Case study

EMG Signal Processing Lab

This MATLAB lab covers core EMG signal processing for bicep and wrist recordings: rectification, integration, spectral exploration, designing and applying high-pass filters to reduce motion artifacts, visualizing fatigue, and correlating EMG features to grasp force using provided CSV data.

RoleBiosignal analysis and MATLAB implementation

TimelineBiosignal lab

FocusBiosignal Processing

EMG rectification + integrationSpectral analysisArtifact-removal filteringForce correlation

MATLABPlatform

Bicep + wrist EMGSignals

github.com/MaxwellM34/EMG_LabRepository

The brief

Challenge

Build a clean foundation for EMG processing that handles realistic artifacts and supports physiology-level interpretation.

Approach

What we made

Implemented rectification, integration, spectral inspection, and artifact-removal filtering as MATLAB building blocks tied to clear physiology questions.

Rectifies and integrates raw EMG to derive activation envelopes.
Designs and applies high-pass filters to reduce motion artifacts.
Correlates EMG features with grasp force using lab CSV data.

Outcome

Results

A reusable MATLAB foundation for downstream EMG projects, with documented behavior on motion artifacts and force correlation.

MATLABEMG processingFilter design

Gallery

Visual snapshots

Click any image to expand.

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