Published December 3, 2024 | Version v1

Pose-estimated 3D data of infant spontaneous activity from Helsinki and Pisa

  • 1. ROR icon University of Helsinki
  • 2. ROR icon Fondazione Stella Maris
  • 3. ROR icon Helsinki University Hospital

Description

This dataset contains pose-estimated 3D (and 2D proxy) data as well as trained models for generating infant Kinetic Age, collected from research trials in Helsinki and Pisa. The dataset is organized into separate archives for metadata, data streams, trained models, and predictions. Below is a detailed breakdown of the dataset contents:

Metadata

  • metadata/combined.csv
      - test_id: Unique identifier for each infant.
      - corrected_age: Corrected age of the infant in days.
      - outcome: Neurodevelopmental outcome labels (0 typical, 1 weak impairment, 2 MNI).

Data

  • data/features.csv
      - Handcrafted movement features computed for each, by experts annotated, useful video segment.
  • data/streams/combined/*.feather
      - 3D recording segment, with 18 J, B, V, A streams over 600 time steps.
  • data/streams_2d/combined/*.feather 
      - 2D recording segment, with 18 J, B, V, A streams over 600 time steps.

Results

  • results/model/fold_n/...
      - train_predictions.npy: Predictions made on the training set.
      - val_predictions.npy: Predictions made on the validation set.
      - best_model.ckpt: Checkpoint file containing the saved model weights.
      - metadata.json: Metadata describing the fold, including training parameters and validation segments.
      - scatter_*.png: Regression results.

Predictions

  • predictions/jb-aagcn-coord-xy_predictions.csv
      - Model predictions for the 2D model on MNI samples.
  • predictions/jb-aagcn-coord_predictions.csv
      - Model predictions for the 3D model on MNI samples.

Files

data.zip

Files (6.7 GB)

Name Size
md5:fc90767af4b3cc289f580734e4369af1
2.5 GB Preview Download
md5:c3ef8ef85cf49519627996dff7863678
1.1 kB Preview Download
md5:5228332965a9519a06072a0c24421c2a
27.3 kB Preview Download
md5:878ad84779aa6fd4b62330b74d6c5c27
4.2 GB Preview Download

Additional details

Software

Repository URL
https://github.com/deinal/infant-aagcn
Programming language
Python