Stress Detection from Surface Electromyography using Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Stress Detection from Surface Electromyography using Convolutional Neural Networks

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Robles Diego¹,Benchekroun Mouna²,Zalc Vincent²,Istrate Dan²,Taramasco Carla¹

Affiliation:

1. Escuela de Ingeniería Civil Informática, Universidad de Valparaíso,Valparaíso,Chile

2. Université de technologie de Compiègne,Biomechanics and Bioengineering Lab,Compiègne,France

Funder

Universidad de Valparaíso

FONDECYT

ANID

STIC-AmSud código

CONICYT

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871860.pdf?arnumber=9871860

Reference27 articles.

1. Integrating ‘psychosocial’ factors into a theoretical model for work-related musculoskeletal disorders

2. Mental stress and trapezius muscle activation under psychomotor challenge: A focus on EMG gaps during computer work

3. Stress Detection Using Physiological Sensors

4. Psychophysiological stress and emg activity of the trapezius muscle

5. Stress Emotion Recognition Based on RSP and EMG Signals

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploring the impact of human-robot interaction on workers' mental stress in collaborative assembly tasks;Applied Ergonomics;2024-04

2. Virtual Reality Sensor-Based IoT Embedded System for Stress Diagnosis;IEEE Sensors Journal;2023-12-01

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