E. Schneider, X. Irastorza, M. Bakhuys-roozeboom, and I. Houtman, Osh in figures: occupational safety and health in the transport sector-an overview, 2010.

N. Vignais, M. Miezal, G. Bleser, K. Mura, D. Gorecky et al., Innovative system for real-time ergonomic feedback in industrial manufacturing, Applied ergonomics, vol.44, issue.4, pp.566-574, 2013.

S. Ivaldi, L. Fritzsche, J. Babic, F. Stulp, M. Damsgaard et al., Anticipatory models of human movements and dynamics: the roadmap of the andy project, DHM, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01539731

G. Li and P. Buckle, Current techniques for assessing physical exposure to work-related musculoskeletal risks, with emphasis on posture-based methods, Ergonomics, vol.42, issue.5, pp.674-695, 1999.

T. Bossomaier, A. G. Bruzzone, A. Cimino, F. Longo, and G. Mirabelli, Scientific approaches for the industrial workstations ergonomic design: A review, ECMS, pp.189-199, 2010.

A. Malaisé, P. Maurice, F. Colas, F. Charpillet, and S. Ivaldi, Activity recognition with multiple wearable sensors for industrial applications, 2018.

D. Roman-liu, Comparison of concepts in easy-to-use methods for msd risk assessment, Applied ergonomics, vol.45, issue.3, pp.420-427, 2014.

L. Mcatamney and E. N. Corlett, Rula: a survey method for the investigation of work-related upper limb disorders, Applied ergonomics, vol.24, pp.91-99, 1993.

S. Hignett and L. Mcatamney, Rapid entire body assessment, Handbook of Human Factors and Ergonomics Methods, pp.97-108, 2004.

E. N. Corlett and R. Bishop, A technique for assessing postural discomfort, Ergonomics, vol.19, issue.2, pp.175-182, 1976.

E. Occhipinti, Ocra: a concise index for the assessment of exposure to repetitive movements of the upper limbs, Ergonomics, vol.41, issue.9, pp.1290-1311, 1998.

K. Schaub, G. Caragnano, B. Britzke, and R. Bruder, The european assembly worksheet, TIES, vol.14, issue.6, pp.616-639, 2013.

W. Kim, M. Lorenzini, K. Kapicioglu, and A. Ajoudani, Ergotac: A tactile feedback interface for improving human ergonomics in workplaces, IEEE RA, 2018.

B. Busch, G. Maeda, Y. Mollard, M. Demangeat, and M. Lopes, Postural optimization for an ergonomic human-robot interaction, IROS, pp.2778-2785, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01629426

P. Plantard, H. P. Shum, A. Pierres, and F. Multon, Validation of an ergonomic assessment method using kinect data in real workplace conditions, Applied ergonomics, vol.65, pp.562-569, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01393066

A. Dubois and F. Charpillet, Human activities recognition with RGB-Depth camera using HMM, EMBC, pp.4666-4669, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00914319

J. Yamato, J. Ohya, and K. Ishii, Recognizing human action in time-sequential images using hidden markov model, CVPR, pp.379-385, 1992.

I. Guyon and A. Elisseeff, An introduction to variable and feature selection, Journal of machine learning research, vol.3, pp.1157-1182, 2003.

R. Kohavi and G. H. John, Wrappers for feature subset selection, Artificial intelligence, vol.97, issue.1-2, pp.273-324, 1997.

C. Mandery, M. Plappert, J. Borras, and T. Asfour, Dimensionality reduction for whole-body human motion recognition, FUSION, pp.355-362, 2016.

J. Li, K. Cheng, S. Wang, F. Morstatter, R. P. Trevino et al., Feature selection: A data perspective, ACM CSUR, vol.50, issue.6, p.94, 2017.

R. O. Duda, P. E. Hart, and D. G. Stork, Pattern classification, 2012.

O. Banos, J. Galvez, M. Damas, H. Pomares, and I. Rojas, Window size impact in human activity recognition, Sensors, vol.14, issue.4, pp.6474-6499, 2014.

L. Bao and S. S. Intille, Activity recognition from userannotated acceleration data, PerCom, pp.1-17, 2004.