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Record W3159511798 · doi:10.21203/rs.3.rs-413094/v1

Estimating Proprioceptive Position Sense of Upper Limbs Using Joint Distance and Joint Angle Symmetries

2021· preprint· en· W3159511798 on OpenAlexaff
Shivakeshavan Ratnadurai‐Giridharan, Dalina Delfing, Maxime T. Robert, Tomoko Kitago, Andrew M. Gordon, Kathleen M. Friel

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversité Laval
FundersNational Institutes of Health
KeywordsProprioceptionJoint (building)Homogeneous spacePosition (finance)MathematicsComputer scienceGeometryPsychologyEconomicsEngineeringStructural engineeringNeuroscience

Abstract

fetched live from OpenAlex

Abstract Background Proprioceptive position sense (PPS) plays a critical role in movement and coordination of the upper limbs. It is commonly affected in neurological disorders such as unilateral spastic cerebral palsy (USCP) and stroke. However, UL PPS is often not considered during assessment or treatment in motor rehabilitation programs, in part due to limitations of current methods to quantify PPS. Traditional methods assess the similarity or symmetry of angles of a single joint and may not be sufficiently sensitive nor accurate. Emerging methods such as the use of robotic technology typically are limited to 2D and are also not standardizable as they are not easily available to clinics and research labs. This study aims to introduce a standardized and accessible way to quantify multi-joint PPS using 3D kinematic measures. Methods We developed novel multi-joint angle and distance-based measures of symmetry to assess upper limb PPS. Healthy adults (N = 17) and children with USCP (N=9) participated in this study. Kinematics were extracted during upper limb 3D pose matching tasks using a VICON Nexus system. Brunner-Munzel permutation tests were used for statistical comparisons between groups. Pearson’s correlation coefficient was used to investigate the relationship between the different symmetry measures and pose matching tasks. Results We introduced novel angle and distance-based measures of symmetry to estimate PPS. Healthy adults scored higher on both these symmetry measures compared to children with USCP. Angle and distance-based symmetries did correlate with each other. Exploratory factor analysis indicated that both angle symmetry and joint distance symmetry were highly loaded by the latent factor that best explained variance in the data. These results suggest that the two measures of pose symmetry are not redundant. It was also observed that distance symmetry was less sensitive to the different poses while angle symmetry varied across poses. Conclusions Symmetry measures derived from kinematics during upper limb pose matching tasks can estimate multi-joint PPS. Angle and distance-based symmetries together provide information about an individual’s ability to sense joint position. This framework will allow clinicians and researchers to measure PPS of upper limbs only using kinematic acquisition devices.

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)0.004
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.128
GPT teacher head0.371
Teacher spread0.242 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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