A repository by Osuke Doijiri deposited on Harvard Dataverse focuses on algorithms using audible sound waves for non-invasive bone fracture estimation. It contains source code for audible acoustic wave signal analysis and a dataset request protocol detailing capture parameters. No raw clinical data is included, and the work targets low-resource emergency screening using consumer electronics.
Use Cases
- Develop bone fracture estimation algorithms based on audible acoustic wave signal analysis mentioned in the description
- Design data collection protocols for audible sound capture based on the detailed request specification
- Build low-resource trauma screening tools based on the target use case of standard consumer electronics like smartphones
Strengths
- Focuses specifically on audible sound waves within the human-hearing range, distinct from ultrasound or X-rays.
- Includes a detailed dataset request protocol specifying parameters like sensor placement and sampling rates for future data capture.
Limitations
- No raw dataset or human clinical data is uploaded or included in this deposit.
- Column-level documentation is absent; field semantics must be inferred after download.
Provenance
- Source
- Harvard Dataverse
- Freshness
- Last updated 2026-06-17 09:20:31; freshness should be verified.