Effects of Using Immersive Media on the Effectiveness of Training to Prevent Ergonomics Risks.

In this work, the effects of using immersive media such as virtual reality on the performance of training programs to avoid ergonomics risks are analyzed. The advance of technology has made it possible to use low-cost portable devices able to generate highly immersive experiences in training programs. The effects of using this kind of device in training programs have been studied in several fields such as industrial security, medicine and surgery, rehabilitation, or construction. However, there is very little research on the effects of using immersive media in training workers to avoid ergonomics risk factors. In this study, we compare the effects of using traditional and immersive media in a training program to avoid three common ergonomics risk factors in industrial environments. Our results showed that using immersive media increases the participant's engagement during the training. In the same way, the learning contents are perceived as more interesting and useful and are better remembered over time, leading to an increased perception of the ergonomics risks among workers. However, we found that little training was finally transferred to the workplace three months after the training session.

User-interfaces layout optimization using eye-tracking, mouse movements and genetic algorithms.

Establishing the best layout configuration for software-generated interfaces and control panels is a complex problem when they include many controls and indicators. Several methods have been developed for arranging the interface elements; however, the results are usually conceptual designs that must be manually adjusted to obtain layouts valid for real situations. Based on these considerations, in this work we propose a new automatized procedure to obtain optimal layouts for software-based interfaces. Eye-tracking and mouse-tracking data collected during the use of the interface is used to obtain the best configuration for its elements. The solutions are generated using a slicing-trees based genetic algorithm. This algorithm is able to obtain really applicable configurations that respect the geometrical restrictions of elements in the interface. Results show that this procedure increases effectiveness, efficiency and satisfaction of the users when they interact with the obtained interfaces.

Errors Using Observational Methods for Ergonomics Assessment in Real Practice.

OBJECTIVE: The degree in which practitioners use the observational methods for musculoskeletal disorder risks assessment correctly was evaluated. BACKGROUND: Ergonomics assessment is a key issue for the prevention and reduction of work-related musculoskeletal disorders in workplaces. Observational assessment methods appear to be better matched to the needs of practitioners than direct measurement methods, and for this reason, they are the most widely used techniques in real work situations. Despite the simplicity of observational methods, those responsible for assessing risks using these techniques should have some experience and know-how in order to be able to use them correctly. METHOD: We analyzed 442 risk assessments of actual jobs carried out by 290 professionals from 20 countries to determine their reliability. RESULTS: The results show that approximately 30% of the assessments performed by practitioners had errors. In 13% of the assessments, the errors were severe and completely invalidated the results of the evaluation. CONCLUSION: Despite the simplicity of observational method, approximately 1 out of 3 assessments conducted by practitioners in actual work situations do not adequately evaluate the level of potential musculoskeletal disorder risks. APPLICATION: This study reveals a problem that suggests greater effort is needed to ensure that practitioners possess better knowledge of the techniques used to assess work-related musculoskeletal disorder risks and that laws and regulations should be stricter as regards qualifications and skills required by professionals.

Using Kinect™ sensor in observational methods for assessing postures at work.

This paper examines the potential use of Kinect™ range sensor in observational methods for assessing postural loads. Range sensors can detect the position of the joints at high sampling rates without attaching sensors or markers directly to the subject under study. First, a computerized OWAS ergonomic assessment system was implemented to permit the data acquisition from Kinect™ and data processing in order to identify the risk level of each recorded postures. Output data were compared with the results provided by human observers, and were used to determine the influence of the sensor view angle relative to the worker. The tests show high inter-method agreement in the classification of risk categories (Proportion agreement index = 0.89 κ = 0.83) when the tracked subject is facing the sensor. The camera's point of view relative to the position of the tracked subject significantly affects the correct classification of the postures. Although the results are promising, some aspects involved in the use of low-cost range sensors should be further studied for their use in real environments.