MétaCan
Menu
Back to cohort
Record W2511224030

Preliminary Findings from Investigations of the Relationship between Hearing and Segmental Orientation during Walking

2016· article· en· W2511224030 on OpenAlexaffvenue
Sin-Tung Lau, Michael E. Cinelli, Karl Zabjek, Jennifer L. Campos

Bibliographic record

VenueCanadian acoustics · 2016
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of OttawaUniversity of TorontoToronto Rehabilitation InstituteWilfrid Laurier UniversityUniversity Health Network
Fundersnot available
KeywordsActive listeningAudiologyTrunkOrientation (vector space)PsychologyTask (project management)SentenceSound localizationPhysical medicine and rehabilitationMedicineCommunicationComputer science
DOInot available

Abstract

fetched live from OpenAlex

Several longitudinal studies over the past seven years have found associations between hearing loss and increased falls risk 1,2 , poor postural control while standing 2 , increased likelihood of having difficulties with walking 3 , slower walking speed 4 and frailty 5 . The present studies investigate one possible explanation of the link between hearing, balance, and mobility, being that listeners may change head and trunk orientation when performing a listening task in which potential sound sources are spatially separated.  In this presentation, preliminary findings with respect to head and trunk positioning (i.e., segmental orientation) from two independent but related studies will be shared. In the first study, younger (18-30 years old) and older (60 years old and older) adults with self-reported normal hearing performed a listening task while walking. Participants completed listening tasks in three conditions. In the first condition, participants walked along a 9m path, when they were 5m from the goal were presented with a 1 kHz pure tone from either the left or right speakers and were instructed to orient their head towards the sound source while maintaining a straight walking directory. In the second and third experimental conditions, participants performed a series of sentence recognition tasks while walking in which they were and were not instructed to orient their head position towards the sound source, respectively. The second study included younger and older adults with self-reported normal hearing, and older adults with poor hearing and who do not use hearing aids. Participants performed a sentence-in-babble recognition task during three experimental conditions: (1) while sitting on a bench, (2) while standing, and (3) while walking along a pathway similar to that of Study 1. In both studies, motion capture technology was used to collect positional information about different parts of the body. References: 1 Lin, F. & Ferrucci, L. (2012). Hearing loss and falls among older adults in the United States. Arch Intern Med , 172 (4), 369-371. 2 Viljanen, A., Kaprio, J., Pyykko I., Sorri, M., Pajala, S., . . . & Rantanen, T. (2009). Hearing as a predictor of falls and postural balance in older female twins. J Gerontol A Biol Sci Med Sci , 64A (2), 312-317. 3 Viljanen, A., Kaprio, J., Pyykko, I., Sorri, M., Koskenvuo, M., & Rantanen, T. (2009). Hearing acuity as a predictor of walking difficulties in older women. J Am Geriatr Soc , 57 , 2282-2286. 4 Li, L., Simonsick, E., Ferrucci, L., & Lin, F. (2013). Hearing loss and gait speed among older adults in the United States. Gait Posture , 38 (1), 25-29. 5 Kamil, R., Li, L., & Lin, F. (2014). Association of hearing impairment and frailty in older adults. J Am Geriatr Soc , 62 (6), 1186-1188.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.047
GPT teacher head0.259
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueCanadian acousticsSame topicHearing Loss and RehabilitationFrench-language works237,207