biomechanics-signal-plot

Create grid-based visualizations for EMG, forceplate, and CoP/CoM trajectory data.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/Rukkha1024/elderly-balance-assessment --skill biomechanics-signal-plot
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: biomechanics-signal-plot
Source: https://github.com/Rukkha1024/elderly-balance-assessment/tree/main/.claude/skills/biomechanics-signal-plot
Command: npx skills add https://github.com/Rukkha1024/elderly-balance-assessment --skill biomechanics-signal-plot

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Biomechanics researchers often struggle to quickly visualize complex signal data such as EMG, forceplate, and CoP/CoM trajectories, hindering insight and communication.

Core Features & Use Cases

  • Guidelines & templates for grid-based visualization of multiple signals (EMG with TKEO pipeline, Fx/Fy/Fz forceplate channels, and CoP/CoM trajectories).
  • Window highlighting, onset markers, and scatter trajectories to compare conditions across velocity-trial combos, with clear color schemes and legends.
  • Code templates for grid plotting and common plotting tasks in templates/grid_plot_template.py, enabling rapid adoption in biomechanics research.

Quick Start

Create a grid-plot visualization for EMG, forceplate, and CoP/CoM trajectories using the provided templates.

Frequently Asked Questions about biomechanics-signal-plot

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I visualize multiple EMG and forceplate signals in a grid plot?▼

To visualize multiple EMG and forceplate signals in a grid plot, use the provided frontmatter-driven templates to structure Fx/Fy/Fz channels and EMG data into comparative grids with predefined color schemes.

What is the best way to plot CoP and CoM trajectories for biomechanics research?▼

Plotting CoP and CoM trajectories is achieved through provided templates that render scatter trajectories, enabling clear comparison across velocity-trial combinations with highlighted windows.

Can I add TKEO onset markers to EMG signal visualizations?▼

Yes, you can add TKEO onset markers to EMG signal visualizations using the provided templates, which support overlaying onset detection markers directly onto grid-plotted EMG data.

Do I need specific dependencies to highlight windows in biomechanics data plots?▼

No specific dependencies are required to highlight windows in biomechanics data plots, as the visualization templates provide built-in utilities for window highlighting without external dependencies.

How do I compare forceplate data across different velocity-trial schemes?▼

To compare forceplate data across velocity-trial schemes, apply the grid-based visualization templates that organize Fx, Fy, and Fz channels into structured matrices with consistent legends and window highlighting.

Are there reusable templates for common biomechanics plotting tasks?▼

Yes, reusable templates for common biomechanics plotting tasks are available in templates/grid_plot_template.py, enabling rapid adoption for EMG, forceplate, and CoP/CoM trajectory visualizations.