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Postural Sway & Center of Pressure (COP) Statokinesigram Skill

License: MIT Python 3.10+ Zero Dependencies OpenClaw Ready MCP Protocol

A sovereign personal agent capability for computational posturography, processing 2D Center of Pressure (COP) statokinesigram trajectories, 95% confidence ellipse area, and Romberg Quotient.

Architecture

flowchart TD
    ForcePlate["COP Trajectory: Mediolateral (x) & Anterior-Posterior (y)"] --> SpatialCov["Spatial Bivariate Covariance Matrix"]
    SpatialCov --> Eigenvalues["Eigenvalue Decomposition (lambda_1, lambda_2)"]
    Eigenvalues --> Ellipse["95% Confidence Ellipse Area (CEA_95)"]
    ForcePlate --> Kinematics["Path Length (mm) & Mean Velocity (mm/s)"]
    Ellipse & Kinematics --> PSI["Postural Stability Index & Fall Risk Tier"]
    PSI --> Romberg["Romberg Quotient (EO vs EC Sensory Re-weighting)"]

Related MCP server: physiological-tremor

Quickstart

from client import PosturalSwayClient

client = PosturalSwayClient()

# Analyze a series of COP displacements (mm)
x_ml = [0.2, 0.5, 0.8, 0.4, -0.1, -0.4, -0.2, 0.1]
y_ap = [1.2, 1.5, 1.1, 0.7, 0.3, -0.2, 0.4, 0.9]

sway = client.analyze_cop_sway(x_ml, y_ap, sample_rate_hz=50.0)

print("Mean Sway Velocity:", sway["mean_sway_velocity_mm_s"], "mm/s")
print("95% Ellipse Area:", sway["confidence_ellipse_area_95_mm2"], "mm²")
print("Postural Stability Index:", sway["postural_stability_index"], "/ 100")

MCP Server Integration

Add to your claude_desktop_config.json or OpenClaw tool registry:

{
  "mcpServers": {
    "postural-sway": {
      "command": "python",
      "args": ["/path/to/genpark-personal-agent-postural-sway-center-of-pressure-skill/mcp_server.py"]
    }
  }
}

License

MIT License.

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