Training with electrical muscle stimulation: a novel method to improve Body Mass Index, lipid profile, growth hormone, and cortisol in overweight subjects

Consequently, EMS training emerges as a time-efficient and effective alternative to conventional exercise routines, enhancing skeletal muscle function.

Authors

Institutions

Publication Details

Journal
The Journal of Sports Medicine and Physical Fitness
Published
2025-03-17
DOI
https://doi.org/10.23736/s0022-4707.25.16188-4
Citations
1
Primary Topic
Cardiovascular and exercise physiology
Type
article
Field-Weighted Citation Impact
2.38
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Training with electrical muscle stimulation: a novel method to improve Body Mass Index, lipid profile, growth hormone, and cortisol in overweight subjects

Jalil Reisi, Milad Abdollahi, Sayyed Mohammad Marandi, Elnaz Riyahi
1 citations
The Journal of Sports Medicine and Physical Fitness
Cardiovascular and exercise physiology
2.38
article

Training with electrical muscle stimulation: a novel method to improve Body Mass Index, lipid profile, growth hormone, and cortisol in overweight subjects

Jalil Reisi, Milad Abdollahi, Sayyed Mohammad Marandi, Elnaz Riyahi
article en
1 citations

Abstract

Consequently, EMS training emerges as a time-efficient and effective alternative to conventional exercise routines, enhancing skeletal muscle function.

The Journal of Sports Medicine and Physical FitnessVol. 65(6)
University of Isfahan (IR)
Zero hunger
Openalex Percentile: Top 15%
Cardiovascular and exercise physiology
2.38
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.