flowchart TD
    Sensor["Accelerometer / Gyroscope Timeseries"] --> Detrend["Mean Removal & Detrending"]
    Detrend --> SpectralEngine["Discrete Spectral Decomposition (0 - 30 Hz)"]
    SpectralEngine --> BandExtract["Band Separation (Low: 3-7Hz, Physio: 8-12Hz, High: 13-25Hz)"]
    BandExtract --> RMS["RMS Amplitude & Peak Frequency"]
    RMS --> Scoring["Tremor Stability Index & Fatigue Categorization"]
    Scoring --> AgentAction["OpenClaw / Hermes Rest & Ergonomic Guidance"]

from client import PhysiologicalTremorClient

client = PhysiologicalTremorClient()

# Analyze an acceleration stream (50 Hz)
samples = [0.08, 0.12, 0.05, -0.07, -0.11, 0.09, 0.13, -0.04]  # Extend to 200+ samples
result = client.analyze_tremor_timeseries(samples, sample_rate_hz=50.0)

print("Dominant Frequency:", result["dominant_peak_frequency_hz"], "Hz")
print("Tremor Stability Index:", result["tremor_stability_index"], "/ 100")
print("Status:", result["status"])

{
  "mcpServers": {
    "physiological-tremor": {
      "command": "python",
      "args": ["/path/to/genpark-personal-agent-physiological-tremor-stability-skill/mcp_server.py"]
    }
  }
}