RESNA 2023 Conference: Mia Hoffman receives Student Scientific Paper Award

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Nicole wearing a black dress and Mia wearing a floral dress standing in front of a large sign at the RESNA conference.Two lab members, Nicole Zaino and Mia Hoffman attended the annual Rehabilitation Engineering and Assistive Technology Society of North America (RESNA) Conference on July 24-26 in New Orleans, LA.

Big congratulations to Mia Hoffman for being selected as an awardee in the Student Scientific Paper Competition (SSPC).

Mia gave a podium presentation on “Exploring the World on Wheels: A Geospatial Comparison of Two Pediatric Mobility Devices”

Nicole was also selected to give an interactive poster presentation on “Quantifying Toddler Exploration in Seated and Standing Postures with Powered Mobility“. She also completed her time as the student board member for RESNA.

Way to go, Mia and Nicole!

Introducing Dr. Nicole Zaino

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Congratulations to Dr. Nicole Zaino on earning her Doctorate in Mechanical Engineering! Dr. Zaino’s PhD thesis dissertation was titled Walking and Rolling: Evaluation Technology to Support Multimodal Mobility for Individuals with Disabilities. Congratulations and best of luck as you move forward training on the Elite Team at Crosscut Mountain Sports Center in para nordic sit skiing and assistive technology field.

MH Schwartz, KM Steele, AJ Ries, AG Georgiadis, BA MacWilliams (2022) “A model for understanding the causes and consequences of walking impairments”

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Journal Article in PLOS ONE:

Causal inference is inherently ambiguous since we cannot observe multiple realizations of the same person with different characteristics. Causal models must be evaluated through indirect means and reasoning.

Aim: The main objectives in conducting this study were to (1) propose a comprehensive model for quantifying the causes and consequences of walking impairments and (2) demonstrate the potential utility of the model for supporting clinical care and addressing basic scientific questions related to walking.

Method: This paper introduced a model consisting of 10 nodes and 23 primary causal paths and demonstrated the model’s utility using a large sample of gait data.

Results: The model was plausible, captured some well-known cause-effect relationships, provided new insights into others, and generated novel hypotheses requiring further testing through simulation or experiment.

Interpretation: This model is a proposal that is meant to be critically evaluated, validated or refuted, altered, and improved over time. Such improvements might include the introduction of new nodes, variables, and paths.