Low Back Biomechanics of Keg Handling Using Inertial Measurement Units
Workers handling beer kegs experience risk factors associated with occupational low back pain (heavy loads, awkward trunk postures). Many breweries are small and lack resources for materials handling equipment, causing much work to be done manually (including keg handling).
Measuring worker motions (kinematics) may aid job design to reduce risk factors associated with lifting. Low back motions may be evaluated using observation techniques and devices which are oftentimes inconvenient in the field. Application of wireless inertial measurement units (IMUs) for human motion provides whole body kinematics information, including low back.
The present study used a 3-dimensional motion capture system to investigate low back kinematics during keg handling at a Colorado brewery. Specifically, five workers lifted spent kegs onto a clean and fill line. Workers wore 17 IMUs as they handled kegs. Low back angular displacements were assessed during keg handling at two heights (low, high). Repeated measures analyses were performed with each trunk angular displacement variable as a function of lift condition.
Differences in low back kinematics between lift conditions were identified. During low lifts, torso flexion was significantly greater than high lifts. A broader range of angular displacements was observed in high lifts. Data collection was feasible during operational hours due to IMU’s small design. Data collected from experienced workers provided researchers with information directly applicable to keg handling in small breweries. Results from the study can help improve workplace design in a craft brewery, reduce risk, and create safer work.
KeywordsCraft beer industry Manual materials handling Low back pain Inertial measurement units
The authors declare no conflict of interest. This study was funded under Mountains and Plains Education Research Center, NIOSH Grant T42OH009229.
- Brewers Association (2016) Industry Updates: U.S. Bureau of Labor Statistics Data Suggests Improved Brewery Safety - Brewers Association (WWW Document). https://www.brewersassociation.org/industry-updates/u-s-bureau-labor-statistics-data-suggests-improved-brewery-safety/. Accessed 2 Apr 2017
- Brewers Association (2017) U.S. hits record-breaking 6,000 breweries in operation. Brewers Association Press Release (WWW Document). https://www.brewersassociation.org/press-releases/2017-craft-beer-review/. Accessed 18 Apr 2018
- Bureau of Labor Statistics (2016) Nonfatal occupational injuries and illnesses with days away from work 2015. https://www.doi.org/USDL-15-2205
- Gatchel RJ, Schultz IZ (2014) Handbook of musculoskeletal pain and disability disorders in the workplace. https://www.doi.org/10.1007/978-1-4939-0612-3
- Karatsidis A, Jung M, Schepers HM, Bellusci G, de Zee M, Veltink PH, Andersen MS (2018) Predicting kinetics using musculoskeletal modeling and inertial motion captureGoogle Scholar
- Lavender S, Marras W, Ferguson S, Splittsteosser R, Yang G (2012) Developing physical exposure-based back injury risk models applicable to manual handling jobs in distribution centers. J Occup Environ Hyg 9:450–459Google Scholar
- Magora A (1975) Investigation of the relation between low back pain and occupation. Scand J Rehabil Med 7:146–151Google Scholar
- Marras WS (1993) Dynamic measures of low back performance. American Industrial Hygiene AssociationGoogle Scholar
- Putz-Anderson V, Bernard B, Burt S (1997) Musculoskeletal disorders and workplace factors: a critical review of epidemiologic evidence for work-related musculoskeletal disorders of the neck, upper extremity, and low back, Second edn. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, CincinnatiGoogle Scholar
- R Core Team (2016) R: a language and environment for statistical computingGoogle Scholar
- Roetenberg D, Luinge H, Slycke P (2013) Xsens MVN: full 6DOF human motion tracking using miniature inertial sensors 3Google Scholar
- Zurada J, Karwowski W, Marras W (2004) Classification of jobs with risk of low back disorders by applying data mining techniques. Occup Ergon 4:291–305Google Scholar