Differences in the force exerted during wrist movements are explained by a general mathematical model

The goal of previous efforts has been to create hand prostheses with natural movements. Researchers have used tools to identify patterns in muscle signals associated with different hand movements. While many studies have successfully classified types of hand movements, it's important to analyze speed and strength to ensure that the resulting movements are natural. In this study, 16 healthy subjects were evaluated for (two) different forces and (six) hand movements using surface electromyographic (sEMG) records. A mixed effects model was used to examine the relationship between force and forearm sEMG signals. The results showed high R2 values (median 0.9) and significant random effects, indicating that sEMG signals can explain variations in force signals during different hand movements by introducing the type of movement as part of the random effects of the model.

Authors

Institutions

Publication Details

Journal
Heritage and Sustainable Development ISSN 2712-0554
Published
2024-12-03
DOI
https://doi.org/10.37868/hsd.v6i2.925
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Differences in the force exerted during wrist movements are explained by a general mathematical model

Antonio Enrique Ibarra Quezada, Diana María Reyes Bravo, Carlos Arizmendi, Omar Lengerke et al.
Heritage and Sustainable Development ISSN 2712-0554
Robot Manipulation and Learning
article

Differences in the force exerted during wrist movements are explained by a general mathematical model

Antonio Enrique Ibarra Quezada, Diana María Reyes Bravo, Carlos Arizmendi, Omar Lengerke, C L Sandoval-Rodríguez, Ricardo Palacio
article en

Abstract

The goal of previous efforts has been to create hand prostheses with natural movements. Researchers have used tools to identify patterns in muscle signals associated with different hand movements. While many studies have successfully classified types of hand movements, it's important to analyze speed and strength to ensure that the resulting movements are natural. In this study, 16 healthy subjects were evaluated for (two) different forces and (six) hand movements using surface electromyographic (sEMG) records. A mixed effects model was used to examine the relationship between force and forearm sEMG signals. The results showed high R2 values (median 0.9) and significant random effects, indicating that sEMG signals can explain variations in force signals during different hand movements by introducing the type of movement as part of the random effects of the model.

Heritage and Sustainable Development ISSN 2712-0554Vol. 6(2)
University of the Basque Country (ES), Universidad Autónoma de Bucaramanga (CO), Unidades Tecnológicas de Santander (CO)
Openalex Percentile: Top 74%
Robot Manipulation and Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Differences in the force exerted during wrist movements are explained by a general mathematical model — Antonio Enrique Ibarra Quezada, Diana María Reyes Bravo, et al. · Heritage and Sustainable Development ISSN 2712-0554 (2024) | TGRS Research Map | TGRS