Respiratory Inductance Plethysmography to Assess Fatigability during Repetitive Work

Sensors (Basel). 2022 Jun 2;22(11):4247. doi: 10.3390/s22114247.

Abstract

Cumulative fatigue during repetitive work is associated with occupational risk and productivity reduction. Usually, subjective measures or muscle activity are used for a cumulative evaluation; however, Industry 4.0 wearables allow overcoming the challenges observed in those methods. Thus, the aim of this study is to analyze alterations in respiratory inductance plethysmography (RIP) to measure the asynchrony between thorax and abdomen walls during repetitive work and its relationship with local fatigue. A total of 22 healthy participants (age: 27.0 ± 8.3 yrs; height: 1.72 ± 0.09 m; mass: 63.4 ± 12.9 kg) were recruited to perform a task that includes grabbing, moving, and placing a box in an upper and lower shelf. This task was repeated for 10 min in three trials with a fatigue protocol between them. Significant main effects were found from Baseline trial to the Fatigue trials (p < 0.001) for both RIP correlation and phase synchrony. Similar results were found for the activation amplitude of agonist muscle (p < 0.001), and to the muscle acting mainly as a joint stabilizer (p < 0.001). The latter showed a significant effect in predicting both RIP correlation and phase synchronization. Both RIP correlation and phase synchronization can be used for an overall fatigue assessment during repetitive work.

Keywords: EMG; RIP; fatigue; industry 4.0; occupational risk; operator 4.0; work.

MeSH terms

  • Adolescent
  • Adult
  • Fatigue / diagnosis
  • Humans
  • Plethysmography* / methods
  • Respiratory Rate*
  • Respiratory System
  • Thorax
  • Young Adult

Grants and funding

This work was supported by Project OPERATOR (NORTE01-0247-FEDER-045910), co-financed by the ERDF—European Regional Development Fund through the North Portugal Regional Operational Program and Lisbon Regional Operational Program and by the Portuguese Foundation for Science and Technology, under the MIT Portugal Program (2019 Open Call for Flagship projects).