MATLAB: Modeling, Simulation, and Data Analysis


Modeling a Multi-Species Food Chain (ODE45)

Developed a MATLAB simulation of a multi-species rainforest food web using coupled differential equations and ODE45 for a final group differential equations project. Incorporated birth and death rates, predatory relationships, and starvation logic to study cascading population effects and ecosystem stability. Tested multiple initial conditions to analyze system sensitivity and emergent behavior.

Rates of change derived from literature estimates.

Scenario 1: Producer Take Over

Scenario 2: Ecosystem Collapse

Example Logic Condition to Determine Rate of Change of Monkey Population


Modeling Arterial Compliance Using MATLAB

Analyzed pressure-time data from a physical 2-element Windkessel model to study the role of arterial compliance in smoothing pulsatile blood flow. Used MATLAB to import experimental data, generate plots, and compare compliant and non-compliant systems. Built upon prior Simulink Windkessel modeling.

Statistical Analysis of Blood Pressure Measurement Variability

Tools: Excel • MATLAB • Simulink


Analyzed indirect blood pressure measurements across techniques, time of day, and cuff placement. Performed one-way ANOVA and Z-tests to evaluate statistical significance, demonstrating how hydrostatic effects and measurement technique influence systolic pressure readings.

Mean systolic blood pressure by time of day, visualized in MATLAB using class measurement data.

Mean systolic blood pressure by cuff placement, visualized in Google Sheets, illustrating increased readings when measurements are taken below heart level.

Tools: Excel • Google Sheets • MATLAB

Previous
Previous

Redesigned Zeroing Caps

Next
Next

Arduino & Circuit-Building Experience