ClinicalTrials.gov
public full text
Public Domain
Cochlear Implant Low Power Strategy
Reducing power consumption in the cochlear implant is crucial to the development of future smaller sound processors. The commercial MP3000 sound coding strategy has been shown to be more efficient in power consumption to the standard ACE strategy. However in order to develop smaller sound processors, further battery life power savings are required. The aim of this study is to evaluate three experimental sets of MP3000 parameter sets, compared against the default ACE program. In the background for each of the four strategies, experimental noise reduction programs (SpatialNR and NR3) will also be in use. In an additional phase of the study, low stimulation rate ACE programs will also be evaluated against the default stimulation rate.
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
- A Slotted ALOHA Scheme Based on Bipartite Graph Optimization#408434
- Acoustic Analysis and Sound Quality Assessment of a Quiet Helicopter for Air Taxi Operations#1119903
- Les archives audiovisuelles de l’INA, une ressource d’expérimentation entre pédagogie et recherche#308368
- Performance and quality testing of CBM RICH front-end electronics#1154578
- The Nootka Sound Controversy: A dissertation#55850
Record · ID 1484092
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