Asymmetry and Variability Should Be Included in the Assessment of Gait Function in Poststroke Hemiplegia With Independent Ambulation During Early Rehabilitation

Published:November 05, 2020DOI:


      • There is multicollinearity among spatiotemporal metrics of poststroke gait.
      • Principal component analysis reduced the spatiotemporal gait metrics to 3 independent components.
      • Three components are related to speed: phase, asymmetry, and variability.
      • Temporal asymmetry and variability should be assessed in poststroke gait.



      To extract independent features from spatiotemporal data of poststroke gait.


      Retrospective observational study.


      Motion analysis laboratory in the rehabilitation department of a university hospital.


      Convenience sample from inpatients in subacute recovery stage post stroke. Of 98 patients post stroke who underwent gait assessment, 69 patients post stroke were included in the data analysis (N=69). They could walk more than 10 m without personal assist or assistive devices.


      Not applicable.

      Main Outcome Measures

      Spatiotemporal parameters during level walking and their asymmetry and variability were obtained by insole foot pressure measurement system.


      Of independent components extracted by principal component analysis, 3 independent components explained 81.9% of total variance of spatiotemporal poststroke gait data. The first component has associations with walking speed and proportion of double support phase, and it explains 46.6% of total variance. The second component has association with temporal asymmetry, and it explains 21.1% of total variance. The third component has association with temporal variability, and it explains 14.2% of total variance. Principal component scores did not show significant differences between stroke types and among stroke lesions.


      Temporal asymmetry and variability should be included in the assessment of poststroke gait during early rehabilitation. They are independent of each other and provide characteristics of poststroke gait that are independent to the walking speed. They are helpful for rehabilitation planning and developing treatment strategy in poststroke gait rehabilitation.


      List of Abbreviations:

      BBS (Berg Balance Scale), MBI (Modified Barthel Index), MMSE (Mini-Mental State Examination), PC (principal component), PCA (principal component analysis), RSD (relative standard abbreviation), SI (symmetry index)
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        • Eng J.J.
        • Tang P.F.
        Gait training strategies to optimize walking ability in people with stroke: a synthesis of the evidence.
        Expert Rev Neurother. 2007; 7: 1417-1436
        • Ada L.
        • Dean C.M.
        • Lindley R.
        • Lloyd G.
        Improving community ambulation after stroke: the AMBULATE Trial.
        BMC Neurol. 2009; 9: 8
        • Langhorne P.
        • Bernhardt J.
        • Kwakkel G.
        Stroke rehabilitation.
        Lancet. 2011; 377: 1693-1702
        • Balaban B.
        • Tok F.
        Gait disturbances in patients with stroke.
        PM R. 2014; 6: 635-642
        • Herssens N.
        • Verbecque E.
        • Hallemans A.
        • Vereeck L.
        • Van Rompaey V.
        • Saeys W.
        Do spatiotemporal parameters and gait variability differ across the lifespan of healthy adults? A systematic review.
        Gait Posture. 2018; 64: 181-190
        • Goldie P.A.
        • Matyas T.A.
        • Evans O.M.
        Deficit and change in gait velocity during rehabilitation after stroke.
        Arch Phys Med Rehabil. 1996; 77: 1074-1082
        • Goldie P.A.
        • Matyas T.A.
        • Evans O.M.
        Gait after stroke: initial deficit and changes in temporal patterns for each gait phase.
        Arch Phys Med Rehabil. 2001; 82: 1057-1065
        • Dickstein R.
        Rehabilitation of gait speed after stroke: a critical review of intervention approaches.
        Neurorehabil Neural Repair. 2008; 22: 649-660
        • Chen G.
        • Patten C.
        • Kothari D.H.
        • Zajac F.E.
        Gait differences between individuals with post-stroke hemiparesis and non-disabled controls at matched speeds.
        Gait Posture. 2005; 22: 51-56
        • Buesing C.
        • Fisch G.
        • O'Donnell M.
        • et al.
        Effects of a wearable exoskeleton stride management assist system (SMA®) on spatiotemporal gait characteristics in individuals after stroke: a randomized controlled trial.
        J Neuroeng Rehabil. 2015; 12: 69
        • Wonsetler E.C.
        • Bowden M.G.
        A systematic review of mechanisms of gait speed change post-stroke. Part 1: spatiotemporal parameters and asymmetry ratios.
        Top Stroke Rehabil. 2017; 24: 435-446
        • Wang Y.
        • Mukaino M.
        • Ohtsuka K.
        • et al.
        Gait characteristics of post-stroke hemiparetic patients with different walking speeds.
        Int J Rehabil Res. 2020; 43: 69-75
        • Verghese J.
        • Wang C.
        • Lipton R.B.
        • Holtzer R.
        • Xue X.
        Quantitative gait dysfunction and risk of cognitive decline and dementia.
        J Neurol Neurosurg Psychiatry. 2007; 78: 929-935
        • Hollman J.H.
        • McDade E.M.
        • Petersen R.C.
        Normative spatiotemporal gait parameters in older adults.
        Gait Posture. 2011; 34: 111-118
        • Lord S.
        • Galna B.
        • Verghese J.
        • Coleman S.
        • Burn D.
        • Rochester L.
        Independent domains of gait in older adults and associated motor and nonmotor attributes: validation of a factor analysis approach.
        J Gerontol A Biol Sci Med Sci. 2013; 68: 820-827
        • Olney S.J.
        • Griffin M.P.
        • McBride I.D.
        Multivariate examination of data from gait analysis of persons with stroke.
        Phys Ther. 1998; 78: 814-828
        • Thingstad P.
        • Egerton T.
        • Ihlen E.F.
        • Taraldsen K.
        • Moe-Nilssen R.
        • Helbostad J.L.
        Identification of gait domains and key gait variables following hip fracture.
        BMC Geriatr. 2015; 15: 150
        • Verlinden V.J.
        • van der Geest J.N.
        • Hoogendam Y.Y.
        • Hofman A.
        • Breteler M.M.
        • Ikram M.A.
        Gait patterns in a community-dwelling population aged 50 years and older.
        Gait Posture. 2013; 37: 500-505
        • Morris R.
        • Hickey A.
        • Del Din S.
        • Godfrey A.
        • Lord S.
        • Rochester L.
        A model of free-living gait: a factor analysis in Parkinson's disease.
        Gait Posture. 2017; 52: 68-71
        • Kim C.M.
        • Eng J.J.
        Symmetry in vertical ground reaction force is accompanied by symmetry in temporal but not distance variables of gait in persons with stroke.
        Gait Posture. 2003; 18: 23-28
        • Patterson K.K.
        • Parafianowicz I.
        • Danells C.J.
        • et al.
        Gait asymmetry in community-ambulating stroke survivors.
        Arch Phys Med Rehabil. 2008; 89: 304-310
        • Zukowski L.A.
        • Feld J.A.
        • Giuliani C.A.
        • Plummer P.
        Relationships between gait variability and ambulatory activity post stroke.
        Top Stroke Rehabil. 2019; 26: 255-260
        • Price C.
        • Parker D.
        • Nester C.
        Validity and repeatability of three in-shoe pressure measurement systems.
        Gait Posture. 2016; 46: 69-74
        • Jung H.Y.
        • Park B.K.
        • Shin H.S.
        • et al.
        Development of the Korean Version of Modified Barthel Index (K-MBI): multi-center study for subjects with stroke.
        J Korean Acad Rehabil Med. 2007; 31: 283-297
        • Kang Y.
        • Na D.L.
        • Hahn S.
        A validity study on the Korean Mini-Mental State Examination (K-MMSE) in dementia patients.
        J Korean Neurol Assoc. 1997; 15: 300-308
        • Blum L.
        • Korner-Bitensky N.
        Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review.
        Phys Ther. 2008; 88: 559-566
        • Collen F.M.
        • Wade D.T.
        • Bradshaw C.M.
        Mobility after stroke: reliability of measures of impairment and disability.
        Int Disabil Stud. 1990; 12: 6-9
        • Roerdink M.
        • Beek P.J.
        Understanding inconsistent step-length asymmetries across hemiplegic stroke patients: impairments and compensatory gait.
        Neurorehabil Neural Repair. 2011; 25: 253-258
        • Lauziere S.
        • Betschart M.
        • Aissaoui R.
        • Nadeau S.
        Understanding spatial and temporal gait asymmetries in individuals post stroke.
        Int J Phys Med Rehabil. 2014; 2: 201
        • Viteckova S.
        • Kutilek P.
        • Svoboda Z.
        • Krupicka R.
        • Kauler J.
        • Szabo Z.
        Gait symmetry measures: a review of current and prospective methods.
        Biomed Signal Process Control. 2018; 42: 89-100
        • Kaiser H.F.
        An index of factorial simplicity.
        Psychometrika. 1974; 39: 31-36
        • Peres-Neto P.R.
        • Jackson D.A.
        • Somers K.M.
        Giving meaningful interpretation to ordination axes: assessing loading significance in principal component analysis.
        Ecology. 2003; 84: 2347-2363
        • Fukuchi C.A.
        • Fukuchi R.K.
        • Duarte M.
        Effects of walking speed on gait biomechanics in healthy participants: a systematic review and meta-analysis.
        Syst Rev. 2019; 8: 153
        • Kim W.S.
        Subtasks affecting step-length asymmetry in post-stroke hemiparetic walking.
        Hum Mov Sci. 2016; 49: 87-94
        • Peterson C.L.
        • Hall A.L.
        • Kautz S.A.
        • Neptune R.R.
        Pre-swing deficits in forward propulsion, swing initiation and power generation by individual muscles during hemiparetic walking.
        J Biomech. 2010; 43: 2348-2355
        • Patterson K.K.
        • Mansfield A.
        • Biasin L.
        • Brunton K.
        • Inness E.L.
        • McIlroy W.E.
        Longitudinal changes in poststroke spatiotemporal gait asymmetry over inpatient rehabilitation.
        Neurorehabil Neural Repair. 2015; 29: 153-162
        • Brach J.S.
        • Studenski S.
        • Perera S.
        • VanSwearingen J.M.
        • Newman A.B.
        Stance time and step width variability have unique contributing impairments in older persons.
        Gait Posture. 2008; 27: 431-439
        • Balasubramanian C.K.
        • Neptune R.R.
        • Kautz S.A.
        Variability in spatiotemporal step characteristics and its relationship to walking performance post-stroke.
        Gait Posture. 2009; 29: 408-414
        • Chisholm A.E.
        • Makepeace S.
        • Inness E.L.
        • Perry S.D.
        • McIlroy W.E.
        • Mansfield A.
        Spatial-temporal gait variability poststroke: variations in measurement and implications for measuring change.
        Arch Phys Med Rehabil. 2014; 95: 1335-1341
        • Lamontagne A.
        • Stephenson J.L.
        • Fung J.
        Physiological evaluation of gait disturbances post stroke.
        Clin Neurophysiol. 2007; 118: 717-729
        • Lo O.Y.
        • Halko M.A.
        • Zhou J.
        • Harrison R.
        • Lipsitz L.A.
        • Manor B.
        Gait speed and gait variability are associated with different functional brain networks.
        Front Aging Neurosci. 2017; 9: 390
        • Takakusaki K.
        Functional neuroanatomy for posture and gait control.
        J Mov Disord. 2017; 10: 1-17
        • Moon H.I.
        • Pyun S.B.
        • Tae W.S.
        • Kwon H.K.
        Neural substrates of lower extremity motor, balance, and gait function after supratentorial stroke using voxel-based lesion symptom mapping.
        Neuroradiology. 2016; 58: 723-731
        • Handelzalts S.
        • Melzer I.
        • Soroker N.
        Analysis of brain lesion impact on balance and gait following stroke.
        Front Hum Neurosci. 2019; 13: 149
        • Beauchet O.
        • Allali G.
        • Sekhon H.
        • et al.
        Guidelines for assessment of gait and reference values for spatiotemporal gait parameters in older adults: the Biomathics and Canadian Gait Consortiums initiative.
        Front Hum Neurosci. 2017; 11: 353
        • Greene B.R.
        • Foran T.G.
        • McGrath D.
        • Doheny E.P.
        • Burns A.
        • Caulfield B.
        A comparison of algorithms for body-worn sensor-based spatiotemporal gait parameters to the GAITRite electronic walkway.
        J Appl Biomech. 2012; 28: 349-355
        • Crea S.
        • Donati M.
        • De Rossi S.M.
        • Oddo C.M.
        • Vitiello N.
        A wireless flexible sensorized insole for gait analysis.
        Sensors (Basel). 2014; 14: 1073-1093
        • Murakami K.
        • Shinozaki N.
        • Fujiwara A.
        • et al.
        A systematic review of principal component analysis-derived dietary patterns in Japanese adults: are major dietary patterns reproducible within a country?.
        Adv Nutr. 2019; 10: 237-249
        • Shanahan C.J.
        • Boonstra F.M.C.
        • Cofre Lizama L.E.
        • et al.
        Technologies for advanced gait and balance assessments in people with multiple sclerosis.
        Front Neurol. 2017; 8: 708
        • Tao W.
        • Liu T.
        • Zheng R.
        • Feng H.
        Gait analysis using wearable sensors.
        Sensors (Basel). 2012; 12: 2255-2283