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Zero-dependency sovereign personal agent skill for non-invasive evaluation of Pre-Ejection Period (PEP), Left Ventricular Ejection Time (LVET), Weissler rate-corrected indices, and myocardial inotropic kinetics.
flowchart TD
ECG_PCG["ECG & Phonocardiography / ICG Sensors"] --> PEP_LVET["Systolic Time Intervals Extraction"]
PEP_LVET --> Weissler["Weissler Equations (PEPI, LVETI, PEP/LVET)"]
Weissler --> Inotropy["Myocardial Inotropic Efficiency Analysis"]
Inotropy --> Agent["OpenClaw / Hermes Personal Agent Actions"]Deterministic Math: Pure Python standard library implementation with zero external dependencies.
Weissler Standard Indices: Automatic rate correction according to standard non-invasive cardiography formulas.
Inotropic Performance Stratification: Quantitative evaluation of sympathetic vs depressed myocardial contractility.
Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.
Related MCP server: arc-baseline-kernel
from client import SystolicTimeIntervalsClient
client = SystolicTimeIntervalsClient()
result = client.evaluate_systolic_intervals(
pep_ms=96.0,
lvet_ms=295.0,
heart_rate_bpm=70.0
)
print("PEP/LVET Ratio:", result["pep_lvet_ratio"])
print("Classification:", result["classification"])Apache-2.0
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