Estimating Rotational Acceleration in Shoulder and Elbow Joints Using a Transformer Algorithm and a Fusion of Biosignals.

Yu Bai, Xiaorong Guan, Long He, Zheng Wang, Zhong Li, Meng Zhu

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Feature-Level Fusion of Surface Electromyography and Mechanomyography Signals for MVC-Normalized Shoulder Abduction Force-Level Classification in Healthy Adults.Sensors (Basel, Switzerland) · 2026
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yu BaiSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Xiaorong GuanSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.ORCID 0000-0003-0860-6966

Long HeSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Zheng WangSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Zhong LiSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Meng ZhuSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the present study, we used a transformer model and a fusion of biosignals to estimate rotational acceleration in elbow and shoulder joints. To achieve our study objectives, we proposed a mechanomyography (MMG) signal isolation technique based on a variational mode decomposition (VMD) algorithm. Our results show that the VMD algorithm delivered excellent performance in MMG signal extraction compared to the commonly used technique of empirical mode decomposition (EMD). In addition, we found that transformer models delivered estimates of joint acceleration that were more precise than those produced by mainstream time series forecasting models. The average R

Indexed as

Elbow JointAccelerationAlgorithmsShoulderUpper Extremityestimation of human joint rotational accelerationmechanomyographysurface electromyographytransformer algorithm

Identifiers

PMID38543989

DOI10.3390/s24061726

PMCPMC10974125

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.