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Record W4417054495 · doi:10.1371/journal.pone.0337647

Motor-cognitive analysis of dual task walking in chronic obstructive pulmonary disease patients: An observational study using functional near infrared spectroscopy

2025· article· en· W4417054495 on OpenAlexafffund
Syed Ahmed Hassan, Leandro Viçosa Bonetti, Manjiri Kulkarni, Dmitry Rozenberg, W. Darlene Reid

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsUniversity Health NetworkToronto Rehabilitation InstituteUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsTask (project management)CognitionGaitPulmonary diseaseCOPDTask analysisElementary cognitive task

Abstract

fetched live from OpenAlex

Chronic Obstructive Pulmonary Disease (COPD), characterized by airflow limitation, commonly manifests cognitive and physical impairments that are often managed separately. The aim of this paper was to describe a dual task protocol of walking with a cognitive task to assess related decrements and associated ΔO2Hb in patients with COPD and older adults. Sample data illustrates responses from two individuals. Two single tasks and a dual task were applied in random order: (1) single task walking evaluated by the Zeno Electronic Walkway to measure gait speed; (2) a cognitive task of determining the number of 5-letter words accurately spelled backwards; (3) dual task walking combined with spelling words backwards. The decrements of performance were evaluated by examining the differences from single to dual task performance for two participants, to illustrate the methodology, as well as normalizing the decrement to the single task performance by the following equation:.

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)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.068
GPT teacher head0.332
Teacher spread0.264 · 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
Published2025
Admission routes2
Has abstractyes

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Same venuePLoS ONESame topicOptical Imaging and Spectroscopy TechniquesFrench-language works237,207