ArticleApplied ergonomics2022
Classifying hazardous movements and loads during manual materials handling using accelerometers and instrumented insoles.
Article in Applied ergonomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Deep Learning Algorithms for Human Activity Recognition in Manual Material Handling Tasks.Sensors (Basel, Switzerland) · 2025Article
- Exploring the clinical utility of postural outcome tools for back and neck pain clinical outcomes: a systematic scoping review.F1000Research · 2025Article
- Criteria for Assessing Exposure to Biomechanical Risk Factors: A Research-to-Practice Guide-Part 1: General Issues and Manual Material Handling.Life (Basel, Switzerland) · 2024Review
- A Wearable Real-time Kinematic and Kinetic Measurement Sensor Setup for Human Locomotion.Wearable technologies · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Improper manual material handling (MMH) techniques are shown to lead to low back pain, the most common work-related musculoskeletal disorder. Due to the complex nature and variability of MMH and obtrusiveness and subjectiveness of existing hazard analysis methods, providing systematic, continuous, and automated risk assessment is challenging. We present a machine learning algorithm to detect and classify MMH tasks using minimally-intrusive instrumented insoles and chest-mounted accelerometers. Six participants performed standing, walking, lifting/lowering, carrying, side-to-side load transferring (i.e., 5.7 kg and 12.5 kg), and pushing/pulling. Lifting and carrying loads as well as hazardous behaviors (i.e., stooping, overextending and jerky lifting) were detected with 85.3%/81.5% average accuracies with/without chest accelerometer. The proposed system allows for continuous exposure assessment during MMH and provides objective data for use with analytical risk assessment models that can be used to increase workplace safety through exposure estimation.
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Registered trials
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