Title
Can HDEMG-Based Low Back Muscle Fatigue Estimates Be Used in Exoskeleton Control During Prolonged Trunk Bending? A Pilot Study
Author
Brouwer, N.P.
Tabasi, A.
Moya-Esteban, A.
Sartori, M.
van Dijk, W.
Kingma, I.
van Dieen, J.H.
Contributor
Moreno, J.C. (editor)
Masood, J. (editor)
Schneider, U. (editor)
Maufroy, C. (editor)
Pons, J.L. (editor)
Publication year
2022
Abstract
The effectiveness of exoskeletons could be enhanced by incorporating low back muscle fatigue estimates in their control. The aim of the present study was to evaluate whether low back muscle fatigue can be estimated using the spectral content of trunk extensor muscle high-density EMG (HDEMG) by considering the motor unit action potential conduction velocity (MUAP CV) as a reference. The HDEMG-based MUAP CV was estimated for multiple sites on the lower back consistently throughout a 30 degrees lumbar flexion endurance trial. Significant linear relationships were observed between MUAP CV and spectral content. However, MUAP CV and spectral changes over time did not show the expected decrease, probably due to additional recruitment of motor units or alternating activity of synergistic muscles. The anatomical information about the sites that allow MUAP CV estimation can be valuable for future low back muscle fatigue estimations.
Subject
Lifting
Exoskeletons
Biomechanical
Low back pain
Manual lifting
Models
Muscles
To reference this document use:
http://resolver.tudelft.nl/uuid:75ce7275-beda-45ca-99e1-6680ab1e5e24
DOI
https://doi.org/10.1007/978-3-030-69547-7_30
TNO identifier
957894
Publisher
Cham, Springer
ISBN
9783030695477
Source
Wearable Robotics: Challenges and Trends. WeRob 2020, International Symposium on Wearable Robotics, 27 (27), 183-187
Series
Biosystems & Biorobotics
Document type
bookPart