Activity Recognition for Ergonomics Assessment of Industrial Tasks with Automatic Feature Selection

Adrien Malaisé 1 Pauline Maurice 1 Francis Colas 1 Serena Ivaldi 1
1 LARSEN - Lifelong Autonomy and interaction skills for Robots in a Sensing ENvironment
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Abstract : In industry, ergonomic assessment is currently performed manually based on the identification of postures and actions by experts. We aim at proposing a system for automatic ergonomic assessment based on activity recognition. In this paper, we define a taxonomy of activities, composed of four levels, compatible with items evaluated in standard ergonomic worksheets. The proposed taxonomy is applied to learn activity recognition models based on Hidden Markov Models. We also identify dedicated sets of features to be used as input of the recognition models so as to maximize the recognition performance for each level of our taxonomy. We compare three feature selection methods to obtain these subsets. Data from 13 participants performing a series of tasks mimicking industrial tasks are collected to train and test the recognition module. Results show that the selected subsets allow us to successfully infer ergonomically relevant postures and actions.
Document type :
Journal articles
Complete list of metadatas

Cited literature [24 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01985013
Contributor : Adrien Malaisé <>
Submitted on : Thursday, January 17, 2019 - 3:11:13 PM
Last modification on : Thursday, February 7, 2019 - 5:16:19 PM

File

malaise_activity_ral.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01985013, version 1

Collections

Citation

Adrien Malaisé, Pauline Maurice, Francis Colas, Serena Ivaldi. Activity Recognition for Ergonomics Assessment of Industrial Tasks with Automatic Feature Selection. IEEE Robotics and Automation Letters, IEEE 2019. ⟨hal-01985013⟩

Share

Metrics

Record views

121

Files downloads

330