Experimental Brain Research

, Volume 237, Issue 2, pp 477–491 | Cite as

Biomechanical and neurocognitive performance outcomes of walking with transtibial limb loss while challenged by a concurrent task

  • Alison L. PruzinerEmail author
  • Emma P. Shaw
  • Jeremy C. Rietschel
  • Brad D. Hendershot
  • Matthew W. Miller
  • Erik J. Wolf
  • Bradley D. Hatfield
  • Christopher L. Dearth
  • Rodolphe J. Gentili
Research Article


Individuals who have sustained loss of a lower limb may require adaptations in sensorimotor and control systems to effectively utilize a prosthesis, and the interaction of these systems during walking is not clearly understood for this patient population. The aim of this study was to concurrently evaluate temporospatial gait mechanics and cortical dynamics in a population with and without unilateral transtibial limb loss (TT). Utilizing motion capture and electroencephalography, these outcomes were simultaneously collected while participants with and without TT completed a concurrent task of varying difficulty (low- and high-demand) while seated and walking. All participants demonstrated a wider base of support and more stable gait pattern when walking and completing the high-demand concurrent task. The cortical dynamics were similarly modulated by the task demand for both groups, to include a decrease in the novelty-P3 component and increase in the frontal theta/parietal alpha ratio power when completing the high-demand task, although specific differences were also observed. These findings confirm and extend prior efforts indicating that dual-task walking can negatively affect walking mechanics and/or neurocognitive performance. However, there may be limited additional cognitive and/or biomechanical impact of utilizing a prosthesis in a stable, protected environment in TT who have acclimated to ambulating with a prosthesis. These results highlight the need for future work to evaluate interactions between these cognitive–motor control systems for individuals with more proximal levels of lower limb loss, and in more challenging (ecologically valid) environments.


Limb loss Cognitive workload Biomechanics Electroencephalogram Dual-task walking 



Analysis of variance


Computer-Assisted Rehabilitation ENvironment




Event-related potentials


Frontal theta/parietal alpha ratio


National Aeronautics and Space Administration-Task Load Index


Transtibial limb loss



The authors wish to thank Ms. Vanessa Gatmaitan, MS and Ms. Elizabeth Husson, BA, at Walter Reed National Military Medical Center, and Drs. Kyle Jaquess, Ph.D. and Li-Chuan Lo, Ph.D., at the University of Maryland, for their assistance with data collection and processing. This work was supported by the Center for Rehabilitation Science Research, Department of Rehabilitation Medicine, Uniformed Services University, Bethesda, MD, (awards HU0001-11-1-0004 and HU0001-15-2-0003) and supported by the Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., and the DoD-VA Extremity Trauma and Amputation Center of Excellence (Public Law 110-417, National Defense Authorization Act 2009, Section 723). Pruziner and Wolf contributed to overall study design, data collection and interpretation, and manuscript development; Gentili, Hatfield, Miller, and Rietschel contributed to overall study design, data interpretation, and manuscript development; Hendershot and Shaw contributed to data collection and interpretation, and manuscript development; Dearth contributed to data interpretation and manuscript development.

Compliance with ethical standards

Conflict of interest

The authors declare no competing financial interests. The views expressed in this article are those of the authors and do not reflect the official policy of the Department of Army/Navy/Air Force, Department of Defense, or U.S. Government. The identification of specific products or instrumentation is considered an integral part of the scientific endeavor and does not constitute endorsement or implied endorsement on the part of the authors, Department of Defense, or any component agency.

Supplementary material

221_2018_5419_MOESM1_ESM.docx (30 kb)
Supplementary material 1 (DOCX 30 KB)


  1. Alderman BL, Olson RL, Bates ME, Selby EA, Buckman JF, Brush CJ, Panza EA, Kranzler A, Eddie D, Shors TJ (2015) Rumination in major depressive disorder is associated with impaired neural activation during conflict monitoring. Front Hum Neurosci 9:296Google Scholar
  2. Bauer L, Goldstein R, Stern J (1987) Effects of information processing demands on physiological response patterns. Hum Factors 29:213–234Google Scholar
  3. Beauchet O, Dubost V, Herrmann FR, Kressig RW (2005) Stride-to-stride variability while backward counting among healthy young adults. J Neuroeng Rehabil 2(1):26Google Scholar
  4. Beauchet O, Allali G, Annweiler C, Bridenbaugh S, Assal F, Kressig RW, Herrmann FR (2009) Gait variability among healthy adults: low and high stride-to-stride variability are both a reflection of gait stability. Gerontology 55(6):702–706Google Scholar
  5. Beurskens R, Steinberg F, Antoniewicz F, Wolff W, Granacher U (2016) Neural correlates of dual-task walking: effects of cognitive versus motor interference in young adults. Neural Plasticity 2016:9Google Scholar
  6. Brach JS, Berlin JE, VanSwearingen JM, Newman AB, Studenski SA (2005) Too much or too little step width variability is associated with a fall history in older persons who walk at or near normal gait speed. J Neuroeng Rehabil 2(1):21Google Scholar
  7. Brouwer AM, Hogervorst MA, Van Erp JB, Heffelaar T, Zimmerman PH, Oostenveld R (2012) Estimating workload using EEG spectral power and ERPs in the n-back task. J Neural Eng 9(4):045008Google Scholar
  8. Cavanagh JF, Cohen MX, Allen JJB (2009) Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring. J Neurosci 29:98–105Google Scholar
  9. Cheng MY, Hung CL, Huang CJ, Chang YK, Lo LC, Shen C, Hung TM (2015) Expert-novice differences in SMR activity during dart throwing. Biol Psychol 110:212–218Google Scholar
  10. Cohen J, Polich J (1997) On the number of trials needed for P300. Int J Psychophysiol 25:249–255Google Scholar
  11. Coombes SA, Janelle CM, Duley AR, Conway T (2005) Adults with dyslexia: theta power changes during performance of a sequential motor task. Int J Psychophysiol 56:1–14Google Scholar
  12. De Sanctis P, Butler JS, Malcolm BR, Foxe JJ (2014) Recalibration of inhibitory control systems during walking-related dual-task interference: a mobile brain-body imaging (MOBI) study. NeuroImage 94:55–64Google Scholar
  13. Deeny S, Chicoine C, Hargrove L, Parrish T, Jayaraman A (2014) A simple ERP method for quantitative analysis of cognitive workload in myoelectric prosthesis control and human-machine interaction. PLoS One 9(11):e112091Google Scholar
  14. Dubost V, Kressig RW, Gonthier R, Herrmann FR, Aminian K, Najafi B, Beauchet O (2006) Relationships between dual-task related changes in stride velocity and stride time variability in healthy older adults. Hum Mov Sci 25(3):372–382Google Scholar
  15. Dyke FB, Leiker AM, Grand KF, Godwin MM, Thompson AG, Rietschel JC, McDonald CG, Miller MW (2015) The efficacy of auditory probes in indexing cognitive workload is dependent on stimulus complexity. Int J Psychophysiol 95(1):56–62Google Scholar
  16. Fabiani M, Kazmerski VA, Cycowicz YM, Friedman D (1996) Naming norms for brief environmental sounds: effects of age and dementia. Psychophysiology 33:462–475Google Scholar
  17. Fraizer EV, Mitra S (2008) Methodological and interpretive issues in posture-cognition dual-tasking in upright stance. Gait Posture 27(2):271–279Google Scholar
  18. Gates DH, Darter BJ, Dingwell JB, Wilken JM (2012) Comparison of walking overground and in a Computer Assisted Rehabilitation Environment (CAREN) in individuals with and without transtibial amputation. J Neuroeng Rehabil 9:81Google Scholar
  19. Gentili RJ, Bradberry TJ, Oh H, Hatfield BD, Contreras Vidal JL (2011) Cerebral cortical dynamics during visuomotor transformation: adaptation to a cognitive-motor executive challenge. Psychophysiology 48(6):813–824Google Scholar
  20. Gentili RJ, Rietschel JC, Jaquess KJ, Lo LC, Prevost CM, Miller MW, Mohler JM, Oh H, Tan YY, Hatfield BD (2014) Brain biomarkers based assessment of cognitive workload in pilots under various task demands. In: 36th IEEE international conference of the engineering in medicine and biology society, pp 5860–5863Google Scholar
  21. Gentili RJ, Jaquess KJ, Shuggi IM, Shaw EP, Oh H, Lo L-C, Tan YY, Domingues CA, Blanco JA, Rietschel JC, Miller MW, Hatfield BD (2018) Combined assessment of attentional reserve and cognitive-motor effort under various levels of challenge with a dry EEG system. Psychophysiology (in press) Google Scholar
  22. Gevins A, Smith ME (2000) Neurophysiological measures of working memory and individual differences in cognitive ability and cognitive style. Cereb Cortex 10(9):829–839Google Scholar
  23. Gevins A, Smith ME (2003) Neurophysiological measures of cognitive workload during human-computer interaction. Theor Issues Ergon Sci 4(1–2):113–131Google Scholar
  24. Grabiner MD, Troy KL (2005) Attention demanding tasks during treadmill walking reduce step width variability in young adults. J Neuroeng Rehabil 2(1):25Google Scholar
  25. Hak L, van Dieen JH, van der Wurff P, Maarten RP, Mert A, Beek PJ, Houdijk H (2013) Walking in an unstable environment: strategies used by transtibial amputees to prevent falling during gait. Arch Phys Med Rehabil 94(11):2186–2193Google Scholar
  26. Hart SG (2006) NASA-task load index (NASA-TLX); 20 years later. In Proceedings of the human factors and ergonomics society 50th annual meeting, pp 904–908Google Scholar
  27. Hart SG, Staveland LE (1988) Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. Adv Psychol 52:139–183Google Scholar
  28. Hausdorff JM (2005) Gait variability: methods, modeling and meaning. J Neuroeng Rehabil 2(1):19Google Scholar
  29. 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):250–258Google Scholar
  30. Hollman JH, Kovash FM, Kubik JJ, Linbo RA (2007) Age-related differences in spatiotemporal markers of gait stability during dual task walking. Gait Posture 26(1):113–119Google Scholar
  31. Holm A, Lukander K, Korpela J, Sallinen M, Müller KMI (2009) Estimating brain load from the EEG. Sci World J 9:639–651Google Scholar
  32. Howard CL, Perry B, Chow JW, Wallace C, Stokic D (2017) Increased alertness, better than posture prioritization, explains dual-task performance in prosthesis users and controls under increasing postural and cognitive challenge. Exp Brain Res 235(11):3527–3539Google Scholar
  33. Huang CY, Zhao CG, Hwang IS (2014) Neural basis of postural focus effect on concurrent postural and motor tasks: phase-locked electroencephalogram responses. Behav Brain Res 274:95–107Google Scholar
  34. Jaiswal N, Ray W, Slobounov S (2010) Encoding of visual-spatial information in working memory requires more cerebral efforts than retrieval: evidence from EEG and virtual reality study. Brain Res 1347:80–89Google Scholar
  35. Jaquess KJ, Gentili RJ, Lo LC, Oh H, Zhang J, Rietschel JC, Miller MW, Tan YY, Hatfield BD (2017) Empirical evidence for the relationship between cognitive workload and attentional reserve. Int J Psychophysiol 121:46–55Google Scholar
  36. Jarvis HL, Bennett AN, Twiste M, Phillip RD, Etherington J, Baker R (2017) Temporal spatial and metabolic measures of walking in highly functional individuals with lower limb amputations. Arch Phys Med Rehabil 98(7):1389–1399Google Scholar
  37. Kelly VE, Eusterbrock AJ, Shumway-Cook A (2013) Factors influencing dynamic prioritization during dual-task walking in healthy young adults. Gait Posture 37(1):131–134Google Scholar
  38. Lamoth CJ, Ainsworth E, Polomski W, Houdijk H (2010) Variability and stability analysis of walking of transfemoral amputees. Med Eng Phys 32(9):1009–1014Google Scholar
  39. Little CE, Woollacott M (2015) EEG measures reveal dual-task interference in postural performance in young adults. Exp Brain Res 233(1):27–37Google Scholar
  40. Lord S, Howe T, Greenland J, Simpson L, Rochester L (2011) Gait variability in older adults: a structured review of testing protocol and clinimetric properties. Gait Posture 34(4):443–450Google Scholar
  41. Maki BE (1997) Gait changes in older adults: predictors of falls or indicators of fear? J Am Geriatr Soc 45(3):313–320Google Scholar
  42. Miller MW, Rietschel JC, McDonald CG, Hatfield BD (2011) A novel approach to the physiological measurement of mental workload. Int J Psychophysiol 80(1):75–78Google Scholar
  43. Miller MW, Presacco A, Groman LJ, Bur S, Rietschel JC, Gentili RJ, McDonald CG, Iso-Ahola SE, Hatfield BD (2014) The effects of team environment on cerebral cortical processes and attentional reserve. Sport Exerc Perform Psychol 3(1):61–74Google Scholar
  44. Mirelman A, Maidan I, Bernad-Elazari H, Nieuwhof F, Reelick M, Giladi N, Hausdorff JM (2014) Increased frontal brain activation during walking while dual tasking: an fNIRS study in healthy young adults. J Neuroeng Rehabil 11:85Google Scholar
  45. Morgan SJ, Hafner BJ, Kelly VE (2016) The effects of a concurrent task on walking in persons with transfemoral amputation compared to persons without limb loss. Prosthet Orthot Int 40(4):490–496Google Scholar
  46. Morgan SJ, Hafner BJ, Kelly VE (2017) Dual-task walking over a compliant foam surface: a comparison of people with transfemoral amputation and controls. Gait Posture 58:41–45Google Scholar
  47. Murray NP, Janelle CM (2007) Event-related potential evidence for the processing efficiency theory. J Sports Sci 25(2):161–171Google Scholar
  48. Ochoa J, Sternad D, Hogan N (2017) Treadmill vs. overground walking: different response to physical interaction. J Neurophysiol 118(4):2089–2102Google Scholar
  49. Oliveira AS, Gizzi L, Ketabi S, Farina D, Kersting UG (2016) Modular control of treadmill vs overground running. PLoS One 11(4):e0153307Google Scholar
  50. Olson RL, Chang YK, Brush CJ, Kwok AN, Gordon VX, Alderman BL (2016) Neurophysiological and behavioral correlates of cognitive control during low and moderate intensity exercise. NeuroImage 131(1):171–180Google Scholar
  51. Onton J, Delorm A, Makeig S (2005) Frontal midline EEG dynamics during working memory. NeuroImage 27:341–356Google Scholar
  52. Onton J, Westerfield M, Townsend J, Makeig S (2006) Imaging human EEG dynamics using independent component analysis. Neurosci Biobehav Rev 30:808–822Google Scholar
  53. Plummer-D’Amato P, Altmann LJ, Behrman AL, Marsiske M (2010) Interference between cognition, double-limb support, and swing during gait in community-dwelling individuals poststroke. Neurorehabil Neural Repair 24(6):542–549Google Scholar
  54. Rietschel JC, Miller MW, Gentili RJ, Goodman RN, McDonald CG, Hatfield BD (2012) Cerebral-cortical networking and activation increase as a function of cognitive-motor task difficulty. Biol Psychol 90(2):127–133Google Scholar
  55. Rietschel JC, McDonald CG, Goodman RN, Miller MW, Jones-Lush LM, Wittenberg GF, Hatfield BD (2014) Psychophysiological support of increasing attentional reserve during the development of a motor skill. Biol Psychol 103:349–356Google Scholar
  56. Riley PO, Paolini G, Della Croce U, Paylo KW, Kerrigan DC (2007) A kinematic and kinetic comparison of overground and treadmill walking in healthy subjects. Gait Posture 26(1):17–24Google Scholar
  57. SanMiguel I, Corral MJ, Escera C (2008) When loading working memory reduces distraction: behavioral and electrophysiological evidence from an auditory-visual distraction paradigm. J Cogn Neurosci 20(7):1131–1145Google Scholar
  58. Shaw EP, Rietschel JC, Hendershot BD, Pruziner AL, Miller MW, Hatfield BD, Gentili RJ (2018) Measurement of attentional reserve and mental effort for cognitive workload assessment under various task demands during dual-task walking. Biol Psychol 134:39–51Google Scholar
  59. Shuggi IM, Shewokis PA, Herrmann JW, Gentili RJ (2017) Changes in motor performance and mental workload during practice of reaching movements: a team dynamics perspective. Exp Brain Res 236(2):433–451Google Scholar
  60. Shuggi IM, Oh H, Shewokis PA, Gentili RJ (2018) Mental workload and motor performance dynamics during practice of reaching movements under various levels of task difficulty. Neuroscience 360:166–179Google Scholar
  61. Slobounov SM, Teel L, Newell KM (2013) Modulation of cortical activity in response to visually induced postural perturbation: combined VR and EEG study. Neurosci Lett 547:6–9Google Scholar
  62. Slobounov SM, Ray W, Johnson B, Slobounov E, Newell KM (2015) Modulation of cortical activity in 2D versus 3D virtual reality environments: an EEG study. Int J Psychophysiol 95(3):254–260Google Scholar
  63. Sloot LH, Van der Krogt MM, Harlaar J (2014) Effects of adding a virtual reality environment to different modes of treadmill walking. Gait Posture 39(3):939–945Google Scholar
  64. Smith ME, McEvoy LK, Gevins A (1999) Neurophysiological indices of strategy development and skill acquisition. Brain Res Cogn Brain Res 7(3):389–404Google Scholar
  65. Yang F, King GA (2016) Dynamic gait stability of treadmill versus overground walking in young adults. J Electromyogr Kinesiol 31:81–87Google Scholar
  66. Yogev-Seligmann G, Rotem-Galili Y, Mirelman A, Dickstein R, Giladi N, Hausdorff JM (2010) How does explicit prioritization alter walking during dual-task performance? Effects of age and sex on gait speed and variability. Phys Ther 90(2):177–186Google Scholar
  67. Zhang W, White M, Zahabi M, Winslow AT, Zhang F, Huang H, Kaber D (2016) Cognitive workload in conventional direct control vs. pattern recognition control of an upper-limb prosthesis. In: 2016 IEEE international conference on systems, man, and cybernetics, SMC 2016, October 9–12, BudapestGoogle Scholar

Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2018

Authors and Affiliations

  • Alison L. Pruziner
    • 1
    • 2
    • 3
    Email author
  • Emma P. Shaw
    • 2
    • 4
    • 5
  • Jeremy C. Rietschel
    • 4
    • 6
  • Brad D. Hendershot
    • 1
    • 2
    • 3
  • Matthew W. Miller
    • 7
  • Erik J. Wolf
    • 1
    • 2
    • 3
  • Bradley D. Hatfield
    • 4
    • 5
  • Christopher L. Dearth
    • 1
    • 2
    • 3
    • 8
  • Rodolphe J. Gentili
    • 4
    • 5
    • 9
  1. 1.DoD-VA Extremity Trauma and Amputation Center of ExcellenceBethesdaUSA
  2. 2.Department of RehabilitationWalter Reed National Military Medical CenterBethesdaUSA
  3. 3.Department of Rehabilitation MedicineUniformed Services University of the Health SciencesBethesdaUSA
  4. 4.Department of Kinesiology, School of Public HealthUniversity of MarylandCollege ParkUSA
  5. 5.Neuroscience and Cognitive Science ProgramUniversity of MarylandCollege ParkUSA
  6. 6.Baltimore Veterans Administration Medical CenterBaltimoreUSA
  7. 7.Center for Neuroscience, School of KinesiologyAuburn UniversityAuburnUSA
  8. 8.Department of SurgeryUniformed Services University of the Health SciencesBethesdaUSA
  9. 9.Maryland Robotics CenterUniversity of MarylandCollege ParkUSA

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