A Simple Proposition for Improving Industrial Hygiene Air Sampling Methods

When conducting an exposure assessment, the primary goal of the industrial hygienist is to fully characterize the worker's exposure during a work shift to compare it with an occupational exposure limit. This applies regardless of the duration of the work activity as an activity that is relatively short in duration can still present exposure in excess of the occupational exposure limit even when normalized over an 8-hr shift. This goal, however, is often impeded by the specification of a minimum sample volume in the published sampling method, which may prevent the sample from being collected or submitted for analysis. Removing the specification of minimum sample volume (or adjusting it from a requirement to a recommendation), in contrast, allows for a broader assessment of jobs that consist of short-duration and high-exposure activities and also eliminates the unnecessary practice of running sampling pumps in clean air to collect a specified, minimum volume.

Automation of Workplace Lifting Hazard Assessment for Musculoskeletal Injury Prevention

OBJECTIVES: Existing methods for practically evaluating musculoskeletal exposures such as posture and repetition in workplace settings have limitations. We aimed to automate the estimation of parameters in the revised United States National Institute for Occupational Safety and Health (NIOSH) lifting equation, a standard manual observational tool used to evaluate back injury risk related to lifting in workplace settings, using depth camera (Microsoft Kinect) and skeleton algorithm technology. METHODS: A large dataset (approximately 22,000 frames, derived from six subjects) of simultaneous lifting and other motions recorded in a laboratory setting using the Kinect (Microsoft Corporation, Redmond, Washington, United States) and a standard optical motion capture system (Qualysis, Qualysis Motion Capture Systems, Qualysis AB, Sweden) was assembled. Error-correction regression models were developed to improve the accuracy of NIOSH lifting equation parameters estimated from the Kinect skeleton. Kinect-Qualysis errors were modelled using gradient boosted regression trees with a Huber loss function. Models were trained on data from all but one subject and tested on the excluded subject. Finally, models were tested on three lifting trials performed by subjects not involved in the generation of the model-building dataset. RESULTS: Error-correction appears to produce estimates for NIOSH lifting equation parameters that are more accurate than those derived from the Microsoft Kinect algorithm alone. Our error-correction models substantially decreased the variance of parameter errors. In general, the Kinect underestimated parameters, and modelling reduced this bias, particularly for more biased estimates. Use of the raw Kinect skeleton model tended to result in falsely high safe recommended weight limits of loads, whereas error-corrected models gave more conservative, protective estimates. CONCLUSIONS: Our results suggest that it may be possible to produce reasonable estimates of posture and temporal elements of tasks such as task frequency in an automated fashion, although these findings should be confirmed in a larger study. Further work is needed to incorporate force assessments and address workplace feasibility challenges. We anticipate that this approach could ultimately be used to perform large-scale musculoskeletal exposure assessment not only for research but also to provide real-time feedback to workers and employers during work method improvement activities and employee training.

Análise ergonômica do trabalho em unidades de beneficiamento de tomates de mesa: movimentação manual de cargas / Ergonomic work analyses method in fresh tomato packing houses: manual material handling

A movimentação manual de cargas (MMC) nas unidades de beneficiamento de tomates (UB) é a atividade laboral mais freqüente nas etapas do processo de beneficiamento. O objetivo deste estudo foi analisar, sob a ótica da ergonomia, as tarefas de MMC em seis UB de tomate de mesa do Estado de São Paulo. Foi aplicado o método da análise ergonômica do trabalho (AET) para conhecimento dos problemas associados à carga laboral. Nos postos de trabalho onde a MMC foi predominante, aplicou-se o método da equação do National Institute for Occupational Safety and Health (NIOSH) para determinar o Limite de Peso Recomendado e o método do Diagrama das Áreas Dolorosas para identificar as áreas do corpo dos trabalhadores que apresentam desconforto. Em todas os casos estudados, o peso real da carga movimentada manualmente superou o limite de peso recomendado pelo NIOSH.

The manual material handling (MMH) is the most frequent labor activity in tomato packing houses. The main goal of this paper was to analyze, under an ergonomic point of view, the MMH tasks in six fresh tomato packing houses. The ergonomic work analyses method was applied for an overall approach of work activities. The NIOSH equation was applied to calculate the recommended weight limit and a Body Discomfort Diagram was used to identify the painful body workers areas. In all cases, the actual load overcame the recommended weight limits by NIOSH.