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      Wearable technology for spine movement assessment: A systematic review

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          Abstract

          Continuous monitoring of spine movement function could enhance our understanding of low back pain development. Wearable technologies have gained popularity as promising alternative to laboratory systems in allowing ambulatory movement analysis. This paper aims to review the state of art of current use of wearable technology to assess spine kinematics and kinetics.

          Four electronic databases and reference lists of relevant articles were searched to find studies employing wearable technologies to assess the spine in adults performing dynamic movements. Two reviewers independently identified relevant papers. Customised data extraction and quality appraisal form were developed to extrapolate key details and identify risk of biases of each study. Twenty-two articles were retrieved that met the inclusion criteria: 12 were deemed of medium quality (score 33.4–66.7%), and 10 of high quality (score >66.8%). The majority of articles (19/22) reported validation type studies. Only 6 reported data collection in real-life environments. Multiple sensors type were used: electrogoniometers (3/22), strain gauges based sensors (3/22), textile piezoresistive sensor (1/22) and accelerometers often used with gyroscopes and magnetometers (15/22). Two sensors units were mainly used and placing was commonly reported on the spine lumbar and sacral regions. The sensors were often wired to data transmitter/logger resulting in cumbersome systems. Outcomes were mostly reported relative to the lumbar segment and in the sagittal plane, including angles, range of motion, angular velocity, joint moments and forces.

          This review demonstrates the applicability of wearable technology to assess the spine, although this technique is still at an early stage of development.

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          Most cited references32

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          Human movement analysis using stereophotogrammetry. Part 3. Soft tissue artifact assessment and compensation.

          When using optoelectronic stereophotogrammetry, skin deformation and displacement causes marker movement with respect to the underlying bone. This movement represents an artifact, which affects the estimation of the skeletal system kinematics, and is regarded as the most critical source of error in human movement analysis. A comprehensive review of the state-of-the-art for assessment, minimization and compensation of the soft tissue artifact (STA) is provided. It has been shown that STA is greater than the instrumental error associated with stereophotogrammetry, has a frequency content similar to the actual bone movement, is task dependent and not reproducible among subjects and, of lower limb segments, is greatest at the thigh. It has been shown that in in vivo experiments only motion about the flexion/extension axis of the hip, knees and ankles can be determined reliably. Motion about other axes at those joints should be regarded with much more caution as this artifact produces spurious effects with magnitudes comparable to the amount of motion actually occurring in those joints. Techniques designed to minimize the contribution of and compensate for the effects of this artifact can be divided up into those which model the skin surface and those which include joint motion constraints. Despite the numerous solutions proposed, the objective of reliable estimation of 3D skeletal system kinematics using skin markers has not yet been satisfactorily achieved and greatly limits the contribution of human movement analysis to clinical practice and biomechanical research. For STA to be compensated for effectively, it is here suggested that either its subject-specific pattern is assessed by ad hoc exercises or it is characterized from a large series of measurements on different subject populations. Alternatively, inclusion of joint constraints into a more general STA minimization approach may provide an acceptable solution.
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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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              The Use of Wearable Inertial Motion Sensors in Human Lower Limb Biomechanics Studies: A Systematic Review

              Wearable motion sensors consisting of accelerometers, gyroscopes and magnetic sensors are readily available nowadays. The small size and low production costs of motion sensors make them a very good tool for human motions analysis. However, data processing and accuracy of the collected data are important issues for research purposes. In this paper, we aim to review the literature related to usage of inertial sensors in human lower limb biomechanics studies. A systematic search was done in the following search engines: ISI Web of Knowledge, Medline, SportDiscus and IEEE Xplore. Thirty nine full papers and conference abstracts with related topics were included in this review. The type of sensor involved, data collection methods, study design, validation methods and its applications were reviewed.
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                Author and article information

                Contributors
                Journal
                J Biomech
                J Biomech
                Journal of Biomechanics
                Elsevier Science
                0021-9290
                1873-2380
                07 November 2017
                07 November 2017
                : 64
                : 186-197
                Affiliations
                [a ]Department of Surgery and Cancer, Imperial College London, London, UK
                [b ]Department of Bioengineering, Imperial College London, London, UK
                Author notes
                [* ]Corresponding author at: Department of Surgery and Cancer, Imperial College London, Room 7L16, Floor 7, Laboratory Block, Charing Cross Hospital, London W6 8RF, UK.Department of Surgery and CancerImperial College LondonRoom 7L16Floor 7Laboratory BlockCharing Cross HospitalLondonW6 8RFUK e.papi@ 123456imperial.ac.uk
                Article
                S0021-9290(17)30510-9
                10.1016/j.jbiomech.2017.09.037
                5700811
                29102267
                508f2d4e-8c56-4b54-a253-f4166566ca1a
                © 2017 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 25 September 2017
                Categories
                Article

                Biophysics
                spine,wearable sensor,motion analysis,kinematics,kinetics
                Biophysics
                spine, wearable sensor, motion analysis, kinematics, kinetics

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