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Record W7037206181

Effect of Joint Angle on EMG-Torque Model During Constant-Posture, Quasi-Constant-Torque Contractions

2011· article· en· W7037206181 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDigital WPI · 2011
Typearticle
Languageen
FieldEngineering
TopicStonefly species taxonomy and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsStability (learning theory)Noise (video)ElectromyographyFilter (signal processing)Work (physics)Control theory (sociology)
DOInot available

Abstract

fetched live from OpenAlex

The electrical activity of skeletal muscle¡ªthe electromyogram (EMG)¡ªis of value to many different application areas, including ergonomics, clinical biomechanics and prosthesis control. For many applications the EMG is related to muscular tension, joint torque and/or applied forces. In these cases, a goal is for an EMG-torque model to emulate the natural relationship between the central nervous system and peripheral joints and muscles. This thesis mainly describes an experimental study which relates the simultaneous biceps/triceps surface EMG of 12 subjects to elbow torque at seven joint angles (ranging from 45¡ÃƒÂ£to 135¡ÃƒÂ£) during constant-posture, quasi-constant-torque contractions. The contractions ranged between 50% maximum voluntary contractions (MVC) extension and 50% MVC flexion. Advanced EMG amplitude (EMG¦Ãƒâ€™) estimation processors were investigated, and three nonlinear EMG¦Ãƒâ€™-torque models were evaluated. Results show that advanced (i.e., whitened, multiple-channel) EMG¦Ãƒâ€™ processors lead to improved joint torque estimation, compared to unwhitened, single-channel EMG¦Ãƒâ€™ processors. Depending on the joint angle, use of the multiple-channel whitened EMG¦Ãƒâ€™ processor with higher polynomial degrees produced a median error that was 50%-66% that found when using the single-channel, unwhitened EMG¦Ãƒâ€™ processor with a polynomial degree of 1. The best angle-specific model achieved a minimum error of 3.39% MVCF90 (i.e., error referenced to MVC at 90¢X flexion), yet it does not allow interpolation across angles. The best model which parameterizes the angle dependence achieved an error of 3.55% MVCF90. This thesis also summarizes other collaborative research contributions performed as part of this thesis. (1) Decomposition of needle EMG data was performed as part of a study to characterize motor unit behavior in patients with amyotrophic lateral sclerosis (ALS) [with Spaulding Rehabilitation Hospital, Boston, MA]. (2) EMG-force modeling of force produced at the finger tips was studied with the purpose of assessing the ability to determine two or more independent, continuous degrees of freedom of control from the muscles of the forearm [with WPI and Sherbrooke University]. (3) Identification of a nonlinear, dynamic EMG-torque relationship about the elbow was studied [WPI]. (4) Signal whitening preprocessing for improved classification accuracies in myoelectric control of a prosthesis was studied [with WPI and the University of New Brunswick].

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.967

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 head0.017
GPT teacher head0.200
Teacher spread0.182 · 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