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StanfordBDHG/SensorTSLM

SensorTSLM Core Framework

Dataset-agnostic captioning pipeline for sensor time-series data.

Setup

Install dependencies and set the dataset path before running:

python3 -m pip install -r requirements.txt
export MHC_DATASET_DIR="../hf-daily_max-nonwear=50"

Usage

python3 captionizer.py

Explorer

Use the interactive explorer to inspect one row at a time, switch signals, and see which detector events fired where on the time series.

Start it with:

python3 explorer.py --min-wear-pct=50.0

Useful controls:

  • Use the bottom row slider or < / > buttons to move between dataset rows.
  • Click a signal in the right-hand signal list or in the channel overview heatmap to switch channels.
  • Use the Matplotlib zoom and pan tools on the main plot to inspect parts of the signal in detail.
  • Click reset or press home to reset the zoom.
  • Use the overlay buttons to toggle trend, spike, drop, and nonwear overlays.
  • Use the stats, events, captions, and help tabs in the details panel to switch what metadata is shown.
  • Scroll inside the details panel with the mouse wheel or the ^ / v buttons.

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WIP project about extending TSLMs for sensor data

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