data-context

What problem does it solve?

This Skill provides a standardized context for analyzing data related to the "platform translation perturbation" experiment, ensuring that all analyses align with the specific goals and methodologies outlined in the associated research paper, particularly concerning the comparison of step vs. non-step recovery strategies.

Core Features & Use Cases

• Consistent Analysis Framework: Ensures that code and analysis adhere to the paper's defined comparison units (subject-velocity-trial), statistical modeling (LMM with specific fixed/random effects), and multiple comparison correction methods (FDR).
• Data Semantics Preservation: Guides users to reuse established data structures and naming conventions (e.g., onset-aligned-merged-parquet) to avoid reinventing data handling.
• Use Case: When developing a new analysis script for comparing EMG signals between step and non-step trials under identical perturbation conditions, this Skill ensures the script defaults to using raw trial data, appropriate statistical models, and correct data semantics, preventing deviations from the paper's established methodology.

Quick Start

Use the data-context skill to set up a new analysis script for comparing EMG signals between step and non-step trials.