Validity and reliability of wearable inertial sensors in healthy adult walking: a systematic review and meta-analysis

Background Inertial measurement units (IMUs) offer the ability to measure walking gait through a variety of biomechanical outcomes (e.g., spatiotemporal, kinematics, other). Although many studies have assessed their validity and reliability, there remains no quantitive summary of this vast body of literature. Therefore, we aimed to conduct a systematic review and meta-analysis to determine the i) concurrent validity and ii) test-retest reliability of IMUs for measuring biomechanical gait outcomes during level walking in healthy adults. Methods Five electronic databases were searched for journal articles assessing the validity or reliability of IMUs during healthy adult walking. Two reviewers screened titles, abstracts, and full texts for studies to be included, before two reviewers examined the methodological quality of all included studies. When sufficient data were present for a given biomechanical outcome, data were meta-analyzed on Pearson correlation coefficients (r) or intraclass correlation coefficients (ICC) for validity and reliability, respectively. Alternatively, qualitative summaries of outcomes were conducted on those that could not be meta-analyzed. Results A total of 82 articles, assessing the validity or reliability of over 100 outcomes, were included in this review. Seventeen biomechanical outcomes, primarily spatiotemporal parameters, were meta-analyzed. The validity and reliability of step and stride times were found to be excellent. Similarly, the validity and reliability of step and stride length, as well as swing and stance time, were found to be good to excellent. Alternatively, spatiotemporal parameter variability and symmetry displayed poor to moderate validity and reliability. IMUs were also found to display moderate reliability for the assessment of local dynamic stability during walking. The remaining biomechanical outcomes were qualitatively summarized to provide a variety of recommendations for future IMU research. Conclusions The findings of this review demonstrate the excellent validity and reliability of IMUs for mean spatiotemporal parameters during walking, but caution the use of spatiotemporal variability and symmetry metrics without strict protocol. Further, this work tentatively supports the use of IMUs for joint angle measurement and other biomechanical outcomes such as stability, regularity, and segmental accelerations. Unfortunately, the strength of these recommendations are limited based on the lack of high-quality studies for each outcome, with underpowered and/or unjustified sample sizes (sample size median 12; range: 2–95) being the primary limitation.

[1]  Vipul Lugade,et al.  Reliability and validity of a smartphone-based assessment of gait parameters across walking speed and smartphone locations: Body, bag, belt, hand, and pocket. , 2017, Gait & posture.

[2]  Haisheng Xia,et al.  Validation of a smart shoe for estimating foot progression angle during walking gait. , 2017, Journal of biomechanics.

[3]  Xavier Crevoisier,et al.  Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors. , 2013, Gait & posture.

[4]  Jorunn L Helbostad,et al.  Estimation of gait cycle characteristics by trunk accelerometry. , 2004, Journal of biomechanics.

[5]  H. Dawes,et al.  IMU: inertial sensing of vertical CoM movement. , 2009, Journal of Biomechanics.

[6]  Graham K. Kerr,et al.  Concurrent Validity of Accelerations Measured Using a Tri-Axial Inertial Measurement Unit while Walking on Firm, Compliant and Uneven Surfaces , 2014, PloS one.

[7]  Christopher R. Harris,et al.  Accurate and Reliable Gait Cycle Detection in Parkinson's Disease , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[8]  E. Allseits,et al.  The development and concurrent validity of a real-time algorithm for temporal gait analysis using inertial measurement units. , 2017, Journal of biomechanics.

[9]  Michael Lorenz,et al.  Towards Inertial Sensor Based Mobile Gait Analysis: Event-Detection and Spatio-Temporal Parameters , 2018, Sensors.

[10]  D. Altman,et al.  A note on the use of the intraclass correlation coefficient in the evaluation of agreement between two methods of measurement. , 1990, Computers in biology and medicine.

[11]  Fotis Foukalas,et al.  Wireless Communication Technologies for Safe Cooperative Cyber Physical Systems , 2018, Sensors.

[12]  Andreas Daffertshofer,et al.  Assessing gait stability: the influence of state space reconstruction on inter- and intra-day reliability of local dynamic stability during over-ground walking. , 2013, Journal of biomechanics.

[13]  Vanathi Gopalakrishnan,et al.  cMRI-BED: A novel informatics framework for cardiac MRI biomarker extraction and discovery applied to pediatric cardiomyopathy classification , 2015, BioMedical Engineering OnLine.

[14]  Michael L. Thomas,et al.  Minimization of Childhood Maltreatment Is Common and Consequential: Results from a Large, Multinational Sample Using the Childhood Trauma Questionnaire , 2016, PloS one.

[15]  Lynn Rochester,et al.  Concurrent validity of accelerometry to measure gait in Parkinsons Disease. , 2008, Gait & posture.

[16]  Philippe Terrier,et al.  Local dynamic stability of treadmill walking: intrasession and week-to-week repeatability. , 2013, Journal of biomechanics.

[17]  Adrian Burns,et al.  An adaptive gyroscope-based algorithm for temporal gait analysis , 2010, Medical & Biological Engineering & Computing.

[18]  I Jonkers,et al.  Mobile assessment of the lower limb kinematics in healthy persons and in persons with degenerative knee disorders: A systematic review. , 2018, Gait & posture.

[19]  Marcus J Fuhrer,et al.  Rehabilitation medicine summit: building research capacity Executive Summary , 2006, Journal of NeuroEngineering and Rehabilitation.

[20]  Alexandre Campeau-Lecours,et al.  Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review , 2019, Sensors.

[21]  W. J. Beek,et al.  Hemiplegic gait: a kinematic analysis using walking speed as a basis. , 1992, Journal of biomechanics.

[22]  Kate Button,et al.  Inertial Measurement Units for Clinical Movement Analysis: Reliability and Concurrent Validity , 2018, Sensors.

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

[24]  Daniel Tik-Pui Fong,et al.  The Use of Wearable Inertial Motion Sensors in Human Lower Limb Biomechanics Studies: A Systematic Review , 2010, Sensors.

[25]  Mario Bizzini,et al.  Concurrent validity and intrasession reliability of the IDEEA accelerometry system for the quantification of spatiotemporal gait parameters. , 2008, Gait & posture.

[26]  Scott L Delp,et al.  Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention. , 2014, Gait & posture.

[27]  Diana Hodgins,et al.  Inertial sensor-based knee flexion/extension angle estimation. , 2009, Journal of biomechanics.

[28]  Ilse Jonkers,et al.  Reliability of 3D Lower Extremity Movement Analysis by Means of Inertial Sensor Technology during Transitional Tasks , 2018, Sensors.

[29]  A. Hrõbjartsson,et al.  Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed. , 2011, Journal of clinical epidemiology.

[30]  Guang-Zhong Yang,et al.  Gait Parameter Estimation From a Miniaturized Ear-Worn Sensor Using Singular Spectrum Analysis and Longest Common Subsequence , 2014, IEEE Transactions on Biomedical Engineering.

[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]  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.

[33]  Chandramouli Krishnan,et al.  Validity and repeatability of inertial measurement units for measuring gait parameters. , 2017, Gait & posture.

[34]  Diana Trojaniello,et al.  Accuracy, sensitivity and robustness of five different methods for the estimation of gait temporal parameters using a single inertial sensor mounted on the lower trunk. , 2014, Gait & posture.

[35]  Daniel Hamacher,et al.  Towards the assessment of local dynamic stability of level-grounded walking in an older population. , 2015, Medical engineering & physics.

[36]  B. Zhang,et al.  Evaluation of spatial distribution and characterization of wall shear stress in carotid sinus based on two-dimensional color Doppler imaging , 2018, BioMedical Engineering OnLine.

[37]  D. Altman,et al.  Measuring inconsistency in meta-analyses , 2003, BMJ : British Medical Journal.

[38]  Susan E. Fasoli,et al.  Evidence-Based Rehabilitation: A Guide to Practice , 2003 .

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

[40]  Patrick Boissy,et al.  Inertial measurement systems for segments and joints kinematics assessment: towards an understanding of the variations in sensors accuracy , 2017, BioMedical Engineering OnLine.

[41]  Bertram Taetz,et al.  Validity, Test-Retest Reliability and Long-Term Stability of Magnetometer Free Inertial Sensor Based 3D Joint Kinematics , 2018, Sensors.

[42]  Thomas Seel,et al.  IMU-Based Joint Angle Measurement for Gait Analysis , 2014, Sensors.

[43]  Hikaru Inooka,et al.  A Method for Gait Analysis in a Daily Living Environment by Body-Mounted Instruments , 2001 .

[44]  Gert S. Faber,et al.  Estimating Dynamic Gait Stability Using Data from Non-aligned Inertial Sensors , 2010, Annals of Biomedical Engineering.

[45]  A A Amis,et al.  Gait asymmetry detection in older adults using a light ear-worn sensor , 2014, Physiological measurement.

[46]  Anthony C. Redmond,et al.  Concurrent validation of activity monitors in patients with rheumatoid arthritis , 2013, Clinical biomechanics.

[47]  Andrea Cereatti,et al.  Bilateral step length estimation using a single inertial measurement unit attached to the pelvis , 2012, Journal of NeuroEngineering and Rehabilitation.

[48]  Christine Azevedo Coste,et al.  Implementation and Validation of a Stride Length Estimation Algorithm, Using a Single Basic Inertial Sensor on Healthy Subjects and Patients Suffering from Parkinson’s Disease , 2015 .

[49]  Keith D Hill,et al.  Gait variability in younger and older adult women is altered by overground walking protocol. , 2009, Age and ageing.

[50]  J. Arokoski,et al.  Repeatability of knee impulsive loading measurements with skin-mounted accelerometers and lower limb surface electromyographic recordings during gait in knee osteoarthritic and asymptomatic individuals , 2016, Journal of musculoskeletal & neuronal interactions.

[51]  Bart Jansen,et al.  Reliability and clinical correlates of 3D-accelerometry based gait analysis outcomes according to age and fall-risk. , 2011, Gait & posture.

[52]  D. V. Van Citters,et al.  Stance and swing phase knee flexion recover at different rates following total knee arthroplasty: An inertial measurement unit study. , 2019, Journal of biomechanics.

[53]  K. Aminian,et al.  Evaluation of an ambulatory system for gait analysis in hip osteoarthritis and after total hip replacement. , 2004, Gait & posture.

[54]  R. Baker Gait analysis methods in rehabilitation , 2006, Journal of NeuroEngineering and Rehabilitation.

[55]  Jukka S Jurvelin,et al.  Reproducibility of loading measurements with skin-mounted accelerometers during walking. , 2007, Archives of physical medicine and rehabilitation.

[56]  Andrea Mannini,et al.  Fourier-based integration of quasi-periodic gait accelerations for drift-free displacement estimation using inertial sensors , 2015, BioMedical Engineering OnLine.

[57]  Peter H Veltink,et al.  Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. , 2002, Journal of biomechanics.

[58]  Mark S. Redfern,et al.  Extraction of Stride Events From Gait Accelerometry During Treadmill Walking , 2015, IEEE Journal of Translational Engineering in Health and Medicine.

[59]  Allan Donner,et al.  Sample size requirements for the design of reliability study: review and new results , 2004 .

[60]  M L'Hermette,et al.  A New Portable Device for Assessing Locomotor Performance , 2007, International journal of sports medicine.

[61]  Federica Verdini,et al.  Gait parameter and event estimation using smartphones. , 2017, Gait & posture.

[62]  Jorunn L Helbostad,et al.  Gait variability measures may represent different constructs. , 2010, Gait & posture.

[63]  P. Gorce,et al.  Analysis of several methods and inertial sensors locations to assess gait parameters in able-bodied subjects. , 2015, Gait & posture.

[64]  Brian Caulfield,et al.  Gyroscope-based assessment of temporal gait parameters during treadmill walking and running , 2012 .

[65]  Steven Morrison,et al.  Reliability of segmental accelerations measured using a new wireless gait analysis system. , 2006, Journal of biomechanics.

[66]  Haisheng Xia,et al.  Validity and reliability of a shoe-embedded sensor module for measuring foot progression angle during over-ground walking. , 2019, Journal of biomechanics.

[67]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

[68]  Guang-Zhong Yang,et al.  Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review , 2016, IEEE Journal of Biomedical and Health Informatics.

[69]  R. Moe-Nilssen Test-retest reliability of trunk accelerometry during standing and walking. , 1998, Archives of physical medicine and rehabilitation.

[70]  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.

[71]  Paul B Gastin,et al.  Validity of a trunk-mounted accelerometer to assess peak accelerations during walking, jogging and running , 2015, European journal of sport science.

[72]  Naomichi Ogihara,et al.  Estimation of foot trajectory during human walking by a wearable inertial measurement unit mounted to the foot. , 2016, Gait & posture.

[73]  Tao Liu,et al.  Gait Analysis Using Wearable Sensors , 2012, Sensors.

[74]  A Leardini,et al.  Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: Validation on normal subjects by standard gait analysis , 2012, Comput. Methods Programs Biomed..

[75]  Long Tang,et al.  Instantaneous Real-Time Kinematic Decimeter-Level Positioning with BeiDou Triple-Frequency Signals over Medium Baselines , 2015, Sensors.

[76]  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.

[77]  Eling D de Bruin,et al.  Reproducibility of spatio-temporal gait parameters under different conditions in older adults using a trunk tri-axial accelerometer system. , 2009, Gait & posture.

[78]  Martina Minnerop,et al.  Accuracy and repeatability of two methods of gait analysis - GaitRite™ und Mobility Lab™ - in subjects with cerebellar ataxia. , 2016, Gait & posture.

[79]  B. Dobkin,et al.  Reliability and Validity of Bilateral Thigh and Foot Accelerometry Measures of Walking in Healthy and Hemiparetic Subjects , 2006, Neurorehabilitation and neural repair.

[80]  Jeffrey M. Hausdorff,et al.  Estimation of spatio-temporal parameters of gait from magneto-inertial measurement units: multicenter validation among Parkinson, mildly cognitively impaired and healthy older adults , 2018, BioMedical Engineering OnLine.

[81]  R Senden,et al.  Validity of an inertial measurement unit to assess pelvic orientation angles during gait, sit-stand transfers and step-up transfers: Comparison with an optoelectronic motion capture system. , 2016, Medical engineering & physics.

[82]  Bernd Markert,et al.  A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms. , 2017, Gait & posture.

[83]  G. Drummond,et al.  Reporting of method comparison studies: a review of advice, an assessment of current practice, and specific suggestions for future reports. , 2016, British journal of anaesthesia.

[84]  Eric Chalmers,et al.  Inertial sensing algorithms for long-term foot angle monitoring for assessment of idiopathic toe-walking. , 2014, Gait & posture.

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

[86]  Tao Liu,et al.  Novel approach to ambulatory assessment of human segmental orientation on a wearable sensor system. , 2009, Journal of biomechanics.

[87]  Ian Sheret,et al.  A smart device inertial-sensing method for gait analysis. , 2014, Journal of biomechanics.

[88]  Kazuya Okamoto,et al.  Reliability and validity of gait analysis by android-based smartphone. , 2012, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[89]  H.J. Stam,et al.  Automated estimation of initial and terminal contact timing using accelerometers; development and validation in transtibial amputees and controls , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[90]  Martina Furrer,et al.  Validation of a smartphone-based measurement tool for the quantification of level walking. , 2015, Gait & posture.

[91]  H. M. Schepers,et al.  Musculoskeletal model-based inverse dynamic analysis under ambulatory conditions using inertial motion capture. , 2019, Medical engineering & physics.

[92]  Wiebren Zijlstra,et al.  Trunk-acceleration based assessment of gait parameters in older persons: a comparison of reliability and validity of four inverted pendulum based estimations. , 2013, Gait & posture.

[93]  Brian Caulfield,et al.  A comparison of algorithms for body-worn sensor-based spatiotemporal gait parameters to the GAITRite electronic walkway. , 2012, Journal of applied biomechanics.

[94]  Subashan Perera,et al.  The reliability and validity of measures of gait variability in community-dwelling older adults. , 2008, Archives of physical medicine and rehabilitation.

[95]  K. Meijer,et al.  Acceleration-based gait test for healthy subjects: reliability and reference data. , 2009, Gait & posture.

[96]  Stefano Paolucci,et al.  Wearable inertial sensors for human movement analysis , 2016, Expert review of medical devices.

[97]  Daniel Hamacher,et al.  Towards clinical application: repetitive sensor position re-calibration for improved reliability of gait parameters. , 2014, Gait & posture.

[98]  Andrea Furlan,et al.  Updated Method Guidelines for Systematic Reviews in the Cochrane Collaboration Back Review Group , 2003, Spine.

[99]  Claudia Mazzà,et al.  Gait event detection in laboratory and real life settings: Accuracy of ankle and waist sensor based methods. , 2016, Gait & posture.

[100]  Kamiar Aminian,et al.  Heel and Toe Clearance Estimation for Gait Analysis Using Wireless Inertial Sensors , 2012, IEEE Transactions on Biomedical Engineering.

[101]  Anthony Dalton,et al.  Analysis of gait and balance through a single triaxial accelerometer in presymptomatic and symptomatic Huntington's disease. , 2013, Gait & posture.

[102]  Iain Murray,et al.  Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems , 2019, Sensors.

[103]  Lynn Rochester,et al.  Gait variability in older adults: a structured review of testing protocol and clinimetric properties. , 2011, Gait & posture.

[104]  Jesús Fontecha,et al.  Comparison between passive vision-based system and a wearable inertial-based system for estimating temporal gait parameters related to the GAITRite electronic walkway , 2016, J. Biomed. Informatics.

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

[106]  Mark R. Cutkosky,et al.  Novel Foot Progression Angle Algorithm Estimation via Foot-Worn, Magneto-Inertial Sensing , 2016, IEEE Transactions on Biomedical Engineering.

[107]  Hao Zhu,et al.  Smartphone App–Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability , 2018, JMIR mHealth and uHealth.

[108]  Sheldon R Simon,et al.  Quantification of human motion: gait analysis-benefits and limitations to its application to clinical problems. , 2004, Journal of biomechanics.

[109]  Julius Hannink,et al.  Towards Mobile Gait Analysis: Concurrent Validity and Test-Retest Reliability of an Inertial Measurement System for the Assessment of Spatio-Temporal Gait Parameters , 2017, Sensors.

[110]  Katja Orlowski,et al.  Examination of the reliability of an inertial sensor-based gait analysis system , 2017, Biomedizinische Technik. Biomedical engineering.

[111]  E Allseits,et al.  A practical step length algorithm using lower limb angular velocities. , 2018, Journal of biomechanics.

[112]  L. Hedges,et al.  The Handbook of Research Synthesis and Meta-Analysis , 2009 .

[113]  Qingguo Li,et al.  Concurrent validation of Xsens MVN measurement of lower limb joint angular kinematics , 2013, Physiological measurement.

[114]  Mario Bizzini,et al.  Test–retest reliability of the IDEEA system in the quantification of step parameters during walking and stair climbing , 2009, Clinical physiology and functional imaging.

[115]  Katja D. Mombaur,et al.  Robust Foot Clearance Estimation Based on the Integration of Foot-Mounted IMU Acceleration Data , 2015, Sensors.

[116]  R. Moe-Nilssen,et al.  Test-retest reliability of trunk accelerometric gait analysis. , 2004, Gait & posture.