Jorge Alcaide-Marzal

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 cameras 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.

Innovation assessment in traditional industries. A proposal of aesthetic innovation indicators

Innovative activities are fundamental to the competitiveness strategies of the firms in a globalized market. Their assessment, using indicators such as those utilized in the Community Innovation Survey (CIS), shows significant sectoral dispersion. Traditional industries are in a weak position because the innovation they are involved in is mainly aesthetic, which is not really addressed in innovation surveys. In this work, we review the various criticisms levelled at existing indicators and propose some new indicators that would capture the types of innovations that are conducted by the traditional industries. This work is based on a study of the features of traditional industries and the concept of aesthetic novelty. The proposed indicators are tested in the Spanish footwear industry.

Solving facility layout problems with strict geometric constraints using a two-phase genetic algorithm

This article puts forward a two-phase genetic algorithm that is able to solve facility layout problems strictly respecting the geometric constraints imposed on activities. In the first phase the algorithm attempts to locate an optimum slicing tree to group the activities appropriately. In the second phase the layout is obtained from this tree. In order to assess the slicing trees in the first phase we propose an evaluation function able to predict if, by making the appropriate cuts, the tree structure is able to generate layouts that satisfy the geometric restrictions imposed on the facilities to be arranged, and to minimize the cost of transporting materials between the production activities. It also permits the determination of the most suitable aspect ratio of the layout zone in order to minimize non-compliance with the geometric restrictions. The algorithm and the method of calculating the indicator proposed in the evaluation function are described, and the results obtained in the experiments carried out are also given.

Slicing tree's geometric potential: an indicator for layout problems based on slicing tree structure

In this paper we propose an indicator to measure the capacity of a slicing tree to generate geometrically acceptable solutions for layout problems based on the slicing tree structure. This indicator can predict if, by making the appropriate cuts, the tree structure is able to generate layouts that satisfy the geometrical restrictions imposed on the items to be arranged. It also permits the determination of the most suitable aspect ratio of the layout zone in order to minimize non-compliance with the geometric restrictions. The method of calculating the indicator and its application to the facility layout problem are described, and the results obtained in the experiments carried out are also given.

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.

A computer based system to design expressive avatars

Abstract Avatars are used in different contexts and situations: e-commerce, e-therapy, virtual worlds, videogames, collaborative online design… In this context, a good design of an avatar may improve the user experience. The ability of controlling the way an avatar convey messages and emotions is capital. In this work, a procedure to design avatar faces capable of conveying to the observer the most suitable sensations according to a given context is developed. The proposed system is based on a combination of genetic algorithms and artificial neural networks whose training is based on perceptual human responses to a set of faces.