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.

Using RGB-D sensors and evolutionary algorithms for the optimization of workstation layouts.

RGB-D sensors can collect postural data in an automatized way. However, the application of these devices in real work environments requires overcoming problems such as lack of accuracy or body parts' occlusion. This work presents the use of RGB-D sensors and genetic algorithms for the optimization of workstation layouts. RGB-D sensors are used to capture workers' movements when they reach objects on workbenches. Collected data are then used to optimize workstation layout by means of genetic algorithms considering multiple ergonomic criteria. Results show that typical drawbacks of using RGB-D sensors for body tracking are not a problem for this application, and that the combination with intelligent algorithms can automatize the layout design process. The procedure described can be used to automatically suggest new layouts when workers or processes of production change, to adapt layouts to specific workers based on their ways to do the tasks, or to obtain layouts simultaneously optimized for several production processes.

Influences on the use of observational methods by practitioners when identifying risk factors in physical work.

Most observational methods for musculoskeletal disorder risk assessment have been developed by researchers to be applied in specific situations, and practitioners could find difficulties in their use in real-work conditions. The main objective of this study was to identify the factors which have an influence on how useful the observational techniques are perceived to be by practitioners and to what extent these factors influence their perception. A survey was conducted on practitioners regarding the problems normally encountered when implementing these methods, as well as the perceived overall utility of these techniques. The results show that practitioners place particular importance on the support the methods provide in making decisions regarding changes in work systems and how applicable they are to different types of jobs. The results of this study can serve as guide to researchers for the development of new assessment techniques that are more useful and applicable in real-work situations.