4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Validation of Spatiotemporal and Kinematic Measures in Functional Exercises Using a Minimal Modeling Inertial Sensor Methodology

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          This study proposes a minimal modeling magnetic, angular rate and gravity (MARG) methodology for assessing spatiotemporal and kinematic measures of functional fitness exercises. Thirteen healthy persons performed repetitions of the squat, box squat, sandbag pickup, shuffle-walk, and bear crawl. Sagittal plane hip, knee, and ankle range of motion (ROM) and stride length, stride time, and stance time measures were compared for the MARG method and an optical motion capture (OMC) system. The root mean square error (RMSE), mean absolute percentage error (MAPE), and Bland–Altman plots and limits of agreement were used to assess agreement between methods. Hip and knee ROM showed good to excellent agreement with the OMC system during the squat, box squat, and sandbag pickup (RMSE: 4.4–9.8°), while ankle ROM agreement ranged from good to unacceptable (RMSE: 2.7–7.2°). Unacceptable hip and knee ROM agreement was observed for the shuffle-walk and bear crawl (RMSE: 3.3–8.6°). The stride length, stride time, and stance time showed good to excellent agreement between methods (MAPE: (3.2 ± 2.8)%–(8.2 ± 7.9)%). Although the proposed MARG-based method is a valid means of assessing spatiotemporal and kinematic measures during various exercises, further development is required to assess the joint kinematics of small ROM, high velocity movements.

          Related collections

          Most cited references52

          • Record: found
          • Abstract: not found
          • Article: not found

          Nonlinear Complementary Filters on the Special Orthogonal Group

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Beyond statistical significance: clinical interpretation of rehabilitation research literature.

              Phil Page (2014)
              Evidence-based practice requires clinicians to stay current with the scientific literature. Unfortunately, rehabilitation professionals are often faced with research literature that is difficult to interpret clinically. Clinical research data is often analyzed with traditional statistical probability (p-values), which may not give rehabilitation professionals enough information to make clinical decisions. Statistically significant differences or outcomes simply address whether to accept or reject a null or directional hypothesis, without providing information on the magnitude or direction of the difference (treatment effect). To improve the interpretation of clinical significance in the rehabilitation literature, researchers commonly include more clinically-relevant information such as confidence intervals and effect sizes. It is important for clinicians to be able to interpret confidence intervals using effect sizes, minimal clinically important differences, and magnitude-based inferences. The purpose of this commentary is to discuss the different aspects of statistical analysis and determinations of clinical relevance in the literature, including validity, significance, effect, and confidence. Understanding these aspects of research will help practitioners better utilize the evidence to improve their clinical decision-making skills.
                Bookmark

                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                15 August 2020
                August 2020
                : 20
                : 16
                : 4586
                Affiliations
                [1 ]Faculty of Health Sciences and Medicine, Bond University, Gold Coast 4226, Australia; jkeogh@ 123456bond.edu.au (J.W.L.K.); alorimer@ 123456bond.edu.au (A.V.L.)
                [2 ]Sports Performance Research Institute New Zealand (SPRINZ), AUT Millennium Institute, AUT University, Auckland 0632, New Zealand
                [3 ]Cluster for Health Improvement, Faculty of Science, Health, Education and Engineering, University of Sunshine Coast, Sunshine Coast 4556, Australia
                [4 ]Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka 576104, India
                Author notes
                [* ]Correspondence: bhindle@ 123456bond.edu.au
                Author information
                https://orcid.org/0000-0001-9601-9985
                https://orcid.org/0000-0001-9851-1068
                Article
                sensors-20-04586
                10.3390/s20164586
                7472244
                32824216
                483b4b83-4c42-46bc-909b-89325d7df83a
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 22 July 2020
                : 13 August 2020
                Categories
                Article

                Biomedical engineering
                biomechanics,kinematics,spatiotemporal,gait,motion analysis,inertial sensors
                Biomedical engineering
                biomechanics, kinematics, spatiotemporal, gait, motion analysis, inertial sensors

                Comments

                Comment on this article