Biomechanics Signal Plot Skill
Professional guidelines for biomechanics signal data visualization
Overview
This Skill provides guidelines and code templates for visualizing signal data used in biomechanics research.
Supported Data Types:
- EMG Signals: TKEO pipeline, onset detection markers
- Forceplate Signals: Fx, Fy, Fz channel visualization
- CoP/CoM Trajectories: X-Y coordinate trajectory visualization, window color coding
When to Use
- Visualizing EMG signal analysis results
- Visualizing Forceplate data
- Visualizing CoP (Center of Pressure) or CoM (Center of Mass) trajectories
- Creating velocity-trial combination grid plots
- Displaying onset timing markers
- Highlighting analysis windows
File Structure
| File |
Purpose |
SKILL.md |
Main Skill overview and usage instructions |
emg-plot-guide.md |
EMG signal visualization guidelines |
forceplate-guide.md |
Forceplate signal visualization guidelines |
trajectory-guide.md |
CoP/CoM trajectory visualization guidelines |
templates/grid_plot_template.py |
Grid plot code template |
Core Principles
1. Grid Plot Default Behavior
- All visualizations are generated as grid plots by default
- Number of columns =
ceil(sqrt(number of plots))
- Empty subplots are hidden
- Each subplot includes individual title and legend
2. Velocity-Trial Sorting
Data is sorted by velocity-trial combination and arranged in grid:
10-1, 10-2, 10-3
15-1, 15-2, 15-3
20-1, 20-2, 20-3
3. Quality Settings
- DPI: 300 (publication quality)
- Korean font setup required
Guide File References
EMG Visualization
Refer to emg-plot-guide.md for EMG signal visualization:
- TKEO pipeline visualization
- Onset timing markers (vertical dashed lines)
- Window highlights (p1, p2, p3, p4)
Forceplate Visualization
Refer to forceplate-guide.md for Forceplate signal visualization:
- Fx, Fy, Fz channel visualization
- Onset timing markers
- Channel-specific color settings
Trajectory Visualization
Refer to trajectory-guide.md for CoP/CoM trajectory visualization:
- X vs Y scatter plot
- Y-axis flip (anterior-positive)
- Window-based color coding
- Maximum value markers (star markers)
Using Code Templates
Import basic grid plot generation functions from templates/grid_plot_template.py:
from templates.grid_plot_template import (
calculate_grid_dimensions,
setup_korean_font,
create_grid_figure,
save_figure
)
# Calculate grid dimensions
rows, cols = calculate_grid_dimensions(n_plots)
# Setup Korean font
setup_korean_font()
# Create figure
fig, axes = create_grid_figure(rows, cols, figsize=(16, 12))
# Save (DPI 300)
save_figure(fig, output_path)
Common Color Settings
Window Colors
| Window |
Color |
| p1 |
#1f77b4 (Blue) |
| p2 |
#ff7f0e (Orange) |
| p3 |
#2ca02c (Green) |
| p4 |
#d62728 (Red) |
Marker Styles
| Marker Type |
Style |
| onset timing |
Vertical dashed line (linestyle='--') |
| maximum value |
Star marker (marker='*', markersize=10) |
1---2name: biomechanics-signal-plot3description: Visualize biomechanics signal data including EMG, Forceplate (Fx/Fy/Fz), and CoP/CoM trajectories. Use when creating grid plots, onset timing markers, window highlights, TKEO pipeline visualizations, or trajectory scatter plots for biomechanics research. Triggers on EMG plot, forceplate visualization, CoP trajectory, CoM trajectory, TKEO onset, signal grid, biomechanics chart.4---56# Biomechanics Signal Plot Skill78> Professional guidelines for biomechanics signal data visualization910## Overview1112This Skill provides guidelines and code templates for visualizing signal data used in biomechanics research.1314**Supported Data Types**:15- **EMG Signals**: TKEO pipeline, onset detection markers16- **Forceplate Signals**: Fx, Fy, Fz channel visualization17- **CoP/CoM Trajectories**: X-Y coordinate trajectory visualization, window color coding1819## When to Use2021- Visualizing EMG signal analysis results22- Visualizing Forceplate data23- Visualizing CoP (Center of Pressure) or CoM (Center of Mass) trajectories24- Creating velocity-trial combination grid plots25- Displaying onset timing markers26- Highlighting analysis windows2728## File Structure2930| File | Purpose |31|------|---------|32| `SKILL.md` | Main Skill overview and usage instructions |33| `emg-plot-guide.md` | EMG signal visualization guidelines |34| `forceplate-guide.md` | Forceplate signal visualization guidelines |35| `trajectory-guide.md` | CoP/CoM trajectory visualization guidelines |36| `templates/grid_plot_template.py` | Grid plot code template |3738## Core Principles3940### 1. Grid Plot Default Behavior41- All visualizations are generated as grid plots by default42- Number of columns = `ceil(sqrt(number of plots))`43- Empty subplots are hidden44- Each subplot includes individual title and legend4546### 2. Velocity-Trial Sorting47Data is sorted by velocity-trial combination and arranged in grid:48```4910-1, 10-2, 10-35015-1, 15-2, 15-35120-1, 20-2, 20-352```5354### 3. Quality Settings55- DPI: 300 (publication quality)56- Korean font setup required5758## Guide File References5960### EMG Visualization61Refer to [emg-plot-guide.md](./emg-plot-guide.md) for EMG signal visualization:62- TKEO pipeline visualization63- Onset timing markers (vertical dashed lines)64- Window highlights (p1, p2, p3, p4)6566### Forceplate Visualization67Refer to [forceplate-guide.md](./forceplate-guide.md) for Forceplate signal visualization:68- Fx, Fy, Fz channel visualization69- Onset timing markers70- Channel-specific color settings7172### Trajectory Visualization73Refer to [trajectory-guide.md](./trajectory-guide.md) for CoP/CoM trajectory visualization:74- X vs Y scatter plot75- Y-axis flip (anterior-positive)76- Window-based color coding77- Maximum value markers (star markers)7879## Using Code Templates8081Import basic grid plot generation functions from `templates/grid_plot_template.py`:8283```python84from templates.grid_plot_template import (85 calculate_grid_dimensions,86 setup_korean_font,87 create_grid_figure,88 save_figure89)9091# Calculate grid dimensions92rows, cols = calculate_grid_dimensions(n_plots)9394# Setup Korean font95setup_korean_font()9697# Create figure98fig, axes = create_grid_figure(rows, cols, figsize=(16, 12))99100# Save (DPI 300)101save_figure(fig, output_path)102```103104## Common Color Settings105106### Window Colors107| Window | Color |108|--------|-------|109| p1 | `#1f77b4` (Blue) |110| p2 | `#ff7f0e` (Orange) |111| p3 | `#2ca02c` (Green) |112| p4 | `#d62728` (Red) |113114### Marker Styles115| Marker Type | Style |116|-------------|-------|117| onset timing | Vertical dashed line (`linestyle='--'`) |118| maximum value | Star marker (`marker='*'`, `markersize=10`) |