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Improving Gait Activity Detection from GPS and IMUs with Machine Learning (GRA-041)

Summary ~

  • Grant ID: GRA-041
  • Sponsor / funder: DePaul ↔ RFUMS partnership
  • Program: AI in Biomedical Discovery and Healthcare
  • Status: awarded
  • Period: 2023 – —
  • Lead unit: LAS / Jarvis CDM
  • Amount: $65,898

Award details

  • Topics: gait, machine_learning, wearable_sensors
  • Grant type: research_grant

People

  • Sungsoon (Julie) Hwang (PI) — person identity unresolved
  • Ilyas Ustun (Co-PI) — person identity unresolved
  • Muhammad Umer Huzaifa (Co-PI)
  • Chris Connaboy (Collaborator) — person identity unresolved

None documented.

None documented in outputs layer.

See PI person pages for linked publications; grant-level publication edges not yet indexed.

Verification

  • Status: repo_derived (~)
  • Confidence: high
  • Notes: 2023 RFUMS collaborative award; parent program GRA-029. No DePaul facility named in source.

Source URLs

Public source URL not yet indexed; see internal grant registry.

Notes

Internal knowledge object — award metadata for Resource Map hypertext navigation. Full provenance retained in data/grants.yaml.