Comprehensive measurement of stroke gait characteristics with a single accelerometer in the laboratory and community: a feasibility, validity and reliability study

BackgroundApplication of objective measurement of stroke gait with accelerometer-based wearable technology and associated algorithms is increasing, despite reports questioning the accuracy of this technique in quantifying specific stroke-related gait impairments. The aim of this study is to determine the feasibility, validity and reliability of a low-cost open-source system incorporating algorithms and a single tri-axial accelerometer-based wearable to quantify gait characteristics in the laboratory and community post-stroke.MethodsTwenty-five participants with stroke wore the wearable (AX3, Axivity) on the lower back during a laboratory 2 minute continuous walk (preferred pace) on two occasions a week apart and continuously in the community for two consecutive 7 day periods. Video, instrumented walkway (GaitRite) and an OPAL accelerometer-based wearable were used as laboratory references.ResultsFeasibility of the proposed system was good. The system was valid for measuring step count (ICC 0.899). Inherent differences in gait quantification between algorithm and GaitRite resulted in difficulties comparing agreement between the different systems. Agreement was moderate-excellent (ICC 0.503–0.936) for mean and variability gait characteristics vs. OPAL. Agreement was moderate-poor between the system and OPAL for asymmetry characteristics. Moderate-excellent reliability (ICC 0.534–0.857) was demonstrated for 11/14 laboratory measured gait characteristics. Community test-retest reliability was good-excellent (ICC 0.867–0.983) for all except one (ICC 0.699) of the 19 gait characteristics.ConclusionThe proposed system is a low-cost, reliable tool for quantifying gait post-stroke with multiple potential applications. Further refinement to optimise gait quantification algorithms for certain gait characteristics including gait asymmetry is required.

[1]  J. Spence,et al.  Combining Multiple Approaches for the Secondary Prevention of Vascular Events After Stroke: A Quantitative Modeling Study , 2007, Stroke.

[2]  Lynn Rochester,et al.  Is gait variability reliable in older adults and Parkinson's disease? Towards an optimal testing protocol. , 2013, Gait & posture.

[3]  M. Batavia,et al.  The validity and reliability of the GAITRite system's measurements: A preliminary evaluation. , 2001, Archives of physical medicine and rehabilitation.

[4]  D. Wade,et al.  Measurement in neurological rehabilitation. , 1992, Current opinion in neurology and neurosurgery.

[5]  Lynn Rochester,et al.  The pattern of habitual sedentary behavior is different in advanced Parkinson's disease , 2010, Movement disorders : official journal of the Movement Disorder Society.

[6]  Miao-Ju Hsu,et al.  Psychometric Comparisons of 3 Functional Ambulation Measures for Patients With Stroke , 2010, Stroke.

[7]  Lynn Rochester,et al.  Independent domains of gait in older adults and associated motor and nonmotor attributes: validation of a factor analysis approach. , 2013, The journals of gerontology. Series A, Biological sciences and medical sciences.

[8]  A. Godfrey,et al.  iCap: Instrumented assessment of physical capability , 2015, Maturitas.

[9]  J. Lechner-Scott,et al.  Persistence on Therapy and Propensity Matched Outcome Comparison of Two Subcutaneous Interferon Beta 1a Dosages for Multiple Sclerosis , 2013, PloS one.

[10]  Jeffrey M. Hausdorff,et al.  Comparative assessment of different methods for the estimation of gait temporal parameters using a single inertial sensor: application to elderly, post-stroke, Parkinson's disease and Huntington's disease subjects. , 2015, Gait & posture.

[11]  Ines Becker,et al.  Measuring free-living physical activity in adults with and without neurologic dysfunction with a triaxial accelerometer. , 2008, Archives of physical medicine and rehabilitation.

[12]  B. Galna,et al.  Free-living gait characteristics in ageing and Parkinson’s disease: impact of environment and ambulatory bout length , 2016, Journal of NeuroEngineering and Rehabilitation.

[13]  Alan Godfrey,et al.  Detecting free-living steps and walking bouts: validating an algorithm for macro gait analysis , 2017, Physiological measurement.

[14]  Alan Godfrey,et al.  Validation of an Accelerometer to Quantify a Comprehensive Battery of Gait Characteristics in Healthy Older Adults and Parkinson's Disease: Toward Clinical and at Home Use , 2016, IEEE Journal of Biomedical and Health Informatics.

[15]  F. Horak,et al.  Role of Body-Worn Movement Monitor Technology for Balance and Gait Rehabilitation , 2014, Physical Therapy.

[16]  A. Godfrey,et al.  Instrumenting gait with an accelerometer: A system and algorithm examination , 2015, Medical engineering & physics.

[17]  B. Dobkin,et al.  Reliability and Validity of Bilateral Ankle Accelerometer Algorithms for Activity Recognition and Walking Speed After Stroke , 2011, Stroke.

[18]  S. Black,et al.  The Fugl-Meyer Assessment of Motor Recovery after Stroke: A Critical Review of Its Measurement Properties , 2002, Neurorehabilitation and neural repair.

[19]  H. Dawes,et al.  Assessment of spatio-temporal gait parameters using inertial measurement units in neurological populations. , 2011, Gait & posture.

[20]  C. Mazzà,et al.  Step Detection and Activity Recognition Accuracy of Seven Physical Activity Monitors , 2015, PloS one.

[21]  E. D. de Bruin,et al.  Concurrent validity of a trunk tri-axial accelerometer system for gait analysis in older adults. , 2009, Gait & posture.

[22]  J. Marler,et al.  Measurements of acute cerebral infarction: a clinical examination scale. , 1989, Stroke.

[23]  J. Bamford,et al.  Classification and natural history of clinically identifiable subtypes of cerebral infarction , 1991, The Lancet.

[24]  Sarah A. Moore,et al.  Newcastle University E-prints Citation for Item: Physical Activity, Sedentary Behaviour and Metabolic Control following Stroke: a Cross-sectional and Longitudinal Study , 2022 .

[25]  Jennifer L. Keating,et al.  How is physical activity monitored in people following stroke? , 2015, Disability and rehabilitation.

[26]  A. Mansfield,et al.  Title : Inter-and intra-rater reliability of the GAITRite system among individuals with subacute stroke , 2019 .

[27]  T. Dwyer,et al.  Objectively Measured Daily Steps and Subsequent Long Term All-Cause Mortality: The Tasped Prospective Cohort Study , 2015, PloS one.

[28]  A. Geurts,et al.  Definition dependent properties of the cortical silent period in upper-extremity muscles, a methodological study , 2014, Journal of NeuroEngineering and Rehabilitation.

[29]  A. Hof,et al.  Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. , 2003, Gait & posture.

[30]  K Aminian,et al.  Technical and clinical view on ambulatory assessment in Parkinson's disease , 2014, Acta neurologica Scandinavica.

[31]  Ki Woong Kim,et al.  Test-Retest Reliability and Concurrent Validity of a Single Tri-Axial Accelerometer-Based Gait Analysis in Older Adults with Normal Cognition , 2016, PloS one.

[32]  Lynn Rochester,et al.  Understanding the impact of deep brain stimulation on ambulatory activity in advanced Parkinson’s disease , 2012, Journal of Neurology.

[33]  C. Mazzà,et al.  Free‐living monitoring of Parkinson's disease: Lessons from the field , 2016, Movement disorders : official journal of the Movement Disorder Society.

[34]  John D Sorkin,et al.  Steps After Stroke: Capturing Ambulatory Recovery , 2005, Stroke.

[35]  Jeffrey M. Hausdorff,et al.  Estimation of step-by-step spatio-temporal parameters of normal and impaired gait using shank-mounted magneto-inertial sensors: application to elderly, hemiparetic, parkinsonian and choreic gait , 2014, Journal of NeuroEngineering and Rehabilitation.

[36]  D. Reisman,et al.  The Structure of Walking Activity in People After Stroke Compared With Older Adults Without Disability: A Cross-Sectional Study , 2012, Physical Therapy.

[37]  C. Walsh,et al.  Effect of timing of hip extension assistance during loaded walking with a soft exosuit , 2016, Journal of NeuroEngineering and Rehabilitation.

[38]  Linda Little,et al.  Exploring patterns of daily physical and sedentary behaviour in community-dwelling older adults. , 2011, Age and ageing.

[39]  Avril Mansfield,et al.  Inter- and intra-rater reliability of the GAITRite system among individuals with sub-acute stroke. , 2014, Gait & posture.

[40]  G. Fulk,et al.  Predicting home and community walking activity in people with stroke. , 2010, Archives of physical medicine and rehabilitation.

[41]  Sandra G Brauer,et al.  Test-retest reliability of the GAITRite system in people with stroke undergoing rehabilitation , 2011, Disability and rehabilitation.

[42]  Kim L Coleman,et al.  Accelerometer monitoring of home- and community-based ambulatory activity after stroke. , 2004, Archives of physical medicine and rehabilitation.

[43]  Sandra G Brauer,et al.  Recovery of ambulation activity across the first six months post-stroke. , 2016, Gait & posture.