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Record W4293088406 · doi:10.1097/moo.0000000000000840

The remaining obstacles for a totally implantable cochlear implant

2022· review· en· W4293088406 on OpenAlexaff
Mathieu Trudel, David P. Morris

Bibliographic record

VenueCurrent Opinion in Otolaryngology & Head & Neck Surgery · 2022
Typereview
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsDalhousie UniversityUniversité LavalHôpital de l'Enfant-Jésus
Fundersnot available
KeywordsCommercializationCochlear implantComputer scienceEnergy supplyMicroelectromechanical systemsEnergy harvestingEnergy (signal processing)TelecommunicationsMedicineNanotechnologyBusinessMaterials scienceAudiologyPhysics

Abstract

fetched live from OpenAlex

PURPOSE OF THE REVIEW: For years, the development of a totally implantable cochlear implant (TICI) has faced several technical challenges hindering any prototypes from reaching full commercialization. This article aims to review the necessary specifications for a viable TICI. An overview of the remaining challenges when designing TICIs will be provided, focusing on energy supply and implantable microphones. RECENT FINDINGS: The literature review highlights how research efforts to generate sufficient power to supply a fully implantable CI could take advantage of microelectromechanical systems (MEMS)-based energy harvesters incorporating piezoelectric materials. Using one of the various energy sources in the vicinity of the temporal bone would allow the development of a self-sufficient implant, overcoming the limitations of electrochemical batteries. Middle ear implantable microphones could also use similar fabrication techniques and transduction mechanisms to meet the sensor requirements for a TICI. SUMMARY: Recent breakthroughs in power supply using MEMS-based energy harvesting technologies and piezoelectric implantable microphones may make TICIs become a more practical reality in the foreseeable future. Once available, TICIs will have major impact on our patients' quality of life and may help to make hearing rehabilitation a more appealing option to a greater proportion of those who fulfill our candidacy criteria.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.824
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.155
GPT teacher head0.402
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2022
Admission routes1
Has abstractyes

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