Dual-Sensor Pulse Arrival Time (PAT / PTT) Skill
Provides Pulse Arrival Time, Pulse Transit Time, pulse wave velocity, and arterial compliance results to OpenClaw / Hermes personal agents so they can take actions based on the computed cardiovascular metrics.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Dual-Sensor Pulse Arrival Time (PAT / PTT) Skill
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.
Related MCP server: GenPark Bio-Agent
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
This server cannot be deployed
Maintenance
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