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Evaluating cognitive and physical work performance: A comparative study of an active and passive industrial back-support exoskeleton.

Authors :
Govaerts, Renée
Turcksin, Tom
Vanderborght, Bram
Roelands, Bart
Meeusen, Romain
De Pauw, Kevin
De Bock, Sander
Source :
Wearable Technologies; 2023, Vol. 4, p1-16, 16p
Publication Year :
2023

Abstract

Occupational back-support exoskeletons, categorized as active or passive, hold promise for mitigating work-related musculoskeletal disorders. However, their impact on combined physical and cognitive aspects of industrial work performance remains inadequately understood, especially regarding potential differences between exoskeleton categories. A randomized, counterbalanced cross-over study was conducted, comparing the active CrayX, passive Paexo Back, and a no exoskeleton condition. A 15-min dual task was used to simulate both cognitive and physical aspects of industrial work performance. Cognitive workload parameters included reaction time, accuracy, and subjective measures. Physical workload included movement duration, segmented in three phases: (1) walking to and grabbing the box, (2) picking up, carrying, and putting down the box, and (3) returning to the starting point. Comfort of both devices was also surveyed. The Paexo significantly increased movement duration in the first segment compared to NoExo (Paexo = 1.55 ± 0.19 s; NoExo = 1.32 ± 0.17 s; p < .01). Moreover, both the Paexo and CrayX increased movement duration for the third segment compared to NoExo (CrayX = 1.70 ± 0.27 s; Paexo = 1.74 ± 0.27 s, NoExo = 1.54 ± 0.23 s; p < .01). No significant impact on cognitive outcomes was observed. Movement Time 2 was not significantly affected by both exoskeletons. Results of the first movement segment suggest the Paexo may hinder trunk bending, favoring the active device for dynamic movements. Both devices may have contributed to a higher workload as the movement duration in the third segment increased compared to NoExo. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
26317176
Volume :
4
Database :
Complementary Index
Journal :
Wearable Technologies
Publication Type :
Academic Journal
Accession number :
176459312
Full Text :
https://doi.org/10.1017/wtc.2023.25