Electroretinogram Photopic Negative Response (PhNR) Skill
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Electroretinogram Photopic Negative Response (PhNR) Skill
Zero-dependency sovereign personal agent skill for non-invasive analysis of Electroretinogram Photopic Negative Response (PhNR), retinal ganglion cell health, and ocular strain.
flowchart TD
PhotopicFlash["Photopic Light Stimulus"] --> ERG_Waveform["Full-Field Electroretinogram Recording"]
ERG_Waveform --> FeatureExtract["Extraction: a-wave, b-wave, PhNR Trough & Latency"]
FeatureExtract --> RatioCalc["PhNR/b-wave Ratio & Retinal Ganglion Engine"]
RatioCalc --> Agent["OpenClaw / Hermes Personal Agent Actions"]Features
Deterministic Math: Pure Python standard library implementation with zero external dependencies.
ISCEV Standard Electrophysiology: Implements clinical electroretinography standards for photopic negative response quantification.
Retinal Ganglion Strain Stratification: Quantitative detection of inner retinal stress before irreversible visual loss.
Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.
Related MCP server: Acoustic Startle Prepulse Inhibition (PPI) MCP Server
Quickstart
from client import ElectroretinogramPhNRClient
client = ElectroretinogramPhNRClient()
result = client.evaluate_phnr(
b_wave_amplitude_uv=118.0,
phnr_amplitude_uv=46.5,
phnr_latency_ms=71.5
)
print("PhNR/b-wave Ratio:", result["phnr_b_wave_ratio"])
print("Classification:", result["classification"])License
Apache-2.0
This server cannot be deployed
Maintenance
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