Personal Agent Neuromuscular Reaction Time Psychomotor Skill

Zero-dependency Psychomotor Vigilance Task (PVT) attentional lapse counter, reciprocal speed modeler, and cumulative sleep debt neurobehavioral impairment evaluator.

Architecture

flowchart TD
    TrialData[Reaction Times ms Array] --> PVTEngine[Dinges PVT Statistical Engine]
    PVTEngine --> FilterFalseStarts[Filter Anticipation False Starts: < 100 ms]
    PVTEngine --> MeanMedian[Mean & Median Reaction Times]
    PVTEngine --> LapseCount[Lapses Counter: Trials >= 500 ms]
    PVTEngine --> ReciprocalSpeed[Reciprocal Speed: 1000 / RT Mean s^-1]
    LapseCount & ReciprocalSpeed --> SleepDebtModeler[Van Dongen Sleep Debt Dose-Response Model]
    SleepDebtModeler --> ImpairmentEquivalence[Impairment Analogy: 0.05% to >= 0.08% BAC Equivalence]

Quickstart

from client import PersonalAgentNeuromuscularReactionTimePsychomotor

agent = PersonalAgentNeuromuscularReactionTimePsychomotor()
res = agent.evaluate_pvt_attentional_performance([230.0, 245.0, 520.0, 240.0, 260.0])
print(f"Mean RT: {res['mean_reaction_time_ms']} ms | Lapses: {res['attentional_lapse_count_500ms']}")