How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor Signals
Low back disorders (LBDs) are a leading occupational health issue. Wearable sensors, such as inertial measurement units (IMUs) and/or pressure insoles, could automate and enhance the ergonomic assessment of LBD risks during material handling. However, much remains unknown about which sensor signals...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/4/2064 |
| _version_ | 1797618281440346112 |
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| author | Cameron A. Nurse Laura Jade Elstub Peter Volgyesi Karl E. Zelik |
| author_facet | Cameron A. Nurse Laura Jade Elstub Peter Volgyesi Karl E. Zelik |
| author_sort | Cameron A. Nurse |
| collection | DOAJ |
| description | Low back disorders (LBDs) are a leading occupational health issue. Wearable sensors, such as inertial measurement units (IMUs) and/or pressure insoles, could automate and enhance the ergonomic assessment of LBD risks during material handling. However, much remains unknown about which sensor signals to use and how accurately sensors can estimate injury risk. The objective of this study was to address two open questions: (1) How accurately can we estimate LBD risk when combining trunk motion and under-the-foot force data (simulating a trunk IMU and pressure insoles used together)? (2) How much greater is this risk assessment accuracy than using only trunk motion (simulating a trunk IMU alone)? We developed a data-driven simulation using randomized lifting tasks, machine learning algorithms, and a validated ergonomic assessment tool. We found that trunk motion-based estimates of LBD risk were not strongly correlated (r range: 0.20–0.56) with ground truth LBD risk, but adding under-the-foot force data yielded strongly correlated LBD risk estimates (r range: 0.93–0.98). These results raise questions about the adequacy of a single IMU for LBD risk assessment during material handling but suggest that combining an IMU on the trunk and pressure insoles with trained algorithms may be able to accurately assess risks. |
| first_indexed | 2024-03-11T08:10:51Z |
| format | Article |
| id | doaj.art-6f3cc3f6dcce47719b57c36108eb63f4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T08:10:51Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6f3cc3f6dcce47719b57c36108eb63f42023-11-16T23:09:51ZengMDPI AGSensors1424-82202023-02-01234206410.3390/s23042064How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor SignalsCameron A. Nurse0Laura Jade Elstub1Peter Volgyesi2Karl E. Zelik3Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37212, USADepartment of Mechanical Engineering, Vanderbilt University, Nashville, TN 37212, USAInstitute for Software Integrated Systems, Vanderbilt University, Nashville, TN 37212, USADepartment of Mechanical Engineering, Vanderbilt University, Nashville, TN 37212, USALow back disorders (LBDs) are a leading occupational health issue. Wearable sensors, such as inertial measurement units (IMUs) and/or pressure insoles, could automate and enhance the ergonomic assessment of LBD risks during material handling. However, much remains unknown about which sensor signals to use and how accurately sensors can estimate injury risk. The objective of this study was to address two open questions: (1) How accurately can we estimate LBD risk when combining trunk motion and under-the-foot force data (simulating a trunk IMU and pressure insoles used together)? (2) How much greater is this risk assessment accuracy than using only trunk motion (simulating a trunk IMU alone)? We developed a data-driven simulation using randomized lifting tasks, machine learning algorithms, and a validated ergonomic assessment tool. We found that trunk motion-based estimates of LBD risk were not strongly correlated (r range: 0.20–0.56) with ground truth LBD risk, but adding under-the-foot force data yielded strongly correlated LBD risk estimates (r range: 0.93–0.98). These results raise questions about the adequacy of a single IMU for LBD risk assessment during material handling but suggest that combining an IMU on the trunk and pressure insoles with trained algorithms may be able to accurately assess risks.https://www.mdpi.com/1424-8220/23/4/2064risk assessmentlifting biomechanicsergonomics overexertion injurieswork-related musculoskeletal disorders |
| spellingShingle | Cameron A. Nurse Laura Jade Elstub Peter Volgyesi Karl E. Zelik How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor Signals Sensors risk assessment lifting biomechanics ergonomics overexertion injuries work-related musculoskeletal disorders |
| title | How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor Signals |
| title_full | How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor Signals |
| title_fullStr | How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor Signals |
| title_full_unstemmed | How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor Signals |
| title_short | How Accurately Can Wearable Sensors Assess Low Back Disorder Risks during Material Handling? Exploring the Fundamental Capabilities and Limitations of Different Sensor Signals |
| title_sort | how accurately can wearable sensors assess low back disorder risks during material handling exploring the fundamental capabilities and limitations of different sensor signals |
| topic | risk assessment lifting biomechanics ergonomics overexertion injuries work-related musculoskeletal disorders |
| url | https://www.mdpi.com/1424-8220/23/4/2064 |
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