The evaluation of the exposure to risk factors in workplaces and their subsequent redesign represent one of the practices to lessen the frequency of work-related musculoskeletal disorders. In this paper we present K2RULA, a semi-automatic RULA evaluation software based on the Microsoft Kinect v2 depth camera, aimed at detecting awkward postures in real time, but also in off-line analysis. We validated our tool with two experiments. In the first one, we compared the K2RULA grand-scores with those obtained with a reference optical motion capture system and we found a statistical perfect match according to the Landis and Koch scale (proportion agreement index = 0.97, k = 0.87). In the second experiment, we evaluated the agreement of the grand-scores returned by the proposed application with those obtained by a RULA expert rater, finding again a statistical perfect match (proportion agreement index = 0.96, k = 0.84), whereas a commercial software based on Kinect v1 sensor showed a lower agreement (proportion agreement index = 0.82, k = 0.34).

Real time RULA assessment using Kinect v2 sensor / Manghisi, Vito Modesto; Uva, Antonio Emmanuele; Fiorentino, Michele; Bevilacqua, Vitoantonio; Trotta, Gianpaolo Francesco; Monno, Giuseppe. - In: APPLIED ERGONOMICS. - ISSN 0003-6870. - 65:(2017), pp. 481-491. [10.1016/j.apergo.2017.02.015]

Real time RULA assessment using Kinect v2 sensor

MANGHISI, Vito Modesto;UVA, Antonio Emmanuele;FIORENTINO, Michele;BEVILACQUA, Vitoantonio;TROTTA, Gianpaolo Francesco;MONNO, Giuseppe
2017-01-01

Abstract

The evaluation of the exposure to risk factors in workplaces and their subsequent redesign represent one of the practices to lessen the frequency of work-related musculoskeletal disorders. In this paper we present K2RULA, a semi-automatic RULA evaluation software based on the Microsoft Kinect v2 depth camera, aimed at detecting awkward postures in real time, but also in off-line analysis. We validated our tool with two experiments. In the first one, we compared the K2RULA grand-scores with those obtained with a reference optical motion capture system and we found a statistical perfect match according to the Landis and Koch scale (proportion agreement index = 0.97, k = 0.87). In the second experiment, we evaluated the agreement of the grand-scores returned by the proposed application with those obtained by a RULA expert rater, finding again a statistical perfect match (proportion agreement index = 0.96, k = 0.84), whereas a commercial software based on Kinect v1 sensor showed a lower agreement (proportion agreement index = 0.82, k = 0.34).
2017
Real time RULA assessment using Kinect v2 sensor / Manghisi, Vito Modesto; Uva, Antonio Emmanuele; Fiorentino, Michele; Bevilacqua, Vitoantonio; Trotta, Gianpaolo Francesco; Monno, Giuseppe. - In: APPLIED ERGONOMICS. - ISSN 0003-6870. - 65:(2017), pp. 481-491. [10.1016/j.apergo.2017.02.015]
File in questo prodotto:
File Dimensione Formato  
s1 pre -2017-Real time RULA assessment.pdf

accesso aperto

Descrizione: preprint
Tipologia: Documento in Pre-print
Licenza: Creative commons
Dimensione 1.46 MB
Formato Adobe PDF
1.46 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/106712
Citazioni
  • Scopus 154
  • ???jsp.display-item.citation.isi??? 118
social impact