Back to Search Start Over

Fatigue Estimation Using Peak Features from PPG Signals.

Authors :
Chen, Yi-Xiang
Tseng, Chin-Kun
Kuo, Jung-Tsung
Wang, Chien-Jen
Chao, Shu-Hung
Kau, Lih-Jen
Hwang, Yuh-Shyan
Lin, Chun-Ling
Source :
Mathematics (2227-7390). 8/15/2023, Vol. 11 Issue 16, p3580. 23p.
Publication Year :
2023

Abstract

Fatigue is a prevalent subjective sensation, affecting both office workers and a significant global population. In Taiwan alone, over 2.6 million individuals—around 30% of office workers—experience chronic fatigue. However, fatigue transcends workplaces, impacting people worldwide and potentially leading to health issues and accidents. Gaining insight into one's fatigue status over time empowers effective management and risk reduction associated with other ailments. Utilizing photoplethysmography (PPG) signals brings advantages due to their easy acquisition and physiological insights. This study crafts a specialized preprocessing and peak detection methodology for PPG signals. A novel fatigue index stems from PPG signals, focusing on the dicrotic peak's position. This index replaces subjective data from the brief fatigue index (BFI)-Taiwan questionnaire and heart rate variability (HRV) indices derived from PPG signals for assessing fatigue levels. Correlation analysis, involving sixteen healthy adults, highlights a robust correlation (R > 0.53) between the new fatigue index and specific BFI questions, gauging subjective fatigue over the last 24 h. Drawing from these insights, the study computes an average of the identified questions to formulate the evaluated fatigue score, utilizing the newfound fatigue index. The implementation of linear regression establishes a robust fatigue assessment system. The results reveal an impressive 91% correlation coefficient between projected fatigue levels and subjective fatigue experiences. This underscores the remarkable accuracy of the proposed fatigue prediction in evaluating subjective fatigue. This study further operationalized the proposed PPG processing, peak detection method, and fatigue index using C# in a computer environment alongside a PPG device, thereby offering real-time fatigue indices to users. Timely reminders are employed to prompt users to take notice when their index exceeds a predefined threshold, fostering greater attention to their physical well-being. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22277390
Volume :
11
Issue :
16
Database :
Academic Search Index
Journal :
Mathematics (2227-7390)
Publication Type :
Academic Journal
Accession number :
170738844
Full Text :
https://doi.org/10.3390/math11163580