ABSTRACT
This article presents the new Italian database of physical agents, which is available at http://www.portaleagentifisici.it. It supports in risk assessment employers who have to comply with Italy's Legislative Decree 81/2008 (transposing into law European Union Directives 2003/10/EC, 2002/44/EC, 2004/40/EC and 2006/25/EC). The database currently contains measurements and declared European Community (EC) values from over 2540 machines; in particular, the database hosts data on mechanical vibration from over 1430 hand-held power tools (e.g., pneumatic and electric hammers, chainsaws, grinders, drills, sanders and saws) and from over 1020 whole-body machines (e.g., buses, fork lifts and wheel tractors). The database is continuously updated as soon as new experimental and declared data are acquired.
Subject(s)
Databases, Factual , Occupational Diseases/etiology , Occupational Exposure/statistics & numerical data , Electromagnetic Fields/adverse effects , European Union , Hand-Arm Vibration Syndrome/prevention & control , Humans , Internet , Italy , Lighting/adverse effects , Occupational Diseases/prevention & control , Occupational Exposure/prevention & control , Occupational Health , Protective Devices/classification , Risk Assessment , Vibration/adverse effectsABSTRACT
The central nervous system (CNS) controls movements and regulates joint stiffness with muscle co-activation, but until now, few studies have examined muscle pairs during running. This study aims to investigate differences in lower limb muscle coactivation during gait at different speeds, from walking to running. Nineteen healthy runners walked and ran at speeds ranging from 0.8 km/h to 9.3 km/h. Twelve lower limb muscles' co-activation was calculated using the time-varying multi-muscle co-activation function (TMCf) with global, flexor-extension, and rostro-caudal approaches. Spatiotemporal and kinematic parameters were also measured. We found that TMCf, spatiotemporal, and kinematic parameters were significantly affected by gait speed for all approaches. Significant differences were observed in the main parameters of each co-activation approach and in the spatiotemporal and kinematic parameters at the transition between walking and running. In particular, significant differences were observed in the global co-activation (CIglob, main effect F(1,17) = 641.04, p < 0.001; at the transition p < 0.001), the stride length (main effect F(1,17) = 253.03, p < 0.001; at the transition p < 0.001), the stride frequency (main effect F(1,17) = 714.22, p < 0.001; at the transition p < 0.001) and the Center of Mass displacement in the vertical (CoMy, main effect F(1,17) = 426.2, p < 0.001; at the transition p < 0.001) and medial-lateral (CoMz, main effect F(1,17) = 120.29 p < 0.001; at the transition p < 0.001) directions. Regarding the correlation analysis, the CoMy was positively correlated with a higher CIglob (r = 0.88, p < 0.001) and negatively correlated with Full Width at Half Maximum (FWHMglob, r = -0.83, p < 0.001), whereas the CoMz was positively correlated with the global Center of Activity (CoAglob, r = 0.97, p < 0.001). Positive and negative strong correlations were found between global co-activation parameters and center of mass displacements, as well as some spatiotemporal parameters, regardless of gait speed. Our findings suggest that walking and running have different co-activation patterns and kinematic characteristics, with the whole-limb stiffness exerted more synchronously and stably during running. The co-activation indexes and kinematic parameters could be the result of global co-activation, which is a sensory-control integration process used by the CNS to deal with more demanding and potentially unstable tasks like running.