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

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          Abstract

          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.

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          Most cited references85

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          Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention.

          The proliferation of miniaturized electronics has fueled a shift toward wearable sensors and feedback devices for the mass population. Quantified self and other similar movements involving wearable systems have gained recent interest. However, it is unclear what the clinical impact of these enabling technologies is on human gait. The purpose of this review is to assess clinical applications of wearable sensing and feedback for human gait and to identify areas of future research. Four electronic databases were searched to find articles employing wearable sensing or feedback for movements of the foot, ankle, shank, thigh, hip, pelvis, and trunk during gait. We retrieved 76 articles that met the inclusion criteria and identified four common clinical applications: (1) identifying movement disorders, (2) assessing surgical outcomes, (3) improving walking stability, and (4) reducing joint loading. Characteristics of knee and trunk motion were the most frequent gait parameters for both wearable sensing and wearable feedback. Most articles performed testing on healthy subjects, and the most prevalent patient populations were osteoarthritis, vestibular loss, Parkinson's disease, and post-stroke hemiplegia. The most widely used wearable sensors were inertial measurement units (accelerometer and gyroscope packaged together) and goniometers. Haptic (touch) and auditory were the most common feedback sensations. This review highlights the current state of the literature and demonstrates substantial potential clinical benefits of wearable sensing and feedback. Future research should focus on wearable sensing and feedback in patient populations, in natural human environments outside the laboratory such as at home or work, and on continuous, long-term monitoring and intervention. Copyright © 2014 Elsevier B.V. All rights reserved.
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            Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review.

            After decades of evolution, measuring instruments for quantitative gait analysis have become an important clinical tool for assessing pathologies manifested by gait abnormalities. However, such instruments tend to be expensive and require expert operation and maintenance besides their high cost, thus limiting them to only a small number of specialized centers. Consequently, gait analysis in most clinics today still relies on observation-based assessment. Recent advances in wearable sensors, especially inertial body sensors, have opened up a promising future for gait analysis. Not only can these sensors be more easily adopted in clinical diagnosis and treatment procedures than their current counterparts, but they can also monitor gait continuously outside clinics - hence providing seamless patient analysis from clinics to free-living environments. The purpose of this paper is to provide a systematic review of current techniques for quantitative gait analysis and to propose key metrics for evaluating both existing and emerging methods for qualifying the gait features extracted from wearable sensors. It aims to highlight key advances in this rapidly evolving research field and outline potential future directions for both research and clinical applications.
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              Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems.

              A general-purpose system to obtain the kinematics of gait in the sagittal plane based on body-mounted sensors was developed. It consisted of four uniaxial seismic accelerometers and one rate gyroscope per body segment. Tests were done with 10 young healthy volunteers, walking at five different speeds on a treadmill. In order to study the system's accuracy, measurements were made with an optic, passive-marker system and the body-mounted system, simultaneously. In all the comparison cases, the curves obtained from the two systems were very close, showing root mean square errors representing <7% full range in 75% of the cases (overall mean 6.64%, standard deviation 4.13%) and high coefficients of multiple correlation in 100% of cases (overall mean 0.9812, standard deviation 0.02). Calibration of the body-mounted system is done against gravity. The body-mounted sensors do not hinder natural movement. The calculation algorithms are computationally demanding and only are applicable off-line. The body-mounted sensors are accurate, inexpensive and portable and allow long-term recordings in clinical, sport and ergonomics settings.
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                Author and article information

                Contributors
                michael.hunt@ubc.ca
                Journal
                J Neuroeng Rehabil
                J Neuroeng Rehabil
                Journal of NeuroEngineering and Rehabilitation
                BioMed Central (London )
                1743-0003
                11 May 2020
                11 May 2020
                2020
                : 17
                : 62
                Affiliations
                [1 ]GRID grid.25073.33, ISNI 0000 0004 1936 8227, Department of Kinesiology, McMaster University, ; Hamilton, ON Canada
                [2 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, Motion Analysis and Biofeedback Laboratory, , University of British Columbia, ; Vancouver, BC Canada
                [3 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, Graduate Programs in Rehabilitation Sciences, , University of British Columbia, ; Vancouver, BC Canada
                [4 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, Department of Physical Therapy, , University of British Columbia, ; Vancouver, BC Canada
                [5 ]The Running Clinic, Lac Beauport, QC Canada
                Article
                685
                10.1186/s12984-020-00685-3
                7216606
                32393301
                9106d61d-eab0-474c-92b0-356838499dff
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 21 November 2019
                : 7 April 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000038, Natural Sciences and Engineering Research Council of Canada;
                Categories
                Review
                Custom metadata
                © The Author(s) 2020

                Neurosciences
                inertial sensors,inertial measurement units,gait,biomechanics,validity,reliability,review
                Neurosciences
                inertial sensors, inertial measurement units, gait, biomechanics, validity, reliability, review

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