Low Back Biomechanics of Keg Handling Using Inertial Measurement Units

  • Colleen BrentsEmail author
  • Molly Hischke
  • Raoul Reiser
  • John Rosecrance
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 825)


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.


Craft 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.


  1. Abaraogu U, Okafor U, Ezeukwu A, Igwe S (2015) Prevalence of work related musculoskeletal discomfort and its impact on activity: a survey of beverage factory workers in Eastern Nigeria. Work 52:627–634. Scholar
  2. Allread WG, Marras WS, Burr DL (2000) Measuring trunk motions in industry: variability due to task factors, individual differences, and the amount of data collected. Ergonomics 43:691–701. Scholar
  3. Amell TK, Kumar S, Rosser BWJ (2001) Ergonomics, loss management, and occupational injury and illness surveillance. Part 1: elements of loss management and surveillance: A review. Int J Ind Ergon 28:69–84. Scholar
  4. Banos O, Toth M, Damas M, Pomares H, Rojas I (2014) Dealing with the effects of sensor displacement in wearable activity recognition. Sensors 14:9995–10023. Scholar
  5. Basahel AM (2015) ScienceDirect investigation of work-related musculoskeletal disorders (MSDs) in warehouse workers in Saudi Arabia. Procedia Manuf 3:4643–4649. Scholar
  6. Brewers Association (2016) Industry Updates: U.S. Bureau of Labor Statistics Data Suggests Improved Brewery Safety - Brewers Association (WWW Document). Accessed 2 Apr 2017
  7. Brewers Association (2017) U.S. hits record-breaking 6,000 breweries in operation. Brewers Association Press Release (WWW Document). Accessed 18 Apr 2018
  8. Bureau of Labor Statistics (2016) Nonfatal occupational injuries and illnesses with days away from work 2015.
  9. Coenen P, Kingma I, Boot CRL, Bongers PM, van Dieën JH (2014) Cumulative mechanical low-back load at work is a determinant of low-back pain. Occup Environ Med 71:332–337. Scholar
  10. Dagenais S, Caro J, Haldeman S (2008) A systematic review of low back pain cost of illness studies in the United States and internationally. Spine J. Scholar
  11. de Looze MP, Kingma I, Thunnissen W, van Wijk MJ, Toussain HM (1994) The evaluation of a practical biomechanical model estimating lumbar moments in occupational activities. Ergonomics 37:1495–1502CrossRefGoogle Scholar
  12. Driscoll T, Jacklyn G, Orchard J, Passmore E, Vos T, Freedman G, Lim S, Punnett L (2014) The global burden of occupationally related low back pain: estimates from the global burden of disease 2010 study. Ann Rheum Dis 73:975–981. Scholar
  13. Faber GS, Chang CC, Dennerlein JT, van Dieën JH (2016) Estimating 3D L5/S1 moments and ground reaction forces during trunk bending using a full-body ambulatory inertial motion capture system. J Biomech 49:904–912. Scholar
  14. Faber GS, Kingma I, van Dieën JH (2007) The effects of ergonomic interventions on low back moments are attenuated by changes in lifting behaviour. Ergonomics 50:1377–1391. Scholar
  15. Gatchel RJ, Schultz IZ (2014) Handbook of musculoskeletal pain and disability disorders in the workplace.
  16. Granzow RF, Schall MC, Smidt MF, Chen H, Fethke NB, Huangfu R (2018) Characterizing exposure to physical risk factors among reforestation hand planters in the Southeastern United States. Appl Ergon 66:1–8. Scholar
  17. Jones T, Kumar S (2001) Physical ergonomics in low-back pain prevention. J Occup Rehabil 11:309–319. Scholar
  18. Jones T, Strickfaden M, Kumar S (2005) Physical demands analysis of occupational tasks in neighborhood pubs. Appl Ergon 36:535–545. Scholar
  19. 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
  20. Khurelbaatar T, Kim K, Lee SK, Kim YH (2015) Consistent accuracy in whole-body joint kinetics during gait using wearable inertial motion sensors and in-shoe pressure sensors. Gait Posture 42:65–69. Scholar
  21. Kim S, Nussbaum MA (2013) Performance evaluation of a wearable inertial motion capture system for capturing physical exposures during manual material handling tasks. Ergonomics 56:314–326. Scholar
  22. 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
  23. Lee W, Seto E, Lin K-Y, Migliaccio GC (2017) An evaluation of wearable sensors and their placements for analyzing construction worker’s trunk posture in laboratory conditions. Appl Ergon. Scholar
  24. Magora A (1975) Investigation of the relation between low back pain and occupation. Scand J Rehabil Med 7:146–151Google Scholar
  25. Marras WS (1993) Dynamic measures of low back performance. American Industrial Hygiene AssociationGoogle Scholar
  26. Marras WS, Knapik G, Ferguson S (2009) Loading along the lumbar spine as influence by speed, control, load magnitude, and handle height during pushing. Clin Biomech 24:155–163. Scholar
  27. Marras WS, Lavender SA, Ferguson SA, Splittstoesser RE, Yang G (2010) Quantitative biomechanical workplace exposure measures: Distribution centers. J Electromyogr Kinesiol 20:813–822. Scholar
  28. Potvin JR (2008) Occupational spine biomechanics: A journey to the spinal frontier. J Electromyogr Kinesiol 18:891–899. Scholar
  29. 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
  30. R Core Team (2016) R: a language and environment for statistical computingGoogle Scholar
  31. Roetenberg D, Luinge H, Slycke P (2013) Xsens MVN: full 6DOF human motion tracking using miniature inertial sensors 3Google Scholar
  32. Schall MC, Fethke NB, Chen H (2016) Evaluation of four sensor locations for physical activity assessment. Appl Ergon 53:103–109. Scholar
  33. Schall MC, Fethke NB, Chen H, Gerr F (2015) A comparison of instrumentation methods to estimate thoracolumbar motion in field-based occupational studies. Appl Ergon 48:224–231. Scholar
  34. Van der Burg JCE, Van Dieën JH (2001) Underestimation of object mass in lifting does not increase the load on the low back. J Biomech 34:1447–1453. Scholar
  35. Van Der Burg JCE, Van Dieën JH, Toussaint HM (2000) Lifting an unexpectedly heavy object: The effects on low-back loading and balance loss. Clin Biomech 15:469–477. Scholar
  36. van Dieën JH, Faber GS, Loos RCC, Paul P, Kuijer FM, Kingma I, Van Der Molen HF, Frings-Dresen MHW (2010) Validity of estimates of spinal compression forces obtained from worksite measurements. Ergonomics 53:792–800. Scholar
  37. Vignais N, Miezal M, Bleser G, Mura K, Gorecky D, Marin F (2013) Innovative system for real-time ergonomic feedback in industrial manufacturing. Appl Ergon 44:566–574. Scholar
  38. 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

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Colleen Brents
    • 1
    Email author
  • Molly Hischke
    • 1
  • Raoul Reiser
    • 2
  • John Rosecrance
    • 1
  1. 1.Department of Environmental and Radiological Health SciencesColorado State UniversityFort CollinsUSA
  2. 2.Department of Health and Exercise ScienceColorado State UniversityFort CollinsUSA

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