Abstract
Due to the labor-intensive nature of construction tasks, a large number of construction workers frequently suffer from excessive muscle fatigue. Workers’ muscle fatigue can adversely affect their productivity, safety, and well-being. Several attempts have been made to assess workers’ fatigue using subjective methods (e.g., fatigue questionnaire). Despite, the success of subjective methods in assessing workers’ fatigue in a long period, these methods have limited utility on construction sites. For instance, these methods interrupt workers’ ongoing tasks. These methods are also subject to high biases. To address these issues, this study aims to examine the feasibility of a wearable Electromyography (EMG) sensor to measure the electrical impulses produced by workers’ muscles as a means to continuously evaluate workers muscle fatigue without interfering with their ongoing tasks. EMG signals were acquired from eight subjects while lifting a concrete block using their upper limbs (i.e., elbow and shoulder muscles). As the first step, filtering methods (e.g., bandpass filter, rolling filter, and Hampel filter) were applied to reduce EMG signal artifacts. After removing signal artifacts, to examine the potential of EMG in measuring workers’ muscle fatigue, various EMG signal metrics were calculated in time domain (e.g., Signal Mean Absolute Value (MAV) and Root Mean Square (RMS)) and frequency domain (e.g., Median Frequency (MDF) and Mean Frequency (MEF)). Subjects’ perceived muscle exertion (Borg CR-10 scale) was used as a baseline to compare the muscle exertion identified by EMG signals. Results show a significant difference in EMG parameters while subjects were exerting different fatigue levels. Results confirm the feasibility of the wearable EMG to evaluate workers’ muscle fatigue as means for assessing their physical stress on construction sites.
Original language | English (US) |
---|---|
Title of host publication | Advances in Informatics and Computing in Civil and Construction Engineering |
Subtitle of host publication | Proceedings of the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management |
Editors | Ivan Mutis, Timo Hartmann |
Publisher | Springer |
Chapter | 22 |
Pages | 181-187 |
ISBN (Electronic) | 9783030002206 |
ISBN (Print) | 9783030002190, 9783030130930 |
DOIs | |
State | Published - 2019 |
Externally published | Yes |
Keywords
- Wearable electromyography (EMG)
- Signal processing
- Health
- Safety
- Workers’ productivity
- Wearable biosensors
- Physical fatigue
- Local muscle fatigue