Auto-Calibrated Wearable System for Load Vertical Location Estimation During Manual Lifting

Lifting during manual material handling is a major cause of low-back pain (LBP). As an important risk factor that directly influences the risk of LBP, the Load vertical location (LVL) during lifting needs to be measured and controlled. However, existing solutions for LVL measurement are inefficient, inaccurate, and impractical for real-world workplace environments. To address these problems, an unobtrusive wearable system, including smart insoles and smart wristbands, was proposed to measure LVL accurately in workplace environments. Different from traditional methods, which rely on Inertial Measurement Unit (IMU) and suffer from integral drifting errors over time, a novel barometer-based LVL measurement method was proposed in this study. To correct environment-induced LVL measurement errors in the barometer-based method, a novel Known Vertical Location Update (KVLU) method was proposed. This method automatically calibrates the measured LVL using known wrist vertical location at reference points, which can be detected by the proposed wearable system during frequently-used working activities such as standing and walking. The proposed wearable system achieved a mean absolute error (MAE) of 5.12 cm and 5.68 cm in LVL measurement using personalized and generic reference points, respectively, which demonstrates its reliable performance for LVL estimation.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-01-01
DOI
https://doi.org/10.1109/jiot.2025.3605260
Citations
1
Primary Topic
Ergonomics and Musculoskeletal Disorders
Type
article
Field-Weighted Citation Impact
2.44
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article

Auto-Calibrated Wearable System for Load Vertical Location Estimation During Manual Lifting

Diliang Chen, Dain P. LaRoche, Sajay Arthanat, Nozhan Ghoreishi et al.
1 citations
IEEE Internet of Things Journal
Ergonomics and Musculoskeletal Disorders
2.44
article

Auto-Calibrated Wearable System for Load Vertical Location Estimation During Manual Lifting

Diliang Chen, Dain P. LaRoche, Sajay Arthanat, Nozhan Ghoreishi, John R. LaCourse
article en
1 citations

Abstract

Lifting during manual material handling is a major cause of low-back pain (LBP). As an important risk factor that directly influences the risk of LBP, the Load vertical location (LVL) during lifting needs to be measured and controlled. However, existing solutions for LVL measurement are inefficient, inaccurate, and impractical for real-world workplace environments. To address these problems, an unobtrusive wearable system, including smart insoles and smart wristbands, was proposed to measure LVL accurately in workplace environments. Different from traditional methods, which rely on Inertial Measurement Unit (IMU) and suffer from integral drifting errors over time, a novel barometer-based LVL measurement method was proposed in this study. To correct environment-induced LVL measurement errors in the barometer-based method, a novel Known Vertical Location Update (KVLU) method was proposed. This method automatically calibrates the measured LVL using known wrist vertical location at reference points, which can be detected by the proposed wearable system during frequently-used working activities such as standing and walking. The proposed wearable system achieved a mean absolute error (MAE) of 5.12 cm and 5.68 cm in LVL measurement using personalized and generic reference points, respectively, which demonstrates its reliable performance for LVL estimation.

IEEE Internet of Things Journal
University of New Hampshire (US)
Openalex Percentile: Top 10%
Ergonomics and Musculoskeletal Disorders
2.44
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