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Record W2270751868

Development and Evaluation of the iWalker: An Instrumented Rolling Walker to Assess Balance and Mobility in Everyday Activities

2010· dissertation· en· W2270751868 on OpenAlexfundno aff
James Tung

Bibliographic record

VenueTSpace · 2010
Typedissertation
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
FundersUniversity of WaterlooUniversity of TorontoToronto Rehabilitation Institute
KeywordsBalance (ability)Context (archaeology)Physical medicine and rehabilitationCardiorespiratory fitnessPhysical therapyMedicine
DOInot available

Abstract

fetched live from OpenAlex

The rollator is a mobility aid commonly used to facilitate balance and mobility for individuals with cardiorespiratory, musculoskeletal, or neurological deficits. Despite its popularity, there are also reports of adverse effects related to walker use linked to increased fall risks. Studies examining the effectiveness and consequences of rollator use have employed standard laboratory-based measurement methods that rely on performing specific tasks within a short time period and under controlled conditions, potentially limiting generalization to mobility in the everyday context. An instrumented rolling walker (iWalker) was developed as an ambulatory measurement tool applicable to the assessment of balance outside of the lab or clinic for assistive device users. The iWalker autonomously collects measurements of the upper and lower limb behaviour related to balance, walker kinematics, and video of the immediate spatial environment. The design and development of the iWalker is first described, followed by two studies characterizing the involvement of the upper limbs for balance in standing and walking that served to address gaps in the literature and evaluate the utility of the upper limb measures. Overall, the upper limbs can become the primary effectors of balancing forces when lower limb capabilities are compromised. When lower limb involvement was experimentally constrained, the upper limbs became the primary effectors of balance control in healthy, young adults. In older adults, individuals demonstrating the highest upper limb usage during walking were associated with the largest reduction in frontal plane stepping parameters (i.e., step width). A third study evaluated the applicability of the iWalker to assess everyday mobility in a series of in-patients recovering from neurological injury (i.e., stroke, traumatic brain injury). Patients demonstrated significantly different upper limb balancing behaviour in everyday situations compared to in-laboratory assessments. Furthermore, the iWalker captured behaviours that may be precursors to falling, such as collisions, stumbling and lifting the assistive device. The implications of these studies on assessing the effectiveness of rollators and feasibility of using the iWalker in follow-up efforts are discussed.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.370
Teacher spread0.325 · 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 designBench or experimental
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

Citations9
Published2010
Admission routes1
Has abstractyes

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