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A Multi-Parametric Wearable System to Monitor Neck Movements and Respiratory Frequency of Computer Workers.

Authors :
Presti, Daniela Lo
Carnevale, Arianna
D’Abbraccio, Jessica
Massari, Luca
Massaroni, Carlo
Sabbadini, Riccardo
Zaltieri, Martina
Di Tocco, Joshua
Bravi, Marco
Miccinilli, Sandra
Sterzi, Silvia
Longo, Umile G.
Denaro, Vincenzo
Caponero, Michele A.
Formica, Domenico
Oddo, Calogero M.
Schena, Emiliano
Source :
Sensors (14248220); 1/15/2020, Vol. 20 Issue 2, p1-17, 17p
Publication Year :
2020

Abstract

Musculoskeletal disorders are the most common form of occupational ill-health. Neck pain is one of the most prevalent musculoskeletal disorders experienced by computer workers. Wrong postural habits and non-compliance of the workstation to ergonomics guidelines are the leading causes of neck pain. These factors may also alter respiratory functions. Health and safety interventions can reduce neck pain and, more generally, the symptoms of musculoskeletal disorders and reduce the consequent economic burden. In this work, a multi-parametric wearable system based on two fiber Bragg grating sensors is proposed for monitoring neck movements and breathing activity of computer workers. The sensing elements were positioned on the neck, in the frontal and sagittal planes, to monitor: (i) flexion-extension and axial rotation repetitions, and (ii) respiratory frequency. In this pilot study, five volunteers were enrolled and performed five repetitions of both flexion-extension and axial rotation, and ten breaths of both quite breathing and tachypnea. Results showed the good performances of the proposed system in monitoring the aforementioned parameters when compared to optical reference systems. The wearable system is able to well-match the trend in time of the neck movements (both flexion-extension and axial rotation) and to estimate mean and breath-by-breath respiratory frequency values with percentage errors ≤6.09% and ≤1.90%, during quiet breathing and tachypnea, respectively. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
20
Issue :
2
Database :
Complementary Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
141552435
Full Text :
https://doi.org/10.3390/s20020536