A dataset for fatigue estimation during shoulder internal and external rotation movements using wearables

MN Yasar, M Sica, B O'Flynn, S Tedesco, M Menolotto - Scientific Data, 2024 - nature.com
Wearable sensors have recently been extensively used in sports science, physical
rehabilitation, and industry providing feedback on physical fatigue. Information obtained …

Exploring the Applicability of Physiological Monitoring to Manage Physical Fatigue in Firefighters

D Bustos, R Cardoso, DD Carvalho, J Guedes, M Vaz… - Sensors, 2023 - mdpi.com
Physical fatigue reduces productivity and quality of work while increasing the risk of injuries
and accidents among safety-sensitive professionals. To prevent its adverse effects …

Bioactive Compounds in Citrus Reticulata Peel Are Potential Candidates for Alleviating Physical Fatigue through a Triad Approach of Network Pharmacology …

A Ullah, Q Sun, J Li, J Li, P Khatun, G Kou, Q Lyu - Nutrients, 2024 - mdpi.com
Physical fatigue (peripheral fatigue), which affects a considerable portion of the world
population, is a decline in the ability of muscle fibers to contract effectively due to alterations …

The effect of craniosacral therapy on blood levels of stress hormones in male firefighter cadets: a randomized clinical trial

M Wójcik, B Bordoni, I Siatkowski, E Żekanowska - Behavioral Sciences, 2023 - mdpi.com
(1) Background: Fire department cadets preparing to become firefighters and paramedics
experience high levels of stress when participating in incidents like traffic accidents and …

Prediction of instantaneous perceived effort during outdoor running using accelerometry and machine learning

CI Pirscoveanu, AS Oliveira - European Journal of Applied Physiology, 2024 - Springer
The rate of perceived effort (RPE) is a subjective scale widely used for defining training
loads. However, the subjective nature of the metric might lead to an inaccurate …

Exploring the role of cardiac activity in forecasting cognitive fatigue with machine learning

D Nartey, R Karthikeyan, T Chaspari… - IISE Transactions on …, 2025 - Taylor & Francis
Fatigue poses significant risks to safety, productivity, and overall well-being. Traditional
statistical methods have been employed for inferring fatigue-related patterns; however, there …

Relationship between physical fatigue and mental fatigue based on multimodal measurement under different load levels

H **, M **ao, L Liu, S Kan, Y Fu, D Zhang - Ergonomics, 2024 - Taylor & Francis
Based on multimodal measurement methods of NASA task load index (NASA-TLX), task
performance, surface electromyography (sEMG), heart rate (HR), and functional near …

[HTML][HTML] Dynamic Prediction of Physical Exertion: Leveraging AI Models and Wearable Sensor Data During Cycling Exercise

A Smiley, J Finkelstein - Diagnostics, 2024 - mdpi.com
Background/Objectives: This study aimed to explore machine learning approaches for
predicting physical exertion using physiological signals collected from wearable devices …

[PDF][PDF] Wearable Technology and Machine Learning for Assessing Physical Fatigue in Industry 4.0

CA Morillo, M Demichela, D Jawla… - Hum. Factors Wearable …, 2024 - researchgate.net
Industry 4.0 is a shift towards automation and data integration in manufacturing and process
sectors. However, manual material handling and repetitive operations still cause significant …

Heart Rate Variability-Based Stress Detection and Fall Risk Monitoring During Daily Activities: A Machine Learning Approach

IB Messaoud, O Thamsuwan - Computers, 2025 - mdpi.com
Impaired balance and mental stress are significant health concerns, particularly among
older adults. This study investigated the relationship between the heart rate variability and …