TY - JOUR
T1 - Automatically determining lumbar load during physically demanding work
T2 - A validation study
AU - Roossien, Charlotte Christina
AU - Baten, Christian Theodoor Maria
AU - van der Waard, Mitchel Willem Pieter
AU - Reneman, Michiel Felix
AU - Verkerke, Gijsbertus Jacob
N1 - Funding Information:
Funding: This research was funded by the European Regional Development Fund, a co-founder of INCAS3 (Assen, The Netherlands), an independent, non-profit research institute focused on technology from science and industry, the province and municipality of Groningen, and the province of Drenthe, Grant [number T-3036, 2013].
Funding Information:
This research was funded by the European Regional Development Fund, a co-founder of INCAS3 (Assen, The Netherlands), an independent, non-profit research institute focused on technology from science and industry, the province and municipality of Groningen, and the province of Drenthe, Grant [number T-3036, 2013]. We would like to thank Alejandro Miguel Reina Machena, Sylvia Nauta, An-nemarie Boer, Alienke Noordhuis, and Wim Grootens for their support and help during this study. We also would like to thank Leo van Eykern and Jurryt Vellinga of Inbiolab for sharing their knowl-edge, skills, and equipment.
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/4/2
Y1 - 2021/4/2
N2 - A sensor-based system using inertial magnetic measurement units and surface electromyography is suitable for objectively and automatically monitoring the lumbar load during physically demanding work. The validity and usability of this system in the uncontrolled real-life working environment of physically active workers are still unknown. The objective of this study was to test the discriminant validity of an artificial neural network-based method for load assessment during actual work. Nine physically active workers performed work-related tasks while wearing the sensor system. The main measure representing lumbar load was the net moment around the L5/S1 inter-vertebral body, estimated using a method that was based on artificial neural network and perceived workload. The mean differences (MDs) were tested using a paired t-test. During heavy tasks, the net moment (MD = 64.3 ± 13.5%, p = 0.028) and the perceived workload (MD = 5.1 ± 2.1, p < 0.001) observed were significantly higher than during the light tasks. The lumbar load had significantly higher variances during the dynamic tasks (MD = 33.5 ± 36.8%, p = 0.026) and the perceived workload was significantly higher (MD = 2.2 ± 1.5, p = 0.002) than during static tasks. It was concluded that the validity of this sensor-based system was supported because the differences in the lumbar load were consistent with the perceived intensity levels and character of the work tasks.
AB - A sensor-based system using inertial magnetic measurement units and surface electromyography is suitable for objectively and automatically monitoring the lumbar load during physically demanding work. The validity and usability of this system in the uncontrolled real-life working environment of physically active workers are still unknown. The objective of this study was to test the discriminant validity of an artificial neural network-based method for load assessment during actual work. Nine physically active workers performed work-related tasks while wearing the sensor system. The main measure representing lumbar load was the net moment around the L5/S1 inter-vertebral body, estimated using a method that was based on artificial neural network and perceived workload. The mean differences (MDs) were tested using a paired t-test. During heavy tasks, the net moment (MD = 64.3 ± 13.5%, p = 0.028) and the perceived workload (MD = 5.1 ± 2.1, p < 0.001) observed were significantly higher than during the light tasks. The lumbar load had significantly higher variances during the dynamic tasks (MD = 33.5 ± 36.8%, p = 0.026) and the perceived workload was significantly higher (MD = 2.2 ± 1.5, p = 0.002) than during static tasks. It was concluded that the validity of this sensor-based system was supported because the differences in the lumbar load were consistent with the perceived intensity levels and character of the work tasks.
KW - Inertial motion units
KW - Low back pain
KW - Physically active workers
UR - http://www.scopus.com/inward/record.url?scp=85103500508&partnerID=8YFLogxK
U2 - 10.3390/s21072476
DO - 10.3390/s21072476
M3 - Article
C2 - 33918394
AN - SCOPUS:85103500508
SN - 1424-8220
VL - 21
JO - Sensors
JF - Sensors
IS - 7
M1 - 2476
ER -