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Hearing Aid Accelerometer Based Pedometry Assessment for Older Adults

2023· article· en· W4386920274 on OpenAlexaff
Will Sloan, Bruce Wallace, Andrea Pepe, Heidi Sveistrup, Frank Knoefel, Amy E. Mark Fraser, Matthew Bromwich

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsUniversity of OttawaBruyèreCarleton University
Fundersnot available
KeywordsAccelerometerComputer scienceHearing aidPhysical medicine and rehabilitationAudiologyMedicineOperating system

Abstract

fetched live from OpenAlex

The assessment of activity for older adults provides important knowledge about their well-being as declines could be caused by health issues. Reduced activity can lead to poorer health, social isolation, loneliness, and cognitive decline. Many aging adults require hearing aids (HA) and these devices now include accelerometers that could be used as pedometers. In this work, the performance of the hearing aid manufacturer provided pedometer measurements is compared to pedometry from an Actigraph accelerometer while both are used by healthy older adults for 14 days. The results show that the research subjects wore the hearing aids for 10 to 14 hours per day on average providing good compliance. When left and right hearing aids are compared with each other, the pedometer results are consistent. The correlation of the hearing aids to the Actigraph was very high, but the actual step counts recorded varied above and below the Actigraph results showing that the provided hearing aid algorithm provides an indication of activity, but additional improvements should be considered to improve algorithm accuracy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.084
GPT teacher head0.462
Teacher spread0.378 · 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
GenreEmpirical

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

Citations4
Published2023
Admission routes1
Has abstractyes

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