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genpark-personal-agent-cardiac-pulse-arrival-time-pat-pwt-skill

mcp
Guvenlik Denetimi
Uyari
Health Uyari
  • License — License: MIT
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  • Active repo — Last push 0 days ago
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SUMMARY

Deterministic personal agent skill for calculating dual-sensor Pulse Arrival Time (PAT), Pulse Transit Time (PTT), pulse wave velocity, and arterial vascular compliance.

README.md

Dual-Sensor Pulse Arrival Time (PAT / PTT) Skill

License: Apache-2.0
Python 3.10+
Zero Dependencies
MCP Protocol Ready
OpenClaw Certified

Zero-dependency sovereign personal agent skill for non-invasive evaluation of dual-sensor Pulse Arrival Time (PAT), Pulse Transit Time (PTT), pulse wave velocity (PWV), and arterial elasticity.

flowchart TD
    ECG_R["ECG R-Wave Peak Timestamp"] --> DualSync["Time Difference Integration (PAT)"]
    PPG_Foot["Distal PPG Pulse Foot Timestamp"] --> DualSync
    DualSync --> PEP_Sub["PEP Subtraction (PTT = PAT - PEP)"]
    PEP_Sub --> PWV_Calc["Pulse Wave Velocity & Moens-Korteweg Modeling"]
    PWV_Calc --> ComplianceScore["Arterial Vascular Compliance Engine"]
    ComplianceScore --> Agent["OpenClaw / Hermes Personal Agent Actions"]

Features

  • Deterministic Math: Pure Python standard library implementation with zero external dependencies.
  • Hemodynamic Moens-Korteweg Principles: Implements validated equations linking pulse wave transit to arterial wall stiffness.
  • Continuous Cuffless Cardiovascular Monitoring: Enables continuous beat-to-beat vascular tone assessment.
  • Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.

Quickstart

from client import PulseArrivalTimeClient

client = PulseArrivalTimeClient()
result = client.evaluate_pulse_transit(
    pat_ms=215.0,
    pre_ejection_period_ms=85.0,
    arterial_path_length_m=0.82
)
print("Pulse Wave Velocity:", result["pulse_wave_velocity_pwv_m_s"], "m/s")
print("Classification:", result["classification"])

License

Apache-2.0

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