Workers often develop low back pain due to manually lifting heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk in lifting activities. This study aims to verify the hypothesis that high-density surface electromyography (HDsEMG) allows an optimized discrimination of risk levels associated with different fatiguing lifting conditions compared to traditional bipolar sEMG. 15 participants performed three lifting tasks with a progressively increasing lifting index (LI) each lasting 15 min. Erector spinae (ES) activity was recorded using both bipolar and HDsEMG systems. The amplitude of both bipolar and HDsEMG can significantly discriminate each pair of LI. HDsEMG data could discriminate across the different LIs starting from the fourth minute of the task while bipolar sEMG could only do so towards the end. The higher discriminative power of HDsEMG data across the lifting tasks makes such methodology a valuable tool to be used to monitor fatigue while lifting and could extend the possibilities offered by currently available instrumental-based tools.
Bibliographical notePublisher Copyright:
© 2021. Published by Elsevier Ltd.
The research presented in this article was carried out as part of the program BRIC 2016-ID10 funded by INAIL and as part of the SOPHIA project, which has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 871237 .
- Biomechanical risk
- Bipolar and high-Density (HD) sEMG
- Fatiguing frequency-dependent lifting activities
ASJC Scopus subject areas
- Human Factors and Ergonomics
- Physical Therapy, Sports Therapy and Rehabilitation
- Safety, Risk, Reliability and Quality
- Engineering (miscellaneous)