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Record W4411089654 · doi:10.3390/bios15060367

Influence of Gait Speed on Inter-Joint Coordination in People with and Without Parkinson’s Disease

2025· article· en· W4411089654 on OpenAlexaff
Patrick Ippersiel, Philippe C. Dixon, Elke Warmerdam, Robbin Romijnders, Walter Maetzler, Clint Hansen

Bibliographic record

VenueBiosensors · 2025
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsMcGill UniversityUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsParkinson's diseaseGaitPhysical medicine and rehabilitationJoint (building)DiseaseMedicineEngineeringInternal medicineStructural engineering

Abstract

fetched live from OpenAlex

BACKGROUND: The influence of gait speed on lower-extremity coordination while walking in people with Parkinson's disease (pwPD) is poorly understood. This study sought to investigate the relationship between gait speed and hip-knee coordination and coordination variability in older adults and pwPD. METHODS: A total of 27 pwPD and 21 healthy older adults were recruited. Participants walked in a straight line at slow, preferred, and fast walking speeds. Gait data were collected using inertial measurement units, and the kinematics of the hip and knee were calculated. Coordination and coordination variability at the hip-knee joint pair were determined using continuous relative phase. A repeated measures two-way ANCOVA tested the impact of gait speed on coordination and coordination variability, while group differences were evaluated using statistical parametric mapping (SPM). RESULTS: Neither the healthy older adults nor the pwPD adjusted their hip-knee coordination in response to changes in gait speed. pwPD also displayed a trend towards restricted hip and knee joint excursion compared to older adults, which may further limit their ability to adapt gait strategies. CONCLUSIONS: These findings suggest that interventions addressing both joint excursion and motor adaptability may be important for improving gait function in individuals with Parkinson's disease. Real-world applicability can be found in the potential of wearable sensors to become a valuable tool in routine clinical practice for both diagnosis and ongoing management. TRIAL REGISTRATION: The study is registered in the German Clinical Trials Register (DRKS00022998).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.005
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.016
GPT teacher head0.320
Teacher spread0.304 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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