Experimental systems
Running movement experiments with feedback, displays, and synchronized measurement.
Applied work
Tools for movement studies.
This is the practical side of my work: experiment control, signal processing, modeling, and analysis code.
Signal processing
Working with EMG, force, acceleration, kinematic, and behavioral signals.
Modeling and analysis
Using models to interpret uncertainty, adaptation, and variability.
Reproducible workflows
Organizing analysis code, notes, and figures so results can be checked later.
Methods
Programming, hardware interfacing, and modeling matter because they shape what can be measured. I am always looking to learn more about the methods we use and how this may change our data interpretations
Working areas
Experimental control
Python, MATLAB, PsychoPy, NI-DAQmx, Spike2, and custom task logic for human movement experiments.
Movement and physiology data
Electromyography, force transducers, accelerometers, force plates, and biomechanical signal processing.
Analysis and modeling
Data cleaning, visualization, inferential statistics, Bayesian reasoning, state-space models, and cue-combination models.