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Quantitative Sensory Testing (QST) Thermal Threshold Skill

Quantitative Sensory Testing (QST) Thermal Threshold Skill

by Alpha-Park
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Quantitative Sensory Testing (QST) Thermal Threshold 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 Quantitative Sensory Testing (QST) thermal thresholds, Thermal Sensory Limen (TSL), and small-fiber neuropathy.

flowchart TD
    Thermode["Peltier Thermode Dynamic Temperature Ramp (1 deg C/s)"] --> ThresholdCapture["Perception Trigger: WDT, CDT, HPT, CPT"]
    ThresholdCapture --> TSL_Math["Thermal Sensory Limen (TSL = WDT - CDT)"]
    TSL_Math --> FiberScore["Small-Fiber C / A-Delta Neuropathy Engine"]
    FiberScore --> Agent["OpenClaw / Hermes Personal Agent Actions"]

Features

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

  • German Neurological QST Standards (DFNS): Implements validated equations for thermal sensory limen and pain thresholds.

  • Small-Fiber Neuropathy & Allodynia Screening: Sensitive detection of intraepidermal nerve fiber density decline.

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

Related MCP server: stdt-temporal-discrimination

Quickstart

from client import CutaneousThermalQSTClient

client = CutaneousThermalQSTClient()
result = client.evaluate_thermal_thresholds(
    warm_detection_temp_c=35.4,
    cold_detection_temp_c=29.6
)
print("Thermal Sensory Limen:", result["thermal_sensory_limen_tsl_deg_c"], "deg C")
print("Classification:", result["classification"])

License

Apache-2.0

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Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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