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Record W3032705480 · doi:10.1145/3396339.3396381

An interactive sensory system to record and monitor human motion in physical rehabilitation

2020· article· en· W3032705480 on OpenAlexaff
Ali Maddahi, Mohamed-Amine Choukou, Yaser Maddahi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicHand Gesture Recognition Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceGraphical user interfaceOrientation (vector space)Interface (matter)Sensory systemSoftwareTracking (education)Motion captureSIGNAL (programming language)Computer visionMatch movingSimulationDegrees of freedom (physics and chemistry)Motion (physics)Human–computer interactionArtificial intelligence

Abstract

fetched live from OpenAlex

This paper briefly presents the application of an interactive sensory system to sense, record, restore, and monitor the movement of objects such as the human body. The setup, consisting of a data streamer and a software development kit (SDK), has nine degrees of freedom (DoFs): three orientation (roll, pitch, and yaw angles), three linear accelerations, and three magnetic field components. The SKD is a graphical user interface (GUI) that records, restore, and analyzes the signal received from the data streamer and presents advanced statistical analysis such as predicting the behavior of the measured data in the future. An application claimed is to provide patients with an accurate measurement that simplifies the tracking of performance and effectiveness of physical exercises and treatments. To show the proof of concept, we conducted an experimental study on the human's hand at the iRobohabilitation Laboratory, and quantified the signals measured by the sensory system in real-time.

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: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.292

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 communication0.0000.001
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 head0.020
GPT teacher head0.294
Teacher spread0.274 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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