Publications

NSF Convergence Accelerator | Inclusion in the Workplace

Dr. Steele AccessEngineering, Presentation , , , ,

The NSF Convergence Accelerator on Accelerating Disability Inclusion in Workplaces through Technology starts on May 20th.


Title slide of Dr. Steele's talk "Ideas for Inclusion" on a purple background.

 

The goals for this workshop are to identify pathways for technology to solve or mitigate accessibility and inclusion challenges in current and emerging workplaces. As an NSF Convergence Accelerator, participants will seek to identify pathways that could be  pursued by multidisciplinary teams to get solutions at least to a prototype stage in 3-5 years. The long-term goals from this workshop are to set in motion paradigm shifts that brings the percentage of individuals with disabilities participating in the workforce closer to the general population.

Dr. Steele will be presenting some ideas on inclusion in the workplace – from work environments to transportation to workforce development.

Slides

Download PDF of slides.

Email Dr. Steele (kmsteele – at – uw – dot – edu) with questions, comments, or suggestions.

HA Feldner, C Papazian, KM Peters, CJ Cruetzfeldt, KM Steele (2021) “Clinical Use of Surface Electromyography to Track Acute Upper Extremity Muscle Recovery after Stroke: A Descriptive Case Study of a Single Patient”

Elijah JournalArticle, News, Publications , , , ,

Journal Article in Applied System Innovation:

This work highlights the potential of wearable technologoies to monitor muscle activity changes during stroke recovery in acute clinical settings and their importance for motivation and understanding of progression from the survivor’s point of view: ‘I was hopeful that it would show signs of things that are occurring when I couldn’t physically feel it…if you had other scientific evidence that things were happening, even beyond their notion that it would, it gives you a lot of hope. You just have to be patient, and it’s harder to take when someone tells you, but easier to understand if someone actually shows you’.

Left image depicts arm with pads placed over muscle with right pictures depicting similar image

Aim: Describe the use of wireless sEMG sensors to examine changes in muscle activity during acute and subacute phases of stroke recovery, and understand the participant’s perceptions of sEMG monitoring.

Method: Muscle activity was tracked by five wireless sEMG sensors beginning three days post-stroke and continued through discharge from inpatient rehabilitation. Activity logs were completed each session, and a semi-structured interview occurred at the final session with three- and eight-month follow-up sessions.

Results: The longitudinal monitoring of muscle and movement recovery in the clinic and community was feasible using sEMG sensors. The participant and medical team felt monitoring was unobtrusive, interesting, and motivating for recovery, but desired greater in-session feedback to inform rehabilitation.

Interpretation: This work highlights that barriers in equipment and signal quality still exist, but capitalizing on wearable sensing technology in the clinic holds promise for enabling personalized stroke recovery.

2020 Center for Translational Muscle Research

Dr. Steele MotorControl, Orthoses, Outreach, Presentation , , , , ,

How can we decipher human movement?

CTMR: White text on purple background, UW Center for Translational Muscle ResearchOur skeletal muscles have amazing structure. They provide elegant and efficient actuation to move and explore our worlds. But how do we understand how muscles produce movement?

Dr. Steele presents at the inaugural research symposium for the University of Washington Center for Translational Muscle Research. Her presentation shares examples for how we can use musculoskeletal simulation as a tool to connect muscle biology, dynamics, and mobility.

Slides | Transcript

MC Rosenberg, BS Banjanin, SA Burden, KM Steele (2020) “Predicting walking response to ankle exoskeleton using data driven models”

Elijah JournalArticle, News , , , , , ,

Journal Article in The Royal Society:

This work highlights the potential of data-driven models grounded in dynamical systems theory to predict complex individualized responses to ankle exoskeletons., without requiring explicit knowledge of the individual’s physiology or motor control

silhouette walking on left with purple lines and projections on right elipsoids and colored spheres

Aim: Evaluate the ability of three classes of subject-specific phase-varying (PV) models to predict kinematic and myoelectric responses to ankle exoskeletons during walking, without requiring prior knowledge of specific user characteristics.

Method: Data from 12 unimpaired adults walking with bilateral passive ankle exoskeletons were captured. PV, linear PV (LPV), and nonlinear PV (NPV) models leveraged Floquet theory to kinematics and muscle activity in response to three exoskeleton torque conditions.

Results: The LPV model’s predictions were more accurate than the PV model when predicting less than 12.5% of a stride in the future and explained 49–70% of the variance in hip, knee and ankle kinematic responses to torque. The LPV model also predicted kinematic responses with similar accuracy to the more-complex NPV model. Myoelectric responses were challenging to predict with all models, explaining at most 10% of the variance in responses.

Interpretation: This work highlights the potential of data-driven PV models to predict complex subject-specific responses to ankle exoskeletons and inform device design and control.