Trunk and Spine Models for Instrumented Gait Analysis

  • Robert Needham
  • Aoife Healy
  • Nachiappan Chockalingam
Reference work entry


There are several types of motion capture systems which can measure trunk and spine movement as a part of gait analysis. These range from wearable sensors to optoelectronic systems. This chapter focuses on models used within optoelectronic systems and covers both two- and three-dimensional models. This chapter while providing an outline of the current thorax and pelvis models highlights novel concepts in terms of 3-dimensional clusters. Latest methods on data analysis techniques using vector coding have been outlined which will facilitate comprehensive reporting of the movement data.


Spine models Gait Analysis Thorax model 


  1. Armand S, Sangeux M, Baker R (2014) Optimal markers’ placement on the thorax for clinical gait analysis. Gait Posture 39(1):147–153CrossRefGoogle Scholar
  2. Baker R (2006) Gait analysis methods in rehabilitation. J Neuroeng Rehabil 3(1):4CrossRefGoogle Scholar
  3. Baker R (2013) Measuring Walking: A Handbook of Clinical Gait Analysis. Mac Keith Press, CambridgeGoogle Scholar
  4. Borhani M, McGregor AH, Bull AMJ (2013) An alternative technical marker set for the pelvis is more repeatable than the standard pelvic marker set. Gait Posture 38(4):1032–1037CrossRefGoogle Scholar
  5. Cappello A et al (2005) Soft tissue artifact compensation in knee kinematics by double anatomical landmark calibration: performance of a novel method during selected motor tasks. IEEE Trans Biomed Eng 52(6):992–998CrossRefGoogle Scholar
  6. Cappozzo A (1983) The forces and couples in the human trunk during level walking. J Biomech 16(4):265–277CrossRefGoogle Scholar
  7. Cappozzo A et al (1995) Position and orientation in space of bones during movement: anatomical frame definition and determination. Clin Biomech (Bristol, Avon) 10(4):171–178CrossRefGoogle Scholar
  8. Cappozzo A et al (1997) Surface-marker cluster design criteria for 3-D bone movement reconstruction. IEEE Trans Biomed Eng 44(12):1165–1174CrossRefGoogle Scholar
  9. Cappozzo A et al (2005) Human movement analysis using stereophotogrammetry. Part 1: theoretical background. Gait Posture 21(2):186–196Google Scholar
  10. Chockalingam N et al (2003) A comparison of three kinematic systems for assessing spinal range of movement. Int J Ther Rehabil 10(9):402–407CrossRefGoogle Scholar
  11. Chou R et al (2007) Diagnosis and treatment of low back pain: a joint clinical practice guideline from the American College of Physicians and the American Pain Society. Ann Intern Med 147(7):478–491CrossRefGoogle Scholar
  12. Crosbie J, Vachalathiti R, Smith R (1997a) Age, gender and speed effects on spinal kinematics during walking. Gait Posture 5(1):13–20CrossRefGoogle Scholar
  13. Crosbie J, Vachalathiti R, Smith R (1997b) Patterns of spinal motion during walking. Gait Posture 5(1):6–12CrossRefGoogle Scholar
  14. Don R et al (2012) Instrumental measures of spinal function: is it worth? A state-of-the art from a clinical perspective. Eur J Phys Rehabil Med 48(2):255–273MathSciNetGoogle Scholar
  15. Frigo C et al (1998) Functionally oriented and clinically feasible quantitative gait analysis method. Med Biol Eng Comput 36(2):179–185CrossRefGoogle Scholar
  16. Frigo C et al (2003) The upper body segmental movements during walking by young females. Clin Biomech (Bristol, Avon) 18(5):419–425CrossRefGoogle Scholar
  17. Hamill J, Palmer C, Van Emmerik REA (2012) Coordinative variability and overuse injury. SMARTT 4(1):45Google Scholar
  18. Haneline MT et al (2008) Determining spinal level using the inferior angle of the scapula as a reference landmark: a retrospective analysis of 50 radiographs. J Can Chiropr Assoc 52(1):24–29Google Scholar
  19. Hara R et al (2014) Quantification of pelvic soft tissue artifact in multiple static positions. Gait Posture 39(2):712–717CrossRefGoogle Scholar
  20. Heyrman L, Feys H, Molenaers G, Jaspers E, Van de Walle P, Monari D, Aertbeliën E, Desloovere K (2013) Reliability of head and trunk kinematics during gait in children with spastic diplegia. Gait Posture 37(3):424–429Google Scholar
  21. Heyrman L et al (2014) Altered trunk movements during gait in children with spastic diplegia: compensatory or underlying trunk control deficit? Res Dev Disabil 35(9):2044–2052CrossRefGoogle Scholar
  22. Kisho Fukuchi R et al (2010) Evaluation of alternative technical markers for the pelvic coordinate system. J Biomech 43(3):592–594CrossRefGoogle Scholar
  23. Leardini A et al (2005) Human movement analysis using stereophotogrammetry. Part 3. Soft tissue artifact assessment and compensation. Gait Posture 21(2):212–225CrossRefGoogle Scholar
  24. Leardini A et al (2011) Multi-segment trunk kinematics during locomotion and elementary exercises. Clin Biomech (Bristol, Avon) 26(6):562–571CrossRefGoogle Scholar
  25. Lee R (2002) Measurement of movements of the lumbar spine. Physiother Theory Pract 18(4):159–164CrossRefGoogle Scholar
  26. Levine D, Richards J, Whittle MW (2012) Whittle’s Gait Analysis, fifth ed. Churchill Livingstone, LondonGoogle Scholar
  27. Lu TW, O’Connor JJ (1999) Bone position estimation from skin marker co-ordinates using global optimisation with joint constraints. J Biomech 32(2):129–134CrossRefGoogle Scholar
  28. MacWilliams BA et al (2013) Assessment of three-dimensional lumbar spine vertebral motion during gait with use of indwelling bone pins. J Bone Joint Surg (Am Vol) 95(23):e1841–e1848Google Scholar
  29. Manal K et al (2000) Comparison of surface mounted markers and attachment methods in estimating tibial rotations during walking: an in vivo study. Gait Posture 11(1):38–45CrossRefGoogle Scholar
  30. Mason DL et al (2016) Reproducibility of kinematic measures of the thoracic spine, lumbar spine and pelvis during fast running. Gait Posture 43:96–100CrossRefGoogle Scholar
  31. McClelland JA et al (2010) Alternative modelling procedures for pelvic marker occlusion during motion analysis. Gait Posture 31(4):415–419CrossRefGoogle Scholar
  32. McGinley JL et al (2009) The reliability of three-dimensional kinematic gait measurements: a systematic review. Gait Posture 29(3):360–369CrossRefGoogle Scholar
  33. Needham R, Naemi R, Chockalingam N (2014) Quantifying lumbar-pelvis coordination during gait using a modified vector coding technique. J Biomech 47(5):1020–1026CrossRefGoogle Scholar
  34. Needham RA, Naemi R, Chockalingam N (2015) A new coordination pattern classification to assess gait kinematics when utilising a modified vector coding technique. J Biomech 48(12):3506–3511CrossRefGoogle Scholar
  35. Needham R, Naemi R, Healy A, Chockalingam N (2016a) Multi-segment kinematic model to assess three-dimensional movement of the spine and back during gait. Prosthet Orthot Int 40(5):624–635Google Scholar
  36. Needham R, Stebbins J, Chockalingam N (2016b) Three-dimensional kinematics of the lumbar spine during gait using marker-based systems: a systematic review. J Med Eng Technol 40(4):172–185CrossRefGoogle Scholar
  37. Nguyen TC, Baker R (2004) Two methods of calculating thorax kinematics in children with myelomeningocele. Clin Biomech 19(10):1060–1065CrossRefGoogle Scholar
  38. Perry J (1992) Gait Analysis: Normal and Pathological Function. SLACK IncorporatedGoogle Scholar
  39. Perry J, Burnfield J (2010) Gait analysis: normal and pathological function, 2nd ed. Thorofare, NJ: SLACK IncorporatedGoogle Scholar
  40. Peters A et al (2010) Quantification of soft tissue artifact in lower limb human motion analysis: A systematic review. Gait Posture 31(1):1–8CrossRefGoogle Scholar
  41. Rab G, Petuskey K, Bagley A (2002) A method for determination of upper extremity kinematics. Gait Posture 15(2):113–119CrossRefGoogle Scholar
  42. Richards J (2008) Biomechanics in Clinic and Research. Churchill Livingstone, LondonGoogle Scholar
  43. Rozumalski A et al (2008) The in vivo three-dimensional motion of the human lumbar spine during gait. Gait Posture 28(3):378–384CrossRefGoogle Scholar
  44. Schache AG et al (2002) Intra-subject repeatability of the three dimensional angular kinematics within the lumbo-pelvic-hip complex during running. Gait Posture 15(2):136–145CrossRefGoogle Scholar
  45. Seay J, Selbie WS, Hamill J (2008) In vivo lumbo-sacral forces and moments during constant speed running at different stride lengths. J Sports Sci 26(14):1519–1529CrossRefGoogle Scholar
  46. Seay JF, Van Emmerik REA, Hamill J (2011) Influence of low back pain status on pelvis-trunk coordination during walking and running. Spine 36(16):E1070–E1079CrossRefGoogle Scholar
  47. Steele J et al (2015) A randomized controlled trial of the effects of isolated lumbar extension exercise on lumbar kinematic pattern variability during gait in chronic low back pain. PM R 8(2):105–114CrossRefGoogle Scholar
  48. Syczewska M, Oberg T, Karlsson D (1999) Segmental movements of the spine during treadmill walking with normal speed. Clin Biomech (Bristol, Avon) 14(6):384–388CrossRefGoogle Scholar
  49. Taylor NF, Evans OM, Goldie PA (1996) Angular movements of the lumbar spine and pelvis can be reliably measured after 4 minutes of treadmill walking. Clin Biomech (Bristol, Avon) 11(8):484–486CrossRefGoogle Scholar
  50. Thorstensson A et al (1984) Trunk movements in human locomotion. Acta Physiol Scand 121(1):9–22CrossRefGoogle Scholar
  51. Thurston AJ (1982) Repeatability studies of a television/computer system for measuring spinal and pelvic movements. J Biomed Eng 4(2):129–132CrossRefGoogle Scholar
  52. Van Emmerik REA et al (2005) Age-related changes in upper body adaptation to walking speed in human locomotion. Gait Posture 22(3):233–239CrossRefGoogle Scholar
  53. Vogt L et al (2001) Influences of nonspecific low back pain on three-dimensional lumbar spine kinematics in locomotion. Spine 26(17):1910–1919CrossRefGoogle Scholar
  54. Wu G et al (2002) 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 35(4):543–548CrossRefGoogle Scholar
  55. Wu G et al (2005) 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 38(5):981–992CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Robert Needham
    • 1
  • Aoife Healy
    • 1
  • Nachiappan Chockalingam
    • 1
  1. 1.Life Sciences and EducationStaffordshire UniversityStoke On TrentUK

Section editors and affiliations

  • Sebastian I. Wolf
    • 1
  1. 1.Movement Analysis LaboratoryClinic for Orthopedics and Trauma Surgery; Center for Orthopedics, Trauma Surgery and Spinal Cord Injury;Heidelberg University HospitalHeidelbergGermany

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