{
  "id": 16614,
  "url": "https://arxiv.org/abs/2608.00371",
  "title": "Decoding Children's Gait Behavior",
  "summary": "We introduce a new problem domain for human action recognition: the fine-grained analysis of children's gait behaviors from standard RGB video. We specifically target the ambulatory patterns of children aged 3-17 years. Such behaviors arise naturally in the diagnosis and treatment of several critical developmental and neuromuscular disorders, such as cerebral palsy and hemiplegia. Despite their clinical value, current 3D sensor-based gait analysis systems are expensive, intrusive, and often impr",
  "authors": "Yifan Shen, Boyi Li, Meihuan Huang, Yuanzhe Liu, Xu Cao, Jinyang Jin",
  "category": "research",
  "topics": "healthcare,children-education",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-31T20:00:00.000Z",
  "fetched_at": "2026-08-06T05:10:11.148Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/16614",
  "original_url": "https://arxiv.org/abs/2608.00371",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}