title: OCRA: a concise index for the assessment of exposure to repetitive movements of the upper limbs.
abstract: In the light of data and speculation contained in the literature, and based on procedures illustrated in a previous research project in which the author described and evaluated occupational risk factors associated with work-related musculoskeletal disorders of the upper limbs (WMSDs), this paper proposes a method for calculating a concise index of exposure to repetitive movements of the upper limbs. The proposal, which still has to be substantiated and validated by further studies and applications, is conceptually based on the procedure recommended by the NIOSH for calculating the Lifting Index in manual load handling activities. The concise exposure index (OCRA index) in this case is based on the relationship between the daily number of actions actually performed by the upper limbs in repetitive tasks, and the corresponding number of recommended actions. The latter are calculated on the basis of a constant (30 actions per minute), which represents the action frequency factor; it is valid--hypothetically--under so-called optimal conditions; the constant is diminished case by case (using appropriate factors) as a function of the presence and characteristics of the other risk factors (force, posture, additional elements, recovery periods). Although still experimental, the exposure index can be used to obtain an integrated and concise assessment of the various risk factors analysed and to classify occupational scenarios featuring significant and diversified exposure to such risk factors.
authors.affiliation: EPM Research Unit, Milan, Italy.
authors.forename: E
authors.initials: E
authors.lastname: Occhipinti
mesh_terms: D001132:Arm / Q000502:physiology*; D001696:Biomechanical Phenomena; D006804:Ergonomics; D006801:Humans; D008962:Models, Theoretical; D009068:Movement / Q000502:physiology*; D009140:Musculoskeletal Diseases / Q000503:physiopathology; D016272:Occupational Health; D012307:Risk Factors; D013647:Task Performance and Analysis