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Record W2890739226 · doi:10.1109/jtehm.2018.2866105

Design and Integration of an Inexpensive Wearable Mechanotactile Feedback System for Myoelectric Prostheses

2018· article· en· W2890739226 on OpenAlexafffund
Katherine R. Schoepp, Michael R. Dawson, Jonathon S. Schofield, Jason P. Carey, Jacqueline S. Hebert

Bibliographic record

VenueIEEE Journal of Translational Engineering in Health and Medicine · 2018
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsGlenrose Rehabilitation HospitalUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesGlenrose Rehabilitation Hospital FoundationTrue Patriot Love Foundation
KeywordsModular designGRASPComputer scienceWearable computerProsthesisSensory systemProsthetic handHuman–computer interactionSimulationEmbedded systemArtificial intelligence

Abstract

fetched live from OpenAlex

The aim of this paper was to demonstrate the functionality of an inexpensive mechanotactile sensory feedback system for transhumeral myoelectric prostheses. We summarize the development of a tactile-integrated prosthesis, including 1) evaluation of sensors that were retrofit onto existing commercial terminal devices; 2) design of two custom mechanotactile tactors that were integrated into a socket without compromising suction suspension; 3) design of a modular controller which translated sensor input to tactor output, was wirelessly adjusted, and fit within a prosthetic forearm; and 4) evaluation of the system with a single transhumeral participant. Prosthesis functionality was demonstrated over three test sessions; the participant was able to identify tactor stimulation location and demonstrated a reduction in grasp force with the mechanotactile stimulation. This system offers an inexpensive and modular solution for integration of a mechanotactile sensory feedback system into a prosthetic socket without compromising the suction seal. These principles can be applied in future studies to investigate the direct impact of sensory feedback on tangible outcomes for prosthetic users, thereby reducing barriers to clinical translation.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score0.291

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 head0.026
GPT teacher head0.268
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations47
Published2018
Admission routes2
Has abstractyes

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Same venueIEEE Journal of Translational Engineering in Health and MedicineSame topicMuscle activation and electromyography studiesFrench-language works237,207