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Related Experiment Video

Updated: Dec 21, 2025

Psychophysiological Stress Assessment Using Biofeedback

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Published on: July 31, 2009

Stress detection using ECG and EMG signals: A comprehensive study.

Sara Pourmohammadi¹, Ali Maleki¹

¹Biomedical Engineering Department, Semnan University, Semnan, Iran.

Computer Methods and Programs in Biomedicine

|May 15, 2020

Summary

Electromyogram (EMG) signals from back muscles effectively detect multi-level stress. Combining EMG with electrocardiogram (ECG) analysis shows EMG

Keywords:

Electrocardiogram Electromyogram Erector spinae muscle Heart rate variability Multi-level stress detection Stress-inducing protocol Trapezius muscle

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Area of Science:

Biomedical Engineering
Neuroscience
Psychophysiology

Background:

Stress and mental health are significant global concerns.
Traditional stress detection relies on physiological signals like ECG and EMG.
The impact of stress on specific muscle EMG signals and combined signal efficacy requires further investigation.

Purpose of the Study:

To review the utility of EMG signals from trapezius and erector spinae muscles for multi-level stress recognition.
To evaluate the efficacy of EMG signals for stress detection by comparing them with ECG signals.

Main Methods:

Simultaneous acquisition of EMG and ECG signals from 34 healthy students.
Induction of stress using laboratory methods including mental arithmetic, Stroop test, time pressure, and a stressful environment.
Application of distinct feature selection and machine learning algorithms.

Main Results:

Accuracies of 100%, 97.6%, and 96.2% for two, three, and four levels of stress recognition, respectively.
High stress detection accuracies achieved through combinations of feature selection and machine learning.
EMG signals demonstrated strong performance in multi-level stress detection.

Conclusions:

EMG signals are highly effective for multi-level stress detection.
EMG signals show superior or comparable efficacy to ECG for stress detection.
This study highlights the potential of EMG for objective stress assessment.