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      Development and evaluation of the ARM algorithm: A novel approach to quantify musculoskeletal disorder risk factors in manual wheelchair users in the real world

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          Abstract

          This study aimed to develop and evaluate the ARM (arm repetitive movement) algorithm using inertial measurement unit (IMU) data to assess repetitive arm motion in manual wheelchair (MWC) users in real-world settings. The algorithm was tested on community data from four MWC users with spinal cord injury and compared with video-based analysis. Additionally, the algorithm was applied to in-home and free-living environment data from two and sixteen MWC users, respectively, to assess its utility in quantifying differences across activities of daily living and between dominant and non-dominant arms. The ARM algorithm accurately estimated active and resting times (>98%) in the community and confirmed asymmetries between dominant and non-dominant arm usage in in-home and free-living environment data. Analysis of free-living environment data revealed that the total resting bout time was significantly longer (P = 0.049) and total active bout time was significantly shorter (P = 0.011) for the non-dominant arm. Analysis of active bouts longer than 10 seconds showed higher total time (P = 0.015), average duration (P = 0.026), and number of movement cycles per bout (P = 0.020) for the dominant side. These findings support the feasibility of using the IMU-based ARM algorithm to assess repetitive arm motion and monitor shoulder disorder risk factors in MWC users during daily activities.

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          Most cited references26

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          RULA: a survey method for the investigation of work-related upper limb disorders.

          RULA (rapid upper limb assessment) is a survey method developed for use in ergonomics investigations of workplaces where work-related upper limb disorders are reported. This tool requires no special equipment in providing a quick assessment of the postures of the neck, trunk and upper limbs along with muscle function and the external loads experienced by the body. A coding system is used to generate an action list which indicates the level of intervention required to reduce the risks of injury due to physical loading on the operator. It is of particular assistance in fulfilling the assessment requirements of both the European Community Directive (90/270/EEC) on the minimum safety and health requirements for work with display screen equipment and the UK Guidelines on the prevention of work-related upper limb disorders.
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            Rapid entire body assessment (REBA).

            This technical note details the preliminary stage in the development of a postural analysis tool, Rapid Entire Body Assessment (REBA). REBA has been developed to fill a perceived need for a practitioner's field tool, specifically designed to be sensitive to the type of unpredictable working postures found in health care and other service industries. A team of ergonomists, physiotherapists, occupational therapists and nurses collected and individually coded over 600 postural examples to produce a new tool incorporating dynamic and static postural loading factors, human-load interface (coupling), and a new concept of a gravity-assisted upper limb position. Initial reliability for inter-observer coding shows promise but further work is needed to establish the validity of the tool.
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              Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing.

              R Sabatini (2006)
              In this paper, a quaternion based extended Kalman filter (EKF) is developed for determining the orientation of a rigid body from the outputs of a sensor which is configured as the integration of a tri-axis gyro and an aiding system mechanized using a tri-axis accelerometer and a tri-axis magnetometer. The suggested applications are for studies in the field of human movement. In the proposed EKF, the quaternion associated with the body rotation is included in the state vector together with the bias of the aiding system sensors. Moreover, in addition to the in-line procedure of sensor bias compensation, the measurement noise covariance matrix is adapted, to guard against the effects which body motion and temporary magnetic disturbance may have on the reliability of measurements of gravity and earth's magnetic field, respectively. By computer simulations and experimental validation with human hand orientation motion signals, improvements in the accuracy of orientation estimates are demonstrated for the proposed EKF, as compared with filter implementations where either the in-line calibration procedure, the adaptive mechanism for weighting the measurements of the aiding system sensors, or both are not implemented.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SoftwareRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2 April 2024
                2024
                : 19
                : 4
                : e0300318
                Affiliations
                [1 ] Division of Health Care Delivery Research, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, United States of America
                [2 ] Department of Chemical and Biomedical Engineering, West Virginia University, Morgantown, West Virginia, Minnesota, United States of America
                [3 ] Department of Nutrition, Metabolism, & Rehabilitation Sciences, Center for Health Promotion, Performance, and Rehabilitation Research, The University of Texas Medical Branch, Galveston, Texas, United States of America
                Imperial College London, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                [¤]

                Current address: Department of Physical Medicine & Rehabilitation, Mayo Clinic, Rochester, Minnesota, United States of America

                Author information
                https://orcid.org/0000-0002-5379-1462
                https://orcid.org/0000-0002-8954-5415
                https://orcid.org/0009-0002-2991-7384
                https://orcid.org/0000-0003-1961-4195
                https://orcid.org/0000-0002-6500-6572
                Article
                PONE-D-23-29198
                10.1371/journal.pone.0300318
                10986926
                38564576
                c2423a04-c88e-4d52-ad43-500f7876e274
                © 2024 Jahanian et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 30 September 2023
                : 27 February 2024
                Page count
                Figures: 2, Tables: 7, Pages: 14
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100009633, Eunice Kennedy Shriver National Institute of Child Health and Human Development;
                Award ID: R01HD84423
                Award Recipient :
                This publication was made possible by funding from the National Institutes of Health (NIH; grant no. R01HD84423). NIH had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Body Limbs
                Arms
                Medicine and Health Sciences
                Anatomy
                Body Limbs
                Arms
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Shoulders
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Shoulders
                Biology and Life Sciences
                Bioengineering
                Biotechnology
                Medical Devices and Equipment
                Assistive Technologies
                Wheelchairs
                Engineering and Technology
                Bioengineering
                Biotechnology
                Medical Devices and Equipment
                Assistive Technologies
                Wheelchairs
                Medicine and Health Sciences
                Medical Devices and Equipment
                Assistive Technologies
                Wheelchairs
                Biology and Life Sciences
                Biomechanics
                Musculoskeletal Mechanics
                Biology and Life Sciences
                Physiology
                Muscle Physiology
                Musculoskeletal Mechanics
                Engineering and Technology
                Human Factors Engineering
                Ergonomics
                Engineering and Technology
                Electronics Engineering
                Electronics
                Accelerometers
                Custom metadata
                All relevant data are within the manuscript and its Supporting information files.

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