Classification of body postures using smart workwear.

ABSTRACT:

Background

Despite advancing automation, employees in many industrial and service occupations still have to perform physically intensive work that may have negative effects on the health of the musculoskeletal system. For targeted preventive measures, precise knowledge of the work postures and movements performed is necessary.

Methods

Prototype smart work clothes equipped with 15 inertial sensors were used to record reference body postures of 20 subjects. These reference postures were used to create a software-based posture classifier according to the Ovako Working Posture Analysing System (OWAS) by means of an evolutionary training algorithm.

Results

A total of 111,275 posture shots were recorded and used for training the classifier. The results show that smart workw

SUBMITTER: Lins C 

PROVIDER: S-EPMC9580122 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature