AACPDM 2023

Two people smiling and taking a selfie while standing in front of The Shirley Ryan Ability Lab sign. Mia has blonde hair. Charlotte has brown hair and is wearing glasses.

Lab members, Charlotte Caskey and Mia Hoffman attended the 2023 American Academy for Cerebral Palsy and Developmental Medicine (AACPDM) Annual Meeting in Chicago, IL on September 10-13, 2023.

Charlotte gave a poster presentation on “Short-Burst Interval Treadmill Training Increases Step Length and Stability for Children with Cerebral Palsy.”

Mia gave a podium presentation during the Early Detection and Diagnosis session on “Quantifying the Activity Levels of Toddlers with Down Syndrome Playing in a Partial Body Weight Support System.

Great work in the Windy City!

Introducing Dr. Nicole Zaino

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 DisabilitiesCongratulations 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”

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.