Skip to main content

Advertisement

SpringerLink
Log in

Towards the Use of 2D Video-Based Markerless Motion Capture to Measure and Parameterize Movement During Functional Capacity Evaluation

  • Published:
Journal of Occupational Rehabilitation Aims and scope Submit manuscript

Abstract

Purpose The objective of this study was to determine the agreement of kinematic parameters calculated from motion data collected via a 2D video-based pose-estimation (markerless motion capture) approach and a laboratory-based 3D motion capture approach during a floor-to-waist height functional lifting test. Method Twenty healthy participants each performed three floor-to-waist height lifts. Participants’ lifts were captured simultaneously using 2D video (camcorder) in the sagittal plane and 3D motion capture (Vicon, Oxford, UK). The three lifts were representative of a perceived light, medium, and heavy load. Post-collection, video data were processed through a pose-estimation software (i.e., markerless motion capture). Motion data from 3D motion capture and video-based markerless motion capture were each used to calculate objective measures of interest relevant to a functional capacity evaluation (i.e., posture, balance, distance of the load from the body, and coordination). Bland–Altman analyses were used to calculate agreement between the two methods. Results Bland–Altman analysis revealed that mean differences ranged from 1.9° to 22.1° for posture and coordination-based metrics calculated using markerless and 3D motion capture, respectively. Limits of agreement for most posture and coordination measures were approximately + 20°. Conclusions 2D video-based pose estimation offers a strategy to objectively measure movement and subsequently calculated metrics of interest within an FCE context and setting, but at present the agreement between metrics calculated using 2D video-based methods and 3D motion capture is insufficient. Therefore, continued effort is required to improve the accuracy of 2D-video based pose estimation prior to inclusion into functional testing paradigms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

FCE:

Functional capacity evaluation

RTW:

Return to work

BOS:

Base of support

COG:

Center of gravity

MARP:

Mean absolute relative phase

CRP:

Continuous relative phase

MMH:

Manual materials handling

ASIS:

Anterior superior iliac spine

SI:

Superior inferior

AP:

Anterior posterior

ML:

Medial lateral

CBOS:

Center of base of support

FSL:

Functional stability limit

B–A:

Bland–Altman

References

  1. King PM, Tuckwell N, Bawett TE. A critical review of functional capacity evaluations. Phys Ther. 1998;78(8):852–866.

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  3. Dempsey PG. A critical review of biomechanical, epidemiological, physiological and psychophysical criteria for designing manual materials handling tasks. Ergonomics. 1998;41(1):73–88.

    Article  CAS  Google Scholar 

  4. Tengland PA. The concept of work ability. J Occup Rehabil. 2011;21:275–285.

    Article  Google Scholar 

  5. Harbin G, Olson J. Post-offer, pre-placement testing in industry. Am J Ind Med. 2005;47(4):296–307.

    Article  Google Scholar 

  6. Innes E. Reliability and validity of functional capacity evaluations: an update. Int J Disabil Manag. 2006;1(1):135–148.

    Article  Google Scholar 

  7. Trippolini MA, Dijkstra PU, Jansen B, Oesch P, Geertzen JHB, Reneman MF. Reliability of clinician rated physical effort determination during functional capacity evaluation in patients with chronic musculoskeletal pain. J Occup Med Toxicol. 2014;24:361–369.

    CAS  Google Scholar 

  8. 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.

  9. Reneman MF, Fokkens AS, Dijkstra PU, Geertzen JHB, Groothoff JW. Testing lifting capacity: validity of determining effort level by means of observation. Spine. 2005;30(2):40–46.

    Article  Google Scholar 

  10. 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.

    Article  CAS  Google Scholar 

  11. Cao Z, Hidalgo Martinez G, Simon T, Wei SE, Sheikh YA. OpenPose: realtime multi-person 2D pose estimation using part affinity fields. IEEE Trans Pattern Anal Mach Intell. 2019;43(1):172–186.

    Article  Google Scholar 

  12. McKinnon CD, Sonne MW, Keir PJ. Assessment of joint angle and reach envelope demands using a video—based physical demands description tool. Hum Factors. 2020. https://doi.org/10.1177/0018720820951349.

    Article  PubMed  Google Scholar 

  13. Armstrong DP, Budarick AR, Pegg CEE, Graham RB, Fischer SL. Feature detection and biomechanical analysis to objectively identify high exposure movement strategies when performing the EPIC lift capacity test. J Occup Rehab. 2021;31:50–62.

    Article  Google Scholar 

  14. Holbein MA, Redfern MS. Functional stability limits while holding loads in various positions. Int J Ind Ergon. 1997;19(5):387–395.

    Article  CAS  Google Scholar 

  15. Armstrong DP, Ross GB, Graham RB, Fischer SL. Considering movement competency within physical employment standards. Work. 2019;63(4):603–613.

    Article  Google Scholar 

  16. Trafimow J, Aruin AS. The use of negative acceleration as accessory force during lifting. Adv Orthop. 2018. https://doi.org/10.1155/2018/9164590.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Burgess-Limerick R, Abernethy B, Neal RJ. Relative phase quantifies interjoint coordination. J Biomech. 1993;26(1):91–94.

    Article  CAS  Google Scholar 

  18. Galgon AK, Shewokis PA. Using mean absolute relative phase, deviation phase and point-estimation relative phase to measure postural coordination in a serial reaching task. J Sports Sci Med. 2016;15:131–141.

    PubMed  PubMed Central  Google Scholar 

  19. Lowe BD, Weir P, Andrews D. Observation-based posture assessment: review of current practice and recommendations for improvement; 2014.

  20. 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.

    Article  CAS  Google Scholar 

  21. 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.

    Article  CAS  Google Scholar 

  22. Liao JJZ. Sample size calculation for an agreement study. Pharm Stat. 2020;132:125–132.

    Google Scholar 

  23. Howarth SJ, Callaghan JP. Quantitative assessment of the accuracy for three interpolation techniques in kinematic analysis of human movement Quantitative assessment of the accuracy for three interpolation techniques in kinematic analysis of human movement. Comput Methods Biomech Biomed Eng. 2010;13(6):847–855.

    Article  Google Scholar 

  24. Wu G, Siegler S, Allard P, Kirtley C, Leardini A, Rosenbaum D, Whittle M, D’Lima DD, 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.

    Article  Google Scholar 

  25. 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.

    Article  CAS  Google Scholar 

  26. Nussbaum MA, Zhang X. Heuristics for locating upper extremity joint centres from a reduced set of surface markers. Hum Mov Sci. 2000;19(5):797–816.

    Article  Google Scholar 

  27. Bell AL, Brand RA, Pedersen DR. Prediction of hip joint centre location from external landmarks. Hum Mov Sci. 1989;8(1):3–16.

    Article  Google Scholar 

  28. Bell AL, Pedersen DR, Brand RA. A comparison of the accuracy of several hip center location prediction methods. J Biomech. 1989;23(6):617–621.

    Article  Google Scholar 

  29. Winter DA. Biomechanics and motor control of human movement. New York: Wiley; 2009.

    Book  Google Scholar 

  30. Robertson DGE, Caldwell GE, Hamill J. Research methods in biomechanics. 2nd ed. Publisher; 2014.

  31. Drillis R, Contini R. Body segment parameters. New York: Office of Vocational Rehabilitation, (Report No.: No. 1166-03.). 1966.

  32. Holbein-Jenny MA, McDermott K, Shaw C, Demchak J. Validity of functional stability limits as a measure of balance in adults aged 23–73 years. Ergonomics. 2007;50(5):631–646.

    Article  Google Scholar 

  33. Lamb PF, Stöckl M. On the use of continuous relative phase: review of current approaches and outline for a new standard. Clin Biomech. 2014;29(5):484–493.

    Article  Google Scholar 

  34. Albert WJ, Wrigley AT, McLean RB. Are males and females similarly consistent in their respective lifting patterns? Theor Issues Ergon Sci. 2008;9(4):347–358.

    Article  Google Scholar 

  35. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet. 1986;327(8476):307–310.

    Article  Google Scholar 

  36. Keogh JWL, Cox A, Anderson S, Liew B, Olsen A, Schram B, Furness J. Reliability and validity of clinically accessible smartphone applications to measure joint range of motion: a systematic review. PLoS ONE. 2019;14(5):1–24.

    Article  Google Scholar 

  37. Walfish S. A review of statistical outlier methods. Pharm Technol. 2006;30(11):82.

    Google Scholar 

  38. Schurr SA, Marshall AN, Resch JE, Saliba SA. Two-dimensional video analysis is comparable to 3D motion capture in lower extremity movement assessment. Int J Sports Phys Ther. 2017;12(2):163–172.

    PubMed  PubMed Central  Google Scholar 

  39. Pfister A, West AM, Bronner S, Noah JA. Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis. J Med Eng Technol. 2014;38(5):274–280.

    Article  Google Scholar 

  40. Mentiplay BF, Perraton LG, Bower KJ, Pua YH, McGaw R, Heywood S, Clark RA. Gait assessment using the Microsoft Xbox One Kinect: concurrent validity and inter-day reliability of spatiotemporal and kinematic variables. J Biomech. 2015;48(10):2166–2170.

    Article  Google Scholar 

  41. Clark RA, Pua YH, Fortin K, Ritchie C, Webster KE, Denehy L, Bryant AL. Validity of the Microsoft Kinect for assessment of postural control. Gait Posture. 2012;36(3):372–377.

    Article  Google Scholar 

Download references

Funding

This study was supported by an Ontario Early Career Award (ER16-12-163) held by S. Fischer. S. Remedios received partial support via the Employers' Advocacy Council, Occupational Health and Safety Research Scholarship.

Author information

Authors and Affiliations

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

    Sarah M. Remedios & Steven L. Fischer

Authors
  1. Sarah M. Remedios
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Steven L. Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception, design and data analysis. Data collection was performed by Sarah M. Remedios. All authors contributed to drafting of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Steven L. Fischer.

Ethics declarations

Conflict of interest

Sarah M. Remedios and Steven L. Fischer declare that they have no conflict of interest.

Consent to Participate

All participants provided written informed consent prior to participation.

Ethics approval

This study was approved by the University’s Institutional Ethics Board.

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 Helinski 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

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Remedios, S.M., Fischer, S.L. Towards the Use of 2D Video-Based Markerless Motion Capture to Measure and Parameterize Movement During Functional Capacity Evaluation. J Occup Rehabil 31, 754–767 (2021). https://doi.org/10.1007/s10926-021-10002-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10926-021-10002-x

Keywords

Search

Navigation