Systems built end to end.
Four projects that trace my path from rehabilitation hardware to a complete motor-skill measurement system. Each is real work I designed and built; where code exists, it's linked or available on request.
Driving-Inspired Motor-Skill Assessment System
My doctoral project: a behavioral paradigm in which a subject acquires a procedural “driving” motor skill, built to measure that skill precisely and detect how amyloid-β pathology degrades it. I designed and validated the entire stack — a custom apparatus, timestamped tactile / contact-sensor acquisition (~3.6 Hz), and lateral video at 60 fps — then built markerless kinematic tracking in DeepLabCut and a reproducible Python analysis pipeline (linear mixed-effects trajectory models, Mann–Whitney effect sizes, subject-level aggregation), with explicit data-retention QC across an 84-trial dataset.
Manuscript in preparation. Analysis code to be released on GitHub with the preprint.
Wrist CPM Robot with Joystick Serious Game
An earlier, human-facing rehabilitation system: a continuous-passive-motion wrist device driven by Arduino and stepper motors, linked to a joystick built in Processing 3 that controls a simple 2D game — an early attempt at making repetitive rehabilitation movement engaging. The Arduino firmware and Processing 3 game code are available.
Ventricular Deformation Analysis with DIC
My Master's project: a Python computational pipeline for analyzing soft-tissue deformation using Digital Image Correlation, applied to ventricular deformation. It included segmentation, deformation estimation, and machine-learning-assisted masking to improve accuracy on medical imaging data.
Arduino-Controlled CPM Wrist Device
My undergraduate thesis: the design and implementation of a continuous-passive-motion wrist rehabilitation device. I designed the mechanical structure in SolidWorks and developed the Arduino-based motor-control system — the first hardware project in a line that eventually led to my PhD instrumentation.