model (jPCA-RR-HMM), regularized shrunken-centroid discriminant analysis (RDA), and LASSO regression to extract direction-sensitive planning information and movement onset in an upper-limb 3D isometric force task in a human subject. This mode achieves a relatively high true positive force-onset prediction rate of 60% within 250ms, and an above-chance 36% accuracy (17% chance) in predicting one of six planned 3D directions of isometric force using pre-movement signals. We also find direction-distinguishing information up to 400ms before force onset in the pre-movement signals, captured by electrodes placed over the limb-ipsilateral dorsal premotor regions. This approach can contribute to more accurate decoding of higher-level movement goals, at earlier timescales, and inform sensor placement. Our results also contribute to further understanding of the spatiotemporal features of human motor planning.

H Choi, TL Wren, KM Steele (2016) “Gastrocnemius operating length with ankle foot orthoses in cerebral palsy.” Prosthetics & Orthotics International

Example of gastrocnemius operating length from one subject with different AFOs.

Journal article in Prosthetics & Orthotics International:

How does the operating length of the gastrocnemius vary with different common AFOs in children with cerebral palsy?

Clinical relevance: Determining whether ankle foot orthoses stretch tight muscles can inform future orthotic design and potentially provide a platform for integrating therapy into daily life. However, stretching tight muscles must be balanced with other goals of orthoses such as improving gait and preventing bone deformities.

Work by Dr. Steele and Ben Shuman featured in The Daily news post

The team found that of the 473 children who had undergone surgery in their current study, those with higher Walk-DMC scores prior to surgery had better treatment outcomes, even after factoring in age and prior treatment.

The Daily, of the University of Washington, posted an article about Dr. Steele and Ben Shuman’s recent work on predicting cerebral palsy treatment outcomes based on motor modules, or muscle synergies. This work is in partnership with Michael Schwartz at Gillette Children’s Specialty Healthcare.  An excerpt from the article is below. To read the article in full, click here.

Ben Shuman, a PhD student in the Steele Lab, smiles while working with electromyography equipment (EMG). Photo credit: Liam Brozik