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A wearable sensor identifies alterations in community ambulation in multiple sclerosis: contributors to real-world gait quality and physical activity

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Abstract

People with multiple sclerosis (pwMS) often suffer from gait impairments. These changes in gait have been well studied in laboratory and clinical settings. A thorough investigation of gait alterations during community ambulation and their contributing factors, however, is lacking. The aim of the present study was to evaluate community ambulation and physical activity in pwMS and healthy controls and to compare in-lab gait to community ambulation. To this end, 104 subjects were studied: 44 pwMS and 60 healthy controls (whose age was similar to the controls). The subjects wore a tri-axial, lower back accelerometer during usual-walking and dual-task walking in the lab and during community ambulation (1 week) to evaluate the amount, type, and quality of activity. The results showed that during community ambulation, pwMS took fewer steps and walked more slowly, with greater asymmetry, and larger stride-to-stride variability, compared to the healthy controls (p < 0.001). Gait speed during most of community ambulation was significantly lower than the in-lab usual-walking value and similar to the in-lab dual-tasking value. Significant group (pwMS /controls)-by-walking condition (in-lab/community ambulation) interactions were observed (e.g., gait speed). Greater disability was associated with fewer steps and reduced gait speed during community ambulation. In contrast, physical fatigue was correlated with sedentary activity, but was not related to any of the measures of community ambulation gait quality including gait speed. This disparity suggests that more than one mechanism contributes to community ambulation and physical activity in pwMS. Together, these findings demonstrate that during community ambulation, pwMS have marked gait alterations in multiple gait features, reminiscent of dual-task walking measured in the laboratory. Disease-related factors associated with these changes might be targets of rehabilitation.

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References

  1. Comber L, Galvin R, Coote S (2017) Gait deficits in people with multiple sclerosis: a systematic review and meta-analysis. Gait Posture 51:25–35

    PubMed  Google Scholar 

  2. Heesen C, Bohm J, Reich C, Kasper J, Goebel M, Gold SM (2008) Patient perception of bodily functions in multiple sclerosis: gait and visual function are the most valuable. Mult Scler 14:988–991

    CAS  PubMed  Google Scholar 

  3. Larocca NG (2011) Impact of walking impairment in multiple sclerosis: perspectives of patients and care partners. Patient 4:189–201

    PubMed  Google Scholar 

  4. Matsuda PN, Shumway-Cook A, Ciol MA, Bombardier CH, Kartin DA (2012) Understanding falls in multiple sclerosis: association of mobility status, concerns about falling, and accumulated impairments. Phys Ther 92:407–415

    PubMed  Google Scholar 

  5. Motl RW, Cohen JA, Benedict R, Phillips G, LaRocca N, Hudson LD, Rudick R (2017) Validity of the timed 25-foot walk as an ambulatory performance outcome measure for multiple sclerosis. Mult Scler 23:704–710

    PubMed  PubMed Central  Google Scholar 

  6. Bethoux F (2013) Gait disorders in multiple sclerosis. Continuum (Minneap Minn) 19:1007–1022

    Google Scholar 

  7. Hobart JC, Riazi A, Lamping DL, Fitzpatrick R, Thompson AJ (2003) Measuring the impact of MS on walking ability: the 12-Item MS Walking Scale (MSWS-12). Neurology 60:31–36

    CAS  PubMed  Google Scholar 

  8. Socie MJ, Sosnoff JJ (2013) Gait variability and multiple sclerosis. Mult Scler Int 2013:645197

    PubMed  PubMed Central  Google Scholar 

  9. Allali G, Laidet M, Herrmann FR, Armand S, Elsworth-Edelsten C, Assal F, Lalive PH (2016) Gait variability in multiple sclerosis: a better falls predictor than EDSS in patients with low disability. J Neural Transm (Vienna) 123:447–450

    Google Scholar 

  10. Kalron A (2017) Association between gait variability, falls and mobility in people with multiple sclerosis: a specific observation on the EDSS 4.0-4.5 level. NeuroRehabilitation 40:579–585

    PubMed  Google Scholar 

  11. Del DS, Godfrey A, Mazza C, Lord S, Rochester L (2016) Free-living monitoring of Parkinson's disease: lessons from the field. Mov Disord 31:1293–1313

    Google Scholar 

  12. Hillel I, Gazit E, Nieuwboer A, Avanzino L, Rochester L, Cereatti A, Croce UD, Rikkert MO, Bloem BR, Pelosin E, Del DS, Ginis P, Giladi N, Mirelman A, Hausdorff JM (2019) Is every-day walking in older adults more analogous to dual-task walking or to usual walking? Elucidating the gaps between gait performance in the lab and during 24/7 monitoring. Eur Rev Aging Phys Act 16:6

    PubMed  PubMed Central  Google Scholar 

  13. Galperin I, Hillel I, Del DS, Bekkers EMJ, Nieuwboer A, Abbruzzese G, Avanzino L, Nieuwhof F, Bloem BR, Rochester L, Della CU, Cereatti A, Giladi N, Mirelman A, Hausdorff JM (2019) Associations between daily-living physical activity and laboratory-based assessments of motor severity in patients with falls and Parkinson's disease. Parkinsonism Relat Disord 62:85–90

    PubMed  Google Scholar 

  14. Motl RW, Pilutti L, Sandroff BM, Dlugonski D, Sosnoff JJ, Pula JH (2013) Accelerometry as a measure of walking behavior in multiple sclerosis. Acta Neurol Scand 127:384–390

    CAS  PubMed  Google Scholar 

  15. Frechette ML, Meyer BM, Tulipani LJ, Gurchiek RD, McGinnis RS, Sosnoff JJ (2019) Next steps in wearable technology and community ambulation in multiple sclerosis. Curr Neurol Neurosci Rep 19:80

    PubMed  Google Scholar 

  16. Casey B, Coote S, Galvin R, Donnelly A (2018) Objective physical activity levels in people with multiple sclerosis: meta-analysis. Scand J Med Sci Sports 28:1960–1969

    CAS  PubMed  Google Scholar 

  17. Stellmann JP, Neuhaus A, Gotze N, Briken S, Lederer C, Schimpl M, Heesen C, Daumer M (2015) Ecological validity of walking capacity tests in multiple sclerosis. PLoS ONE 10:e0123822

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Storm FA, Nair KPS, Clarke AJ, Van der Meulen JM, Mazza C (2018) Free-living and laboratory gait characteristics in patients with multiple sclerosis. PLoS ONE 13:e0196463

    PubMed  PubMed Central  Google Scholar 

  19. Block VJ, Bove R, Zhao C, Garcha P, Graves J, Romeo AR, Green AJ, Allen DD, Hollenbach JA, Olgin JE, Marcus GM, Pletcher MJ, Cree BAC, Gelfand JM (2019) Association of continuous assessment of step count by remote monitoring with disability progression among adults with multiple sclerosis. JAMA Netw Open 2:e190570

    PubMed  PubMed Central  Google Scholar 

  20. Neven A, Vanderstraeten A, Janssens D, Wets G, Feys P (2016) Understanding walking activity in multiple sclerosis: step count, walking intensity and uninterrupted walking activity duration related to degree of disability. Neurol Sci 37:1483–1490

    PubMed  Google Scholar 

  21. Motl RW (2013) Ambulation and multiple sclerosis. Phys Med Rehabil Clin N Am 24:325–336

    PubMed  Google Scholar 

  22. Postigo-Alonso B, Galvao-Carmona A, Benitez I, Conde-Gavilan C, Jover A, Molina S, Pena-Toledo MA, Aguera E (2018) Cognitive-motor interference during gait in patients with multiple sclerosis: a mixed methods systematic review. Neurosci Biobehav Rev 94:126–148

    CAS  PubMed  Google Scholar 

  23. Postigo-Alonso B, Galvao-Carmona A, Conde-Gavilan C, Jover A, Molina S, Pena-Toledo MA, Valverde-Moyano R, Aguera E (2019) The effect of prioritization over cognitive-motor interference in people with relapsing-remitting multiple sclerosis and healthy controls. PLoS ONE 14:e0226775

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Motl RW, Sosnoff JJ, Dlugonski D, Pilutti LA, Klaren R, Sandroff BM (2014) Walking and cognition, but not symptoms, correlate with dual task cost of walking in multiple sclerosis. Gait Posture 39:870–874

    PubMed  Google Scholar 

  25. Sosnoff JJ, Boes MK, Sandroff BM, Socie MJ, Pula JH, Motl RW (2011) Walking and thinking in persons with multiple sclerosis who vary in disability. Arch Phys Med Rehabil 92:2028–2033

    PubMed  Google Scholar 

  26. Wajda DA, Motl RW, Sosnoff JJ (2013) Dual task cost of walking is related to fall risk in persons with multiple sclerosis. J Neurol Sci 335:160–163

    PubMed  Google Scholar 

  27. Srygley JM, Mirelman A, Herman T, Giladi N, Hausdorff JM (2009) When does walking alter thinking? Age and task associated findings. Brain Res 1253:92–99

    CAS  PubMed  Google Scholar 

  28. Hausdorff JM, Schweiger A, Herman T, Yogev-Seligmann G, Giladi N (2008) Dual-task decrements in gait: contributing factors among healthy older adults. J Gerontol A Biol Sci Med Sci 63:1335–1343

    PubMed  PubMed Central  Google Scholar 

  29. Shema-Shiratzky S, Gazit E, Sun R, Regev K, Karni A, Sosnoff JJ, Herman T, Mirelman A, Hausdorff JM (2019) Deterioration of specific aspects of gait during the instrumented 6-min walk test among people with multiple sclerosis. J Neurol 266:3022–3030

    CAS  PubMed  Google Scholar 

  30. Benedict RH, DeLuca J, Phillips G, LaRocca N, Hudson LD, Rudick R (2017) Validity of the symbol digit modalities test as a cognition performance outcome measure for multiple sclerosis. Mult Scler 23:721–733

    PubMed  PubMed Central  Google Scholar 

  31. Kos D, Kerckhofs E, Carrea I, Verza R, Ramos M, Jansa J (2005) Evaluation of the modified fatigue impact scale in four different European countries. Mult Scler 11:76–80

    CAS  PubMed  Google Scholar 

  32. Weiss A, Herman T, Giladi N, Hausdorff JM (2014) Objective assessment of fall risk in Parkinson's disease using a body-fixed sensor worn for 3 days. PLoS ONE 9:e96675

    PubMed  PubMed Central  Google Scholar 

  33. Feys J (2016) New nonparametric rank tests for interactions in factorial designs with repeated measures. J Mod Appl Statist Meth 15:6

    Google Scholar 

  34. Shah DA, Madden LV (2004) Nonparametric analysis of ordinal data in designed factorial experiments. Phytopathology 94:33–43

    CAS  PubMed  Google Scholar 

  35. Wajda DA, Mirelman A, Hausdorff JM, Sosnoff JJ (2017) Intervention modalities for targeting cognitive-motor interference in individuals with neurodegenerative disease: a systematic review. Expert Rev Neurother 17:251–261

    CAS  PubMed  Google Scholar 

  36. Klaren RE, Motl RW, Dlugonski D, Sandroff BM, Pilutti LA (2013) Objectively quantified physical activity in persons with multiple sclerosis. Arch Phys Med Rehabil 94:2342–2348

    PubMed  Google Scholar 

  37. Sparaco M, Lavorgna L, Conforti R, Tedeschi G, Bonavita S (2018) The role of wearable devices in multiple sclerosis. Mult Scler Int 2018:7627643

    PubMed  PubMed Central  Google Scholar 

  38. Ihlen EAF, Weiss A, Bourke A, Helbostad JL, Hausdorff JM (2016) The complexity of daily life walking in older adult community-dwelling fallers and non-fallers. J Biomech 49:1420–1428

    PubMed  Google Scholar 

  39. van Emmerik REA, Ducharme SW, Amado AC, Hamill J (2016) Comparing dynamical systems concepts and techniques for biomechanical analysis. J Sport Health Sci 5:3–13

    PubMed  PubMed Central  Google Scholar 

  40. Cavanaugh JT, Kochi N, Stergiou N (2010) Nonlinear analysis of ambulatory activity patterns in community-dwelling older adults. J Gerontol A Biol Sci Med Sci 65:197–203

    PubMed  Google Scholar 

  41. Block VA, Pitsch E, Tahir P, Cree BA, Allen DD, Gelfand JM (2016) Remote physical activity monitoring in neurological disease: a systematic review. PLoS ONE 11:e0154335

    PubMed  PubMed Central  Google Scholar 

  42. Morrison JD, Mayer L (2017) Physical activity and cognitive function in adults with multiple sclerosis: an integrative review. Disabil Rehabil 39:1909–1920

    PubMed  Google Scholar 

  43. Motl RW, Gappmaier E, Nelson K, Benedict RH (2011) Physical activity and cognitive function in multiple sclerosis. J Sport Exerc Psychol 33:734–741

    PubMed  Google Scholar 

  44. Blikman LJM, van Meeteren J, Rizopoulos D, de Groot V, Beckerman H, Stam HJ, Bussmann JBJ (2018) Physical behaviour is weakly associated with physical fatigue in persons with multiple sclerosis-related fatigue. J Rehabil Med 50:821–827

    PubMed  Google Scholar 

  45. Rietberg MB, van Wegen EE, Uitdehaag BM, Kwakkel G (2011) The association between perceived fatigue and actual level of physical activity in multiple sclerosis. Mult Scler 17:1231–1237

    PubMed  Google Scholar 

  46. Plummer P, Eskes G (2015) Measuring treatment effects on dual-task performance: a framework for research and clinical practice. Front Hum Neurosci 9:225

    PubMed  PubMed Central  Google Scholar 

  47. 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 90:177–186

    PubMed  PubMed Central  Google Scholar 

  48. Yogev-Seligmann G, Hausdorff JM, Giladi N (2012) Do we always prioritize balance when walking? Towards an integrated model of task prioritization. Mov Disord 27:765–770

    PubMed  Google Scholar 

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Acknowledgements

This work was supported in part by a grant from the National Multiple Sclerosis Society (RG-1507-05433). AM and JMH have received funding from Mobilise-D from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 820820. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. All authors declare no conflict of interests. We thank the study participants and staff for their time and contribution to this research and Dr. Sa Shen for invaluable statistical assistance.

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Authors and Affiliations

  1. Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, 6 Weizmann St., 6423906, Tel Aviv, Israel

    Shirley Shema-Shiratzky, Inbar Hillel, Anat Mirelman & Jeffrey M. Hausdorff

  2. Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel

    Anat Mirelman & Arnon Karni

  3. Department of Neurology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel

    Anat Mirelman, Arnon Karni & Jeffrey M. Hausdorff

  4. Neuroimmunology and Multiple Sclerosis Unit of the Neurology Division, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel

    Keren Regev & Arnon Karni

  5. Motor Control Research Laboratory, Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Katherine L. Hsieh & Jacob J. Sosnoff

  6. Laboratory for Advanced Rehabilitation Research in Simulation, Department of Physical Therapy and Rehabilitation Science, School of Health Professions, University of Kansas Medical Center, Kansas City, KS, USA

    Hannes Devos

  7. Department of Physical Therapy, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel

    Jeffrey M. Hausdorff

  8. Rush Alzheimer’s Disease Center and Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA

    Jeffrey M. Hausdorff

Authors
  1. Shirley Shema-Shiratzky
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  2. Inbar Hillel
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  3. Anat Mirelman
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  5. Katherine L. Hsieh
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  6. Arnon Karni
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  7. Hannes Devos
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  8. Jacob J. Sosnoff
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  9. Jeffrey M. Hausdorff
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Corresponding author

Correspondence to Jeffrey M. Hausdorff.

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Ethical standards

Study protocols were approved by the local ethical review boards and have, therefore, been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

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All participants provided written informed consent prior to participation.

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Shema-Shiratzky, S., Hillel, I., Mirelman, A. et al. A wearable sensor identifies alterations in community ambulation in multiple sclerosis: contributors to real-world gait quality and physical activity. J Neurol 267, 1912–1921 (2020). https://doi.org/10.1007/s00415-020-09759-7

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  • DOI: https://doi.org/10.1007/s00415-020-09759-7

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