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Cardiac Baroreflex Sensitivity (BRS) Sequence Skill

Cardiac Baroreflex Sensitivity (BRS) Sequence 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 spontaneous Cardiac Baroreflex Sensitivity (BRS), beat-to-beat sequence analysis, cardiovagal tone, and autonomic resilience.

flowchart TD
    ContinuousBP["Beat-to-Beat Systolic Blood Pressure (SBP) Stream"] & ContinuousECG["Continuous ECG RR-Interval Stream"] --> SequenceDetection["Sequence Extraction: >= 3 Consecutive Beats (r >= 0.85)"]
    SequenceDetection --> UpUp["Up/Up Sequences (Delta SBP > 0, Delta RR > 0)"]
    SequenceDetection --> DownDown["Down/Down Sequences (Delta SBP < 0, Delta RR < 0)"]
    UpUp & DownDown --> LinearSlope["Regression Slopes (Delta RR / Delta SBP in ms/mmHg)"]
    LinearSlope --> BRS_Mean["Mean Baroreflex Sensitivity (BRS) & Autonomic Score"]
    BRS_Mean --> Agent["OpenClaw / Hermes Personal Agent Resonant Pacing"]

Features

  • Deterministic Math: Pure Python standard library implementation with zero external dependencies.

  • Cardiovascular Autonomic Standards: Implements validated Bertinieri sequence method equations for spontaneous arterial baroreflex gain.

  • Cardiovagal Buffering & Orthostatic Screening: Detects early loss of parasympathetic blood pressure regulation and syncope vulnerability.

  • Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.

Related MCP server: Quantitative Pupillary Light Reflex (PLR) Skill

Quickstart

from client import CardiacBaroreflexSensitivityClient

client = CardiacBaroreflexSensitivityClient()
result = client.evaluate_brs_sequences(
    up_sequences_slopes=[14.5, 16.2, 13.8],
    down_sequences_slopes=[13.2, 14.8, 15.6]
)
print("Mean BRS:", result["mean_brs_ms_per_mmhg"], "ms/mmHg")
print("Baroreflex Score:", result["baroreflex_autonomic_score"])
print("Classification:", result["classification"])

License

Apache-2.0

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