Gillette

Dr. Alyssa Spomer on “Gears of Progress” Podcast

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Gears of Progress Episode 7 featured Alyssa Spomer on biofeedback tech to improve motor control ankle exoskeletons, and work as a clinical scientist at Gillette Children's Hospital.“Gears of Progress” Episode Seven featured Steele Lab Alumni, Dr. Alyssa Spomer on biofeedback tech to improve motor control ankle exoskeletons, and work as a clinical scientist at Gillette Children’s Hospital.

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Name: Gears of Progress

Platforms: Spotify, Apple Podcasts, Amazon Music, Castbox

Release frequency: bi-weekly on Fridays

Theme: Podcast about research and innovations in rehabilitation engineering and assistive technologies aimed to improve accessibility for people with disabilities. Every episode will feature engineers, medical professionals, end-users, and organizations who focus on improving the health and well-being of individuals with disabilities. We will be covering topics such as emerging tech, outcome measures, medical practice, public policy, accessibility education, and so much more!

Twitter: https://twitter.com/GearsOfProgress

Spasticity Research Award Nominations

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Nicole Zaino (wearing glasses) poses on campus

Walking takes energy – but for kids with cerebral palsy, walking can be exhausting. The average child with cerebral palsy consumes two times the amount of energy during walking compared to typically-developing peers – that is the equivalent of jogging or climbing stairs!

The reasons for why walking takes so much energy for children with cerebral palsy remains largely unknown. The extra muscle activity caused by spasticity has often been theorized as a large contributing factor. If this was true, we would expect that treatments that reduce spasticity, like selective dorsal rhizotomy, could dramatically reduce energy during walking.

Led by Nicole Zaino, a new PhD student in the lab, and our collaborator Mike Schwartz at Gillette Children’s Specialty we have been investigating this question. By analyzing energy consumption for children with cerebral palsy who underwent rhizotomy and matched peers with cerebral palsy, we were determined that reducing spasticity does not lead to dramatic decreases in energy consumption.

This research has been nominated as a finalist for two awards at the International Society of Biomechanics Conference. This work was selected as one of 5 finalist for the Clinical Biomechanics Award. Nicole will also present as one of the finalists for the David Winter Young Investigator Award. The final awards will be announced at the conference in Calgary the first week of August. Good luck Nicole!

You can learn more about the study and read the preprint on BioRxiv:

Spasticity reduction in children with cerebral palsy is not associated with reduced energy consumption during walking

BR Shuman, MH Schwartz, KM Steele (2017) “Electromyography Data Processing Impacts Muscle Synergies during Gait for Unimpaired Children and Children with Cerebral Palsy.” Frontiers in Computational Neuroscience

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Example data from a representative TD participant. Left: EMG data processed with varying LP filter cutoffs. Center: Synergy weights and activations. Right: Total variance accounted for by n synergies. Total variance accounted for by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency.

Journal article in Frontiers in Computational Neuroscience:

Filtering parameters impact the results from muscle synergy analyses.

AExample data from a representative TD participant. Left: EMG data processed with varying LP filter cutoffs. Center: Synergy weights and activations. Right: Total variance accounted for by n synergies. Total variance accounted for by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency.bstract: Muscle synergies calculated from electromyography (EMG) data identify weighted groups of muscles activated together during functional tasks. Research has shown that fewer synergies are required to describe EMG data of individuals with neurologic impairments. When considering potential clinical applications of synergies, understanding how EMG data processing impacts results and clinical interpretation is important. The aim of this study was to evaluate how EMG signal processing impacts synergy outputs during gait. We evaluated the impacts of two common processing steps for synergy analyses: low pass (LP) filtering and unit variance scaling. We evaluated EMG data collected during barefoot walking from five muscles of 113 children with cerebral palsy (CP) and 73 typically-developing (TD) children. We applied LP filters to the EMG data with cutoff frequencies ranging from 4 to 40 Hz (reflecting the range reported in prior synergy research). We also evaluated the impact of normalizing EMG amplitude by unit variance. We found that the total variance accounted for (tVAF) by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency (e.g., 9.3 percentage points change for one synergy between 4 and 40 Hz). This change in tVAF can alter the number of synergies selected for further analyses. Normalizing tVAF to a z-score (e.g., dynamic motor control index during walking, walk-DMC) reduced sensitivity to LP cutoff. Unit variance scaling caused comparatively small changes in tVAF. Synergy weights and activations were impacted less than tVAF by LP filter choice and unit variance normalization. These results demonstrate that EMG signal processing methods impact outputs of synergy analysis and z-score based measures can assist in reporting and comparing results across studies and clinical centers.

Walk-DMC – Kat Steele and Michael Schwartz are featured in GeekWire

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A staff member of a gait lab kneels next to a child to apply additional motion detecting markers at Gillette Children's Specialty Healthcare. Another staff member sits behind a desk, observing the instrumentation on the lab computer. Photo taken by Michael Schwartz.

GeekWire, a national technology news resource, has featured Dr. Steele and Dr. Schwartz‘s Walk-DMC in a special series focused on community issues and innovative solutions to societal challenges. Lisa Stiffler reports on the analysis that is used to create Walk-DMC, an assessment tool that uses routinely collected electromyography (EMG) data to identify which kids are the strongest candidates for surgery — and to help develop alternative treatments for children needing a different solution.

“It’s a very complex problem,” said Steele, who is a co-author of a paper explaining the Walk DMC metric published this month in the journal Developmental Medicine & Child Neurology. “You can have two individuals who are walking visually nearly identically,” she said, “but how they’re controlling that motion can be very different.”

To read the full article, click HERE.

Featured in UWToday: Michael Schwartz and Kat Steele have developed a quantitative assessment of motor control in children with cerebral palsy

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A child walking in the motion analysis lab at Gillette Children's Specialty Healthcare. Photo by Michael Schwartz.

Our lab’s director, Dr. Kat Steele, and Dr. Michael Schwartz, from Gillette Children’s Specialty Healthcare, have developed a quantitative assessment of motor control in children with cerebral palsy called Walk-DMC, which could be used to help determine whether or not patients would benefit from aggressive, invasive surgeries to assist in walking and motion. Jennifer Langston reports on the new technique within UWToday. An exert from the article is posted below, but for the full article, read HERE.

“Only about 50 percent of children have significant improvement in their movement after these highly invasive surgeries,” said Kat Steele, a UW assistant professor of mechanical engineering. “Our motivation has really been to figure out how we can push up these success rates.”