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dc.contributor.authorKhaksar, Siavash
dc.contributor.authorPieters, Stefanie
dc.contributor.authorBorazjani, Bita
dc.contributor.authorHyde, Joshua
dc.contributor.authorBooker, Harrison
dc.contributor.authorKhokhar, Adil
dc.contributor.authorMurray, Iain
dc.contributor.authorCampbell, Amity
dc.contributor.editorPassaro, Vittorio
dc.date.accessioned2022-12-08T10:15:18Z
dc.date.available2022-12-08T10:15:18Z
dc.date.issued2022
dc.identifier.citationKhaksar, S. and Pieters, S. and Borazjani, B. and Hyde, J. and Booker, H. and Khokhar, A. and Murray, I. et al. 2022. Posture Monitoring and Correction Exercises for Workers in Hostile Environments Utilizing Non-Invasive Sensors: Algorithm Development and Validation. MDPI Sensors. 22 (24): 9618.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/89782
dc.identifier.doi10.3390/s22249618
dc.description.abstract

Personal protective equipment (PPE) is an essential key factor in standardizing safety within the workplace. Harsh working environments with long working hours can cause stress on the human body that may lead to musculoskeletal disorder (MSD). MSD refers to injuries that impact the muscles, nerves, joints, and many other human body areas. Most work-related MSD results from hazardous manual tasks involving repetitive, sustained force, or repetitive movements in awkward postures. This paper presents collaborative research from the School of Electrical Engineering and School of Allied Health at Curtin University. The main objective was to develop a framework for posture correction exercises for workers in hostile environments, utilizing inertial measurement units (IMU). The developed system uses IMUs to record the head, back, and pelvis movements of a healthy participant without MSD and determine the range of motion of each joint. A simulation was developed to analyze the participant’s posture to determine whether the posture present would pose an increased risk of MSD with limits to a range of movement set based on the literature. When compared to measurements made by a goniometer, the body movement recorded 94% accuracy and the wrist movement recorded 96% accuracy.

dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titlePosture Monitoring and Correction Exercises for Workers in Hostile Environments Utilizing Non-Invasive Sensors: Algorithm Development and Validation
dc.typeJournal Article
dcterms.source.volume22
dcterms.source.number9618
dcterms.source.number24
dcterms.source.titleMDPI Sensors
dc.date.updated2022-12-08T10:15:12Z
curtin.departmentSchool of Elec Eng, Comp and Math Sci (EECMS)
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidKhaksar, Siavash [0000-0002-1944-1418]
curtin.contributor.orcidHyde, Joshua [0000-0002-8568-9876]
curtin.contributor.orcidMurray, Iain [0000-0003-1840-9624]


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