Skip to main content
SpringerLink
Log in
Book cover

Handbook of Human Motion pp 1–27Cite as

Measures to Determine Dynamic Balance

  • Living reference work entry
  • First Online:

  • 241 Accesses

Abstract

This chapter discusses the theory of dynamic balance as is currently understood and the various methods of assessing it. In order to test dynamic balance, it must first be defined, and this is where an understanding is still evolving. As such, a number of balance assessment methods have evolved concurrently.

The chapter starts by introducing some of the concepts of static balance and obvious signs of balance loss. Next, functional testing methods including the TUGT, BBS, DGI, and TBGA are introduced. These are tests that are relatively simple to administer and rely on a rater’s assessment of signs like postural instability or sway in completing a task. From there, instrumentation typically found in a movement analysis lab is described along with the assessments used to quantify dynamic balance. Finally, more advanced mathematical methods of teasing out balance impairments from data are described. These last analyses include usage of Lyapunov exponents, autocorrelation, margin of support, and deviation of the COM from the interfoot line.

Studies indicating the validity of all methods presented are also described in greater or lesser detail as needed throughout the chapter. This serves to introduce readers to the potential populations in which balance deficits exist, as well as the relative validity and reliability of the tests. In some cases, tests are valid with one population, but not with another. At this juncture, there are a myriad of balance tests, and more are being developed as this is being written. Ultimately, researchers and clinicians must choose the appropriate test based on who they are testing, what specific symptoms they wish to identify or diagnose, and the consideration that balance is multifactoral.

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

References

  • Alberts JL, Hirsch JR, Koop MM, Schindler DD, Kana DE, Linder SM, … Thota AK (2015) Using accelerometer and gyroscopic measures to quantify postural stability. J Athl Train 50(6):578–588. doi:10.4085/1062-6050-50.2.01

    Google Scholar 

  • Amboni M, Barone P, Hausdorff JM (2013) Cognitive contributions to gait and falls: evidence and implications. Mov Disord 28(11):1520–1533. doi:10.1002/mds.25674

    Article  Google Scholar 

  • Ashbaugh MS, Chicone CC, Cushman RH (1991) The twisting tennis racket. J Dyn Diff Equat 3(1):67–85. doi:10.1007/BF01049489

    Google Scholar 

  • Azadian E, Torbati HRT, Kakhki ARS, Farahpour N (2016) The effect of dual task and executive training on pattern of gait in older adults with balance impairment: a randomized controlled trial. Arch Gerontol Geriatr 62:83–89. doi:10.1016/j.archger.2015.10.001

    Article  Google Scholar 

  • Banks D, McMorris FR, Arabie P, Gaul W (eds) (2004) Classification, clustering, and data mining applications. Springer, Berlin/Heidelberg. doi:10.1007/978-3-642-17103-1

    Google Scholar 

  • Berg K, Wood-Dauphine S, Williams JI, Gayton D (1989) Measuring balance in the elderly: preliminary development of an instrument. Physiother Can 41(6):304–311. doi:10.3138/ptc.41.6.304

    Article  Google Scholar 

  • Berg KO, Wood-Dauphinee SL, Williams JI, Maki B (1992) Measuring balance in the elderly: validation of an instrument. Can J Public Health 83(Suppl 2):S7–S11

    Google Scholar 

  • Berg WP, Alessio HM, Mills EM, Tong C (1997) Circumstances and consequences of falls in independent community-dwelling older adults. Age Ageing 26(4):261–268. doi:10.1093/ageing/26.4.261

    Article  Google Scholar 

  • Bischoff HA, Stähelin HB, Monsch AU, Iversen MD, Weyh A, von Dechend M, … Theiler R (2003) Identifying a cut-off point for normal mobility: a comparison of the timed “up and go” test in community-dwelling and institutionalised elderly women. Age Ageing 32(3):315–320. doi:10.1093/ageing/32.3.315

    Google Scholar 

  • Boulgarides LK, McGinty SM, Willett JA, Barnes CW (2003) Use of clinical and impairment-based tests to predict falls by community-dwelling older adults. Phys Ther 83(4):328–339

    Google Scholar 

  • Carty CP, Mills P, Barrett R (2011) Recovery from forward loss of balance in young and older adults using the stepping strategy. Gait Posture 33(2):261–267. doi:10.1016/j.gaitpost.2010.11.017

    Article  Google Scholar 

  • Centers for Disease Control (CDC): STEADI Materials for Health Care Providers|STEADI – Older Adult Fall Prevention|CDC Injury Center (n.d.) http://www.cdc.gov/steadi/materials.html. Retrieved 10 Aug 2016

  • Chou L-S, Kaufman KR, Hahn ME, Brey RH (2003) Medio-lateral motion of the center of mass during obstacle crossing distinguishes elderly individuals with imbalance. Gait Posture 18(3):125–133

    Article  Google Scholar 

  • Clark RA, Pua Y-H, Bryant AL, Hunt MA (2013) Validity of the Microsoft Kinect for providing lateral trunk lean feedback during gait retraining. Gait Posture 38(4):1064–1066. doi:10.1016/j.gaitpost.2013.03.029

    Article  Google Scholar 

  • Day KV, Kautz SA, Wu SS, Suter SP, Behrman AL (2012) Foot placement variability as a walking balance mechanism post-spinal cord injury. Clin Biomech (Bristol, Avon) 27(2):145–150. doi:10.1016/j.clinbiomech.2011.09.001

    Article  Google Scholar 

  • Dingwell JB, Cusumano JP, Sternad D, Cavanagh PR (2000) Slower speeds in patients with diabetic neuropathy lead to improved local dynamic stability of continuous overground walking. J Biomech 33(10):1269–1277

    Article  Google Scholar 

  • Dutta A, Goswami A (2010) Human postural model that captures rotational inertia. Am Soc Biomech. Retrieved from http://ambarish.com/paper/Dutta_Goswami_ASB2010.pdf

  • Ellis RJ, Ng YS, Zhu S, Tan DM, Anderson B, Schlaug G, Wang Y (2015) A validated smartphone-based assessment of gait and gait variability in Parkinson’s disease. PLoS ONE 10(10). doi:10.1371/journal.pone.0141694

    Google Scholar 

  • Faber MJ, Bosscher RJ, van Wieringen PC (2006) Clinimetric properties of the performance-oriented mobility assessment. Phys Ther 86(7):944–954

    Google Scholar 

  • Garland SJ, Stevenson TJ, Ivanova T (1997) Postural responses to unilateral arm perturbation in young, elderly, and hemiplegic subjects. Arch Phys Med Rehabil 78(10):1072–1077

    Article  Google Scholar 

  • Hausdorff JM, Zemany L, Peng C-K, Goldberger AL (1999) Maturation of gait dynamics: stride-to-stride variability and its temporal organization in children. J Appl Physiol 86(3):1040–1047

    Google Scholar 

  • Herman T, Giladi N, Hausdorff JM (2011) Properties of the “timed up and go” test: more than meets the eye. Gerontology 57(3):203–210. doi:10.1159/000314963

    Article  Google Scholar 

  • Hof AL, van Bockel RM, Schoppen T, Postema K (2007) Control of lateral balance in walking: experimental findings in normal subjects and above-knee amputees. Gait Posture 25(2):250–258. doi:10.1016/j.gaitpost.2006.04.013

    Article  Google Scholar 

  • Hof AL, Vermerris SM, Gjaltema WA (2010) Balance responses to lateral perturbations in human treadmill walking. J Exp Biol 213(15):2655–2664. doi:10.1242/jeb.042572

    Article  Google Scholar 

  • Howell DR, Osternig LR, Chou L-S (2013) Dual-task effect on gait balance control in adolescents with concussion. Arch Phys Med Rehabil 94(8):1513–1520. doi:10.1016/j.apmr.2013.04.015

    Article  Google Scholar 

  • Hsue B-J, Miller F, Su F-C (2009a) The dynamic balance of the children with cerebral palsy and typical developing during gait. Part I: spatial relationship between COM and COP trajectories. Gait Posture 29(3):465–470. doi:10.1016/j.gaitpost.2008.11.007

    Article  Google Scholar 

  • Hsue B-J, Miller F, Su F-C (2009b) The dynamic balance of the children with cerebral palsy and typical developing during gait. Part II: instantaneous velocity and acceleration of COM and COP and their relationship. Gait Posture 29(3):471–476. doi:10.1016/j.gaitpost.2008.11.008

    Article  Google Scholar 

  • Kegelmeyer DA, Kloos AD, Thomas KM, Kostyk SK (2007) Reliability and validity of the Tinetti Mobility Test for individuals with Parkinson disease. Phys Ther 87(10):1369–1378. doi:10.2522/ptj.20070007

    Article  Google Scholar 

  • Korner-Bitensky N, Wood-Dauphinee S, Teasell R (2006) Best versus actual practices in stroke rehabilitation: results of the Canadian National Survey. Stroke 37:631

    Article  Google Scholar 

  • Krishnan LVP, O’Kane KSP, Gill-Body KMP (2002) Reliability of a modified version of the Dynamic Gait Index – a pilot study. Neurol Rep 26(1):8–14

    Article  Google Scholar 

  • Lafond D, Duarte M, Prince F (2004) Comparison of three methods to estimate the center of mass during balance assessment. J Biomech 37(9):1421–1426. doi:10.1016/S0021-9290(03)00251-3

    Article  Google Scholar 

  • Lamoth CJ, van Deudekom FJ, van Campen JP, Appels BA, de Vries OJ, Pijnappels M (2011) Gait stability and variability measures show effects of impaired cognition and dual tasking in frail people. J Neuroeng Rehabil 8:2. doi:10.1186/1743-0003-8-2

    Article  Google Scholar 

  • Lee H, Sullivan SJ, Schneiders AG (2013) The use of the dual-task paradigm in detecting gait performance deficits following a sports-related concussion: a systematic review and meta-analysis. J Sci Med Sport 16(1):2–7. doi:10.1016/j.jsams.2012.03.013

    Article  Google Scholar 

  • Lewek MD, Bradley CE, Wutzke CJ, Zinder SM (2014) The relationship between spatiotemporal gait asymmetry and balance in individuals with chronic stroke. J Appl Biomech 30(1):31–36. doi:10.1123/jab.2012-0208

    Article  Google Scholar 

  • Lundin-Olsson L, Nyberg L, Gustafson Y (1997) “Stops walking when talking” as a predictor of falls in elderly people. Lancet (London, England) 349(9052):617. doi:10.1016/S0140-6736(97)24009-2

    Article  Google Scholar 

  • Maranhão-Filho PA, Maranhão ET, Lima MA, da Silva MM (2011) Rethinking the neurological examination II: dynamic balance assessment. Arq Neuropsiquiatr 69(6):959–963. doi:10.1590/S0004-282X2011000700022

    Article  Google Scholar 

  • Matsushima A, Kunihiro Y, Hirokazu G, Asuka M, Setsuko M, Katsuya N, Akinori N, Shu-ichi I (2015) Clinical assessment of standing and gait in ataxic patients using a triaxial accelerometer. Cerebellum Ataxias 2:9. doi:10.1186/s40673-015-0028-9

    Article  Google Scholar 

  • McConvey J, Bennett SE (2005) Reliability of the Dynamic Gait Index in individuals with multiple sclerosis. Arch Phys Med Rehabil 86(1):130–133

    Article  Google Scholar 

  • McCrum C, Eysel-Gosepath K, Epro G, Meijer K, Savelberg HHCM, Brüggemann G-P, Karamanidis K (2014) Deficient recovery response and adaptive feedback potential in dynamic gait stability in unilateral peripheral vestibular disorder patients. Physiol Rep 2(12):e12222. doi: 10.14814/phy2.12222

    Google Scholar 

  • Monjezi S, Negahban H, Tajali S, Yadollahpour N, Majdinasab N (2016) Effects of dual-task balance training on postural performance in patients with multiple sclerosis: a double-blind, randomized controlled pilot trial. Clin Rehabil. doi:10.1177/0269215516639735

    Google Scholar 

  • Montero-Odasso M, Casas A, Hansen KT, Bilski P, Gutmanis I, Wells JL, Borrie MJ (2009) Quantitative gait analysis under dual-task in older people with mild cognitive impairment: a reliability study. J Neuroeng Rehabil 6:35. doi:10.1186/1743-0003-6-35

    Article  Google Scholar 

  • Montero-Odasso M, Muir SW, Speechley M (2012) Dual-task complexity affects gait in people with mild cognitive impairment: the interplay between gait variability, dual tasking, and risk of falls. Arch Phys Med Rehabil 93(2):293–299. doi:10.1016/j.apmr.2011.08.026

    Article  Google Scholar 

  • Muhaidat J, Kerr A, Evans JJ, Pilling M, Skelton DA (2014) Validity of simple gait-related dual-task tests in predicting falls in community-dwelling older adults. Arch Phys Med Rehabil 95(1):58–64. doi:10.1016/j.apmr.2013.07.027

    Article  Google Scholar 

  • Muir SW, Berg K, Chesworth B, Speechley M (2008) Use of the Berg Balance Scale for predicting multiple falls in community-dwelling elderly people: a prospective study. Phys Ther 88(4):449–459. doi:10.2522/ptj.20070251

    Article  Google Scholar 

  • Muir JW, Kiel DP, Hannan M, Magaziner J, Rubin CT (2013) Dynamic parameters of balance which correlate to elderly persons with a history of falls. PLoS One 8(8):e70566. doi:10.1371/journal.pone.0070566

    Article  Google Scholar 

  • Niiler T, Miller F, Marchesi S, Henley J (2007) Comparison of CP and normal gait using a kinematic balance index. In: Abstracts of the 16th annual meeting of ESMAC (European Society of Movement Analysis for Adults and Children), Athens, 27–29 Sept 2007. Gait Posture 26(Suppl 1):S29–S30.

    Google Scholar 

  • Niiler T, Henley J, Marchesi S, Miller F (2009) Rectus transfer patients show improved dynamic balance post-surgically. In Proceedings of the 14th annual meeting of the gait and clinical movement analysis society (GCMAS), Denver, 10–13 Mar 2009

    Google Scholar 

  • Niiler T, Henley J, Miller F (2010) Development of dynamic balance in adolescence. In: Proceedings of the Joint ESMAC and GCMAS (JEGM) conference, Miami, 12–15 May 2010

    Google Scholar 

  • Niiler T, Henley J, Miller F (2017) Center of mass perturbation as a normalizable estimate of dynamic balance in gait: an application comparing typically developing children with spastic cerebral palsy. arXiv:1701.00507 [Physics]. Retrieved from http://arxiv.org/abs/1701.00507

  • O’Sullivan M, Blake C, Cunningham C, Boyle G, Finucane C (2009) Correlation of accelerometry with clinical balance tests in older fallers and non-fallers. Age Ageing 38(3):308–313. doi:10.1093/ageing/afp009

    Article  Google Scholar 

  • Peterson DS, Horak FB (2016) Effects of freezing of gait on postural motor learning in people with Parkinson’s disease. Neuroscience 334:283–289. doi:10.1016/j.neuroscience.2016.08.017

    Google Scholar 

  • Podsiadlo D, Richardson S (1991) The timed “up & go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 39(2):142–148. doi:10.1111/j.1532-5415.1991.tb01616.x

    Article  Google Scholar 

  • Richards JG (1999) The measurement of human motion: a comparison of commercially available systems. Hum Mov Sci 18(5):589–602. doi:10.1016/S0167-9457(99)00023-8

    Article  Google Scholar 

  • Rosenblatt NJ, Grabiner MD (2010) Measures of frontal plane stability during treadmill and overground walking. Gait Posture 31(3):380–384. doi:10.1016/j.gaitpost.2010.01.002

    Article  Google Scholar 

  • Rosenstein MT, Collins JJ, DeLuca CJ (1993) A practical method for calculating largest Lyapunov exponents from small data sets. Phys D 65:117–134

    Article  MathSciNet  MATH  Google Scholar 

  • Santos GM, Souza ACS, Virtuoso JF, Tavares GMS, Mazo GZ (2011) Predictive values at risk of falling in physically active and no active elderly with Berg Balance Scale. Brazilian J Phys Ther 15(2):95–101. doi:10.1590/S1413-35552011000200003

    Article  Google Scholar 

  • Schlenstedt C, Brombacher S, Hartwigsen G, Weisser B, Möller B, Deuschl G (2016) Comparison of the Fullerton Advanced Balance Scale, Mini-BESTest, and Berg Balance Scale to predict falls in Parkinson disease. Phys Ther 96(4):494–501. doi:10.2522/ptj.20150249

    Article  Google Scholar 

  • Schrager MA, Kelly VE, Price R, Ferrucci L, Shumway-Cook A (2008) The effects of age on medio-lateral stability during normal and narrow base walking. Gait Posture 28(3):466–471. doi:10.1016/j.gaitpost.2008.02.009

    Article  Google Scholar 

  • Shumway-Cook A, Baldwin M, Polissar NL, Gruber W (1997) Predicting the probability for falls in community-dwelling older adults. Phys Ther 77(8):812–819

    Google Scholar 

  • Silsupadol P, Siu K-C, Shumway-Cook A, Woollacott MH (2006) Training of balance under single- and dual-task conditions in older adults with balance impairment. Phys Ther 86(2):269–281

    Google Scholar 

  • Smeesters C, Hayes WC, McMahon TA (2001) Disturbance type and gait speed affect fall direction and impact location. J Biomech 34(3):309–317. https://doi.org/10.1016/S0021-9290(00)00200-1

    Google Scholar 

  • Socie MJ, Motl RW, Pula JH, Sandroff BM, Sosnoff JJ (2013) Gait variability and disability in multiple sclerosis. Gait Posture 38(1):51–55. doi:10.1016/j.gaitpost.2012.10.012

    Article  Google Scholar 

  • Springer BA, Marin R, Cyhan T, Roberts H, Gill NW (2007) Normative values for the unipedal stance test with eyes open and closed. J Geriatr Phys Ther 30(1):8–15

    Article  Google Scholar 

  • Stodolka J, Golema M, Migasiewicz J (2016) Balance maintenance in the upright body position: analysis of autocorrelation. J Hum Kinet 50(1). doi:10.1515/hukin-2015-0140

    Google Scholar 

  • Stuster J (2006) Validation of the standardized field sobriety test battery at 0.08% blood alcohol concentration. Hum Factors 48(3):608–614

    Article  Google Scholar 

  • Sundermier L, Woollacott M, Roncesvalles N, Jensen J (2001) The development of balance control in children: comparisons of EMG and kinetic variables and chronological and developmental groupings. Exp Brain Res 136(3):340–350

    Article  Google Scholar 

  • Terrier P, Dériaz O (2011) Kinematic variability, fractal dynamics and local dynamic stability of treadmill walking. J Neuroeng Rehabil 8:12. doi:10.1186/1743-0003-8-12

    Article  Google Scholar 

  • Tinetti ME (1986) Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc 34(2):119–126. doi:10.1111/j.1532-5415.1986.tb05480.x

    Article  Google Scholar 

  • Toebes MJP, Hoozemans MJM, Furrer R, Dekker J, van Dieën JH (2012) Local dynamic stability and variability of gait are associated with fall history in elderly subjects. Gait Posture 36(3):527–531. doi:10.1016/j.gaitpost.2012.05.016

    Article  Google Scholar 

  • Trueblood PR, Hodson-Chennault N, McCubbin A, Youngclarke D (2001) Performance and impairment-based assessments among community-dwelling elderly: sensitivity and specificity. Issues Aging 24:2–6

    Google Scholar 

  • Tura A, Raggi M, Rocchi L, Cutti AG, Chiari L (2010) Gait symmetry and regularity in transfemoral amputees assessed by trunk accelerations. J Neuroeng Rehabil 7:4. doi:10.1186/1743-0003-7-4

    Article  Google Scholar 

  • van Emmerik REA, Ducharme SW, Amado AC, Hamill J (2016) Comparing dynamical systems concepts and techniques for biomechanical analysis. J Sport Health Sci 5(1):3–13. doi:10.1016/j.jshs.2016.01.013

    Article  Google Scholar 

  • van Meulen FB, Weenk D, Buurke JH, van Beijnum B-JF, Veltink PH (2016) Ambulatory assessment of walking balance after stroke using instrumented shoes. J Neuroeng Rehabil 13. doi:10.1186/s12984-016-0146-5

    Google Scholar 

  • Vereeck L, Wuyts F, Truijen S, de Heyning PV (2008) Clinical assessment of balance: normative data, and gender and age effects. Int J Audiol 47(2):67–75. doi:10.1080/14992020701689688

    Article  Google Scholar 

  • Vistamehr A, Kautz SA, Bowden MG, Neptune RR (2016) Correlations between measures of dynamic balance in individuals with post-stroke hemiparesis. J Biomech 49(3):396–400. doi:10.1016/j.jbiomech.2015.12.047

    Article  Google Scholar 

  • Whitney S, Wrisley D, Furman J (2003) Concurrent validity of the Berg Balance Scale and the Dynamic Gait Index in people with vestibular dysfunction. Physiother Res Int 8(4):178–186

    Article  Google Scholar 

  • Whitney JC, Lord SR, Close JCT (2005) Streamlining assessment and intervention in a falls clinic using the timed up and go test and physiological profile assessments. Age Ageing 34(6):567–571. doi:10.1093/ageing/afi178

    Article  Google Scholar 

  • Wrisley DM, Kumar NA (2010) Functional gait assessment: concurrent, discriminative, and predictive validity in community-dwelling older adults. Phys Ther 90(5):761–773. doi:10.2522/ptj.20090069

    Article  Google Scholar 

  • Wrisley DM, Walker ML, Echternach JL, Strasnick B (2003) Reliability of the Dynamic Gait Index in people with vestibular disorders. Arch Phys Med Rehabil 84(10):1528–1533. doi:10.1016/S0003-9993(03)00274-0

    Article  Google Scholar 

  • Yang C-C, Hsu Y-L, Shih K-S, Lu J-M (2011) Real-time gait cycle parameter recognition using a wearable accelerometry system. Sensors (Basel, Switzerland) 11(8):7314–7326. doi:10.3390/s110807314

    Article  Google Scholar 

  • Yeung LF, Cheng KC, Fong CH, Lee WCC, Tong K-Y (2014) Evaluation of the Microsoft Kinect as a clinical assessment tool of body sway. Gait Posture 40(4):532–538. doi:10.1016/j.gaitpost.2014.06.012

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Gait Laboratory, Nemours/AI duPont Hospital for Children, Wilmington, DE, USA

    Timothy A. Niiler

Authors
  1. Timothy A. Niiler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Timothy A. Niiler .

Editor information

Editors and Affiliations

  1. Motion & More, Barcelona, Spain

    Bertram Müller

  2. Klinik für Orthopädie und Unfallchirurgi, Universitätsklinikum Heidelberg, Heidelberg, Germany

    Sebastian I. Wolf

  3. Institut for Biomechanics und Orthopedic, German Sport University Cologne, Cologne, Germany

    Gert-Peter Brueggemann

  4. Houston, Texas, USA

    Zhigang Deng

  5. ACRISP, FedUniversity, Cremorne, New South Wales, Australia

    Andrew McIntosh

  6. Wilmington, Delaware, USA

    Freeman Miller

  7. Research, C-Motion, Inc., Germantown, Maryland, USA

    William Scott Selbie

Section Editor information

  1. Movement Analysis Laboratory, Clinic for Orthopedics and Trauma Surgery; Center for Orthopedics, Trauma Surgery and Spinal Cord Injury;Heidelberg University Hospital, Schlierbacher Landstr. 200a, 69118, Heidelberg, Germany

    Sebastian I. Wolf

  2. duPont Hospital for Children, Box 269, 19899, Wilmington, DE, USA

    Freeman Miller

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this entry

Cite this entry

Niiler, T.A. (2016). Measures to Determine Dynamic Balance. In: Müller, B., et al. Handbook of Human Motion. Springer, Cham. https://doi.org/10.1007/978-3-319-30808-1_44-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-30808-1_44-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Online ISBN: 978-3-319-30808-1

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation