Acoustic Frequency Following Response (FFR) Skill

Zero-dependency sovereign personal agent skill for non-invasive evaluation of Auditory Brainstem Frequency Following Response (FFR) Phase-Locking Value (PLV), SNR, and subcortical temporal envelope encoding fidelity.

flowchart TD
    PeriodicSound["Periodic Speech Vowel / Pitch Stimulus (F0 100-300 Hz)"] --> Cochlea["Cochlear Afferent Synchrony & Auditory Nerve Fibers"]
    Cochlea --> InferiorColliculus["Upper Brainstem Inferior Colliculus Phase-Locking"]
    InferiorColliculus --> FFR_Signal["Continuous Scalp-Recorded FFR Potential (Microvolts)"]
    FFR_Signal --> PhaseCoherence["Phase-Locking Value (PLV) & Signal-to-Noise Ratio (SNR)"]
    PhaseCoherence --> TemporalScore["Subcortical Auditory Fidelity & Speech-in-Noise Score"]
    TemporalScore --> Agent["OpenClaw / Hermes Personal Agent Sound Masking Protection"]

Features

• Deterministic Math: Pure Python standard library implementation with zero external dependencies.
• Auditory Electrophysiology Standards: Implements validated equations for brainstem FFR amplitude, inter-trial phase-locking value (PLV), and stimulus cross-correlation.
• Hidden Hearing Loss & Synaptopathy Shield: Sensitive detection of auditory brainstem temporal jitter prior to pure-tone threshold loss.
• Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.

Quickstart

from client import AcousticFrequencyFollowingResponseClient

client = AcousticFrequencyFollowingResponseClient()
result = client.evaluate_ffr(
    stimulus_fundamental_freq_hz=150.0,
    ffr_amplitude_uv=0.42,
    phase_locking_value=0.79,
    signal_to_noise_ratio_db=9.4
)
print("Phase-Locking Value:", result["phase_locking_value"])
print("Precision Score:", result["subcortical_precision_score"])
print("Classification:", result["classification"])

License

Apache-2.0