ClinicalTrials.gov
public full text
Public Domain
Fall Risk Assessment and Speech Intelligibility Enhancement Using In-ear Device
The purpose of this study is to develop and validate methods to use hearing aids equipped with embedded sensors and artificial intelligence to assist in the assessment of fall risk and in the implementation of interventions aimed at reducing the risk of falling, as well as to improve speech intelligibility in quiet and in background noise, track physical activity, and social engagement. The investigators hope is that the knowledge that is generated through this study will ultimately translate to the clinical setting and will help reduce the likelihood that individuals experience a fall, and improve the quality of hearing in individuals who wear hearing aids.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Technical Evaluation of Earswitch Phase B#842729
- Intelligent fall risk prediction and real-time warning system for elderly care based on multimodal deep learning and wearable sensor fusion.#631148
- INVSENSOR00027 Fall Detection Clinical Performance Study#1086076
- Monitoring and Sensing System for People's Behavior During Fall Events Based on Mobility Analysis#126867
- Artificial Intelligence Diagnostic Decision Support to Reduce Antimicrobial Prescriptions in Young Children With Colds#800665
Record · ID 805486
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive