Skip to main content

Feature Detection and Biomechanical Analysis to Objectively Identify High Exposure Movement Strategies When Performing the EPIC Lift Capacity test

Journal of Occupational Rehabilitation volume 31, pages 50–62 (2021)Cite this article

Abstract

Purpose The Epic Lift Capacity (ELC) test is used to determine a worker’s maximum lifting capacity. In the ELC test, maximum lifting capacity is often determined as the maximum weight lifted without exhibiting a visually appraised “high-risk workstyle.” However, the criteria for evaluating lifting mechanics have limited justification. This study applies feature detection and biomechanical analysis to motion capture data obtained while participants performed the ELC test to objectively identify aspects of movement that may help define “high-risk workstyle”. Method In this cross-sectional study, 24 participants completed the ELC test. We applied Principal Component Analysis, as a feature detection approach, and biomechanical analysis to motion capture data to objectively identify movement features related to biomechanical exposure on the low back and shoulders. Principal component scores were compared between high and low exposure trials (relative to median exposure) to determine if features of movement differed. Features were interpreted using single component reconstructions of principal components. Results Statistical testing showed that low exposure lifts and lowers maintained the body closer to the load, exhibited squat-like movement (greater knee flexion, wider base of support), and remained closer to neutral posture at the low back (less forward flexion and axial twist) and shoulder (less flexion and abduction). Conclusions Use of feature detection and biomechanical analyses revealed movement features related to biomechanical exposure at the low back and shoulders. The objectively identified criteria could augment the existing scoring criteria for ELC test technique assessment. In the future, such features can inform the design of classifiers to objectively identify “high-risk workstyle” in real-time.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price includes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3

References

  1. Bureau of Labor Statistics. Nonfatal occupational injuries and illnesses requiring days away from work, 2010. Washington, DC: Bureau of Labor Statistics News Release; 2011.

    Google Scholar 

  2. Armstrong TJ, Franzblau A, Haig A, Keyserling WM, Levine S, Streilein K, Ulin S, Werner R. Developing ergonomic solutions for prevention of musculoskeletal disorder disability. Assist Technol. 2001;13(2):878–877.

    CAS  PubMed  Google Scholar 

  3. Pransky GS, Dempsey PG. Practical aspects of functional capacity evaluations. J Occup Rehabil. 2004;14(3):217–229.

    PubMed  Google Scholar 

  4. Legge J, Burgess-Limerick R, Peeters G. A new pre-employment functional capacity evaluation predicts longer-term risk of musculoskeletal injury in healthy workers: a prospective cohort study. Spine. 2013;38(25):2208.

    PubMed  PubMed Central  Google Scholar 

  5. Epic Rehab. EPIC lift capacity test (ELC). 2016. https://epicrehab.com/products/index.php?main_page=document_general_info&products_id=65.

  6. Matheson LN, Mooney V, Grant JE, Affleck M, Hall H, Melles T, Lichter RL, McIntosh G. A test to measure lift capacity of physically impaired adults. Part 1: development and reliability testing. Spine. 1995;20(19):2119–2129.

    CAS  PubMed  Google Scholar 

  7. Lakke SE, Soer R, Krijnen WP, van der Schans CP, Reneman MF, Geertzen JH. Influence of physical therapists' kinesiophobic beliefs on lifting capacity in healthy adults. Phys Ther. 2015;95(9):1224–1333.

    PubMed  Google Scholar 

  8. Echeita JA, van Holland BJ, Gross DP, Kool J, Oesch P, Trippolini MA, Reneman MF. Association between social factors and performance during functional capacity evaluations: a systematic review. Disabil Rehabil. 2019;41(16):1863–1873.

    Google Scholar 

  9. Echeita JA, Bethge M, van Holland BJ, Gross DP, Kool J, Oesch P, Trippolini MA, Chapman E, Cheng AS, Sellars R, Spavins M. Functional capacity evaluation in different societal contexts: results of a multicountry study. J Occup Rehabil. 2019;29(1):222–236.

    Google Scholar 

  10. Allison S, Galper J, Hoyle D, Mecham, J. Current concepts in functional capacity evaluatION: a best practices guideline. 2018. https://www.orthopt.org/uploads/content_files/files/2018%20Current%20Concepts%20in%20OH%20PT-FCE%2006-20-18%20FINAL.pdf.

  11. Marras WS, Lavender SA, Leurgans SE, Rajulu SL, Allread SW, Fathallah FA, Ferguson SA. The role of dynamic three-dimensional trunk motion in occupationally-related. Spine. 1993;18(5):617–628.

    CAS  PubMed  Google Scholar 

  12. Sinden KE, McGillivary TL, Chapman E, Fischer SL. Survey of kinesiologists’ functional capacity evaluation practice in Canada. Work. 2017;56(4):571–580.

    PubMed  Google Scholar 

  13. Smith RL. Therapists' ability to identify safe maximum lifting in low back pain patients during functional capacity evaluation. J Orthop Sports Phys Ther. 1994;19(5):277–281.

    CAS  PubMed  Google Scholar 

  14. Allen JL, James C, Snodgrass SJ. The effect of load on biomechanics during an overhead lift in the WorkHab Functional Capacity Evaluation. Work. 2012;43(4):487–496.

    PubMed  Google Scholar 

  15. West N, Snodgrass SJ, James C. The effect of load on biomechanics of the back and upper limb in a bench to shoulder lift during the WorkHab Functional Capacity Evaluation. Work. 2018;59(2):201–210.

    PubMed  Google Scholar 

  16. Cole MH, Grimshaw PN, Burden AM. Loads on the lumbar spine during a work capacity assessment test. Work. 2004;23(2):169–178.

    CAS  PubMed  Google Scholar 

  17. Jäger M. Assessment of low-back load during manual material handing. In: Proceedings of the 13th triennial Congress of the International Ergonomics Association, vol. 4, pp. 171–173, 1997.

  18. Waters TR, Putz-Anderson V, Garg A, Fine LJ. Revised NIOSH equation for the design and evaluation of manual lifting tasks. Ergonomics. 1993;36(7):749–776.

    CAS  PubMed  Google Scholar 

  19. Daffertshofer A, Lamoth CJ, Meijer OG, Beek PJ. PCA in studying coordination and variability: a tutorial. Clin Biomech. 2004;19(4):415–428.

    Google Scholar 

  20. Haid TH, Doix AC, Nigg BM, Federolf PA. Age effects in postural control analyzed via a principal component analysis of kinematic data and interpreted in relation to predictions of the optimal feedback control theory. Front Aging Neurosci. 2018;10:22.

    PubMed  PubMed Central  Google Scholar 

  21. Khalaf KA, Parnianpour M, Sparto PJ, Barin K. Determination of the effect of lift characteristics on dynamic performance profiles during manual materials handling tasks. Ergonomics. 1999;42(1):126–145.

    CAS  PubMed  Google Scholar 

  22. Wrigley AT, Albert WJ, Deluzio KJ, Stevenson JM. Principal component analysis of lifting waveforms. Clin Biomech. 2006;21(6):567–578.

    Google Scholar 

  23. Sadler EM, Graham RB, Stevenson JM. Gender difference and lifting technique under light load conditions: a principal component analysis. Theor Issues Ergon Sci. 2013;14(2):159–174.

    Google Scholar 

  24. Sheppard PS, Stevenson JM, Graham RB. Sex-based differences in lifting technique under increasing load conditions: a principal component analysis. Appl Ergon. 2016;54:186–195.

    CAS  PubMed  Google Scholar 

  25. Troje NF. Decomposing biological motion: a framework for analysis and synthesis of human gait patterns. J Vis. 2002;2(5):371–387.

    PubMed  Google Scholar 

  26. Federolf P, Reid R, Gilgien M, Haugen P, Smith G. The application of principal component analysis to quantify technique in sports. Scand J Med Sci Sports. 2014;24(3):491–499.

    CAS  PubMed  Google Scholar 

  27. Gløersen Ø, Myklebust H, Hallén J, Federolf P. Technique analysis in elite athletes using principal component analysis. J Sports Sci. 2018;36(2):229–237.

    PubMed  Google Scholar 

  28. Ross GB, Dowling B, Troje NF, Fischer SL, Graham RB. Objectively differentiating movement patterns between elite and novice athletes. Med Sci Sports Exerc. 2018;50(7):1457–1464.

    PubMed  Google Scholar 

  29. Armstrong DP, Ross GB, Graham RB, Fischer SL. Considering movement competency within physical employment standards. Work. 2019;63(4):603.

    PubMed  Google Scholar 

  30. Howarth SJ, Callaghan JP. Quantitative assessment of the accuracy for three interpolation techniques in kinematic analysis of human movement. Comput Methods Biomech Biomed Eng. 2010;13(6):847–55.

    Google Scholar 

  31. Wu G, Siegler S, Allard P, Kirtley C, Leardini A, Rosenbaum D, Whittle M, D’Lima D, D, Cristofolini L, Witte H, Schmid O, ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion—part I: ankle, hip, and spine. J Biomech. 2002;35(4):543–548.

  32. Wu G, Van der Helm FC, Veeger HD, Makhsous M, Van Roy P, Anglin C, Nagels J, Karduna AR, McQuade K, Wang X, Werner FW. ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion—Part II: shoulder, elbow, wrist and hand. J Biomech. 2005;38(5):981–992.

    CAS  PubMed  Google Scholar 

  33. Chaffin DB. Occupational biomechanics. New York: Wiley Interscience; 2006. p. 37–51.

    Google Scholar 

  34. Miranda H, Viikari-Juntura E, Martikainen R, Takala EP, Riihimäki H. A prospective study of work related factors and physical exercise as predictors of shoulder pain. Occup Environ Med. 2001;58(8):528–534.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Norman R, Wells R, Neumann P, Frank J, Shannon H, Kerr M, Study TO. A comparison of peak vs cumulative physical work exposure risk factors for the reporting of low back pain in the automotive industry. Clin Biomech. 1998;13(8):561–573.

    Google Scholar 

  36. Kerr MS, Frank JW, Shannon HS, Norman RW, Wells RP, Neumann WP, Bombardier C, Ontario Universities Back Pain Study Group. Biomechanical and psychosocial risk factors for low back pain at work. Am J Public Health. 2001;91(7):1069.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Gallagher S, Marras WS. Tolerance of the lumbar spine to shear: a review and recommended exposure limits. Clin Biomech. 2012;27(10):973–978.

    Google Scholar 

  38. Deluzio KJ, Astephen JL. Biomechanical features of gait waveform data associated with knee osteoarthritis: an application of principal component analysis. Gait Posture. 2007;25(1):86–93.

    CAS  PubMed  Google Scholar 

  39. Reid SM, Graham RB, Costigan PA. Differentiation of young and older adult stair climbing gait using principal component analysis. Gait Posture. 2010;31(2):197–203.

    PubMed  Google Scholar 

  40. Jackson JE, Edward A. User’s guide to principal components. New York: Willey; 1991. p. 40.

    Google Scholar 

  41. Sadler EM, Graham RB, Stevenson JM. The personal lift-assist device and lifting technique: a principal component analysis. Ergonomics. 2011;54(4):392–402.

    PubMed  Google Scholar 

  42. Brandon SC, Graham RB, Almosnino S, Sadler EM, Stevenson JM, Deluzio KJ. Interpreting principal components in biomechanics: representative extremes and single component reconstruction. J Electromyogr Kinesiol. 2013;23(6):1304–1310.

    PubMed  Google Scholar 

  43. Jorgensen MJ, Handa A, Veluswamy P, Bhatt M. The effect of pallet distance on torso kinematics and low back disorder risk. Ergonomics. 2005;48(8):949–963.

    PubMed  Google Scholar 

  44. van Dieën JH, Hoozemans MJ, Toussaint HM. Stoop or squat: a review of biomechanical studies on lifting technique. Clin Biomech. 1999;14(10):685–696.

    Google Scholar 

  45. Makhoul PJ, Sinden KE, MacPhee RS, Fischer SL. Relative contribution of lower body work as a biomechanical determinant of spine sparing technique during common paramedic lifting tasks. J Appl Biomech. 2017;33(2):137–143.

    PubMed  Google Scholar 

  46. Drake JD, Aultman CD, McGill SM, Callaghan JP. The influence of static axial torque in combined loading on intervertebral joint failure mechanics using a porcine model. Clin Biomech. 2005;20(10):1038–1045.

    Google Scholar 

  47. Aarås A, Westgaard RH, Stranden E. Postural angles as an indicator of postural load and muscular injury in occupational work situations. Ergonomics. 1988;31(6):915–933.

    PubMed  Google Scholar 

  48. Han S, Lee S. A vision-based motion capture and recognition framework for behavior-based safety management. Autom Constr. 2013;35:131–141.

    Google Scholar 

  49. Starbuck R, Seo J, Han S, Lee S. A stereo vision-based approach to marker-less motion capture for on-site kinematic modeling of construction worker tasks. Comput Civ Build Eng. 2014;2014:1094–1101.

    Google Scholar 

  50. Tsuang YH, Schipplein OD, Trafimow JH, Andersson GB. Influence of body segment dynamics on loads at the lumbar spine during lifting. Ergonomics. 1992;35(4):437–444.

    CAS  PubMed  Google Scholar 

  51. McGill SM, Norman RW. Effects of an anatomically detailed erector spinae model on L4L5 disc compression and shear. J Biomech. 1987;20(6):591–600.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was funded by Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant (RGPIN-2018-04483) and Ontario Ministry of Research and Innovation Early Research Award (ER16-12-163) held by S. Fischer.

Author information

Authors and Affiliations

  1. Department of Kinesiology, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada

    Daniel P. Armstrong, Aleksandra R. Budarick, Claragh E. E. Pegg, Ryan B. Graham & Steven L. Fischer

  2. School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, 75 Laurier Avenue East, Ottawa, ON, K1N 6N5, Canada

    Ryan B. Graham

Authors
  1. Daniel P. Armstrong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aleksandra R. Budarick
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Claragh E. E. Pegg
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ryan B. Graham
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Steven L. Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Steven L. Fischer.

Ethics declarations

Conflict of interest

Daniel P. Armstrong, Aleksandra R. Budarick, Claragh E.E. Pegg, Ryan B. Graham, and Steven L. Fischer declare that they have no conflict of interest.

Informed Consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all patients for being included in the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Armstrong, D.P., Budarick, A.R., Pegg, C.E.E. et al. Feature Detection and Biomechanical Analysis to Objectively Identify High Exposure Movement Strategies When Performing the EPIC Lift Capacity test. J Occup Rehabil 31, 50–62 (2021). https://doi.org/10.1007/s10926-020-09890-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10926-020-09890-2

Keywords

  • Automated pattern recognition
  • Lifting
  • Work capacity evaluation
  • Kinematics
  • Kinetics