ErgoExplorer: Interactive Ergonomic Risk Assessment from Video Collections

Ergonomic risk assessment is now, due to an increased awareness, carried out more often than in the past. The conventional risk assessment evaluation, based on expert-assisted observation of the workplaces and manually filling in score tables, is still predominant. Data analysis is usually done with a focus on critical moments, although without the support of contextual information and changes over time. In this paper we introduce ErgoExplorer, a system for the interactive visual analysis of risk assessment data. In contrast to the current practice, we focus on data that span across multiple actions and multiple workers while keeping all contextual information. Data is automatically extracted from video streams. Based on carefully investigated analysis tasks, we introduce new views and their corresponding interactions. These views also incorporate domain-specific score tables to guarantee an easy adoption by domain experts. All views are integrated into ErgoExplorer, which relies on coordinated multiple views to facilitate analysis through interaction. ErgoExplorer makes it possible for the first time to examine complex relationships between risk assessments of individual body parts over long sessions that span multiple operations. The newly introduced approach supports analysis and exploration at several levels of detail, ranging from a general overview, down to inspecting individual frames in the video stream, if necessary. We illustrate the usefulness of the newly proposed approach applying it to several datasets.Fil: Massiris, Manlio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Rados, Sanjin. VRVis Research Center In Vienna, Austria; AustriaFil: Matkovic, Kresimir. VRVis Research Center; AustriaFil: Groller, M. Eduard. Technische Universitat Wien; AustriaFil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentin

Gestión y evaluación de la seguridad en el trabajo mediante técnicas de visión artificial

Programa de Doctorado en Tecnologías Informáticas.La OMS recomienda efectuar evaluaciones de riesgos laborales (ERL) para disminuir las posibilidades de ocurrencia de accidentes y/o dolencias musculoesqueléticas relacionadas con el trabajo. Estas ERL tienen como objetivo adaptar las condiciones de trabajo a la capacidad de los trabajadores y proponer mejoras cuando se hallen riesgos para su salud. Las ERL se llevan a cabo principalmente mediante la observación in-situ por parte de ergonomistas. Sin embargo, es sabido que los trabajadores alteran su desempeño habitual al sentirse observados, aunado al efecto inevitable de la subjetividad intra- e inter-observador. Así, factores diferenciales como el entorno de observación, el medio de observación, la formación y la experiencia afectan a la reproducibilidad y la trazabilidad de las ERL tradicionales. En esta tesis doctoral se propone investigar y testear nuevas tecnologías basadas en Inteligencia Artificial (IA) aplicadas en un Sistema de Visión por Computadora (CVS) para obtener ERL automatizadas que reduzcan los factores limitativos anteriores. Como resultado, se ha demostrado en el laboratorio, en simulaciones y en entornos laborales reales que estos CVS inteligentes pueden ser entrenados y luego utilizados para el monitoreo de acciones que pueden generar lesiones en los trabajadores. Concretamente, se han diseñado y probado métodos basados en IA en el diseño de CVS para la detección automática de los usos adecuados del equipo de protección personal (EPP), así como para la supervisión automatizada de posibles riesgos musculoesqueléticos relacionados con el trabajo, ambos enmarcados en los procesos de digitalización del entorno de laboral planteada por la Industria-4.0.The WHO recommends performing occupational risk assessments (ORAs) to reduce the chances of accidents and/or work-related musculoskeletal disorders. The purpose of these ORAs is to adapt working conditions to workers' capabilities, and to propose improvements when occupational health risks are found. ORAs are mainly carried out through on-site observation by ergonomists. However, it is known that workers alter their usual performance when they feel observed, added to the inevitable effect of intra- and inter-observer subjectivity. Thus, differential factors such as observation environment, observation medium, training and experience affect the reproducibility and traceability of traditional ORAs. In this doctoral thesis we propose to investigate, and test new technologies based on Artificial Intelligence (AI) applied in a Computer Vision System (CVS) to obtain automated ORAs that reduce the above limiting factors. As a result, it has been demonstrated in the laboratory, in simulations and in real work environments that these intelligent CVS can be trained and then used for monitoring actions that can generate injuries in workers. Specifically, AI-based methods have been designed and tested in the design of CVS for the automatic detection of appropriate uses of personal protective equipment (PPE), as well as for the automated monitoring of possible work-related musculoskeletal risks, both framed in the processes of digitization of the work environment raised by Industry-4.0

Detection of Personal Protection Equipment Using the Yolo Convolutional Neural Network

[Resumen] En un número creciente de entornos de trabajo está tornándose obligatorio el uso de equipos de protección personal, debido a que son la última barrera para detener situaciones potenciales de riesgo físico para el trabajador. Eso determina que controlar en forma periódica y fehaciente el cumplimiento de las normas de seguridad laboral sea una tarea demandante, por lo cual el monitoreo no supervisado representa una solución de alto impacto para la seguridad industrial. El presente artículo propone utilizar visión artificial como alternativa cuantitativa para monitorear la utilización de equipo de protección personal. Se entrenó la red neuronal YOLO con la intención de detectar guantes, cascos, ropa de alta visibilidad y a los trabajadores con un dataset creado a partir de videos generados utilizando cámaras deportivas. Con el sistema entrenado, se presenta un análisis de caso in the open con un video grabado con cámara deportiva sujeta al casco de un trabajador metalúrgico en el sector de la construcción. Los resultados son promisorios y muestran que la estrategia planteada es adecuada para llegar a una solución implantable en ambientes de trabajo.[Abstract] In an increasing number of working environments, the use of personal protective equipment is becoming mandatory, since they are the last barrier to stop potential situations of physical risk for the worker. This means that periodically and reliably monitoring compliance with labor safety standards is a demanding task, which is why unsupervised monitoring represents a high impact solution for safety. This article proposes using artificial visión as a quantitative alternative to monitor the use of personal protective equipment. The YOLO neural network was trained with the intention of detecting gloves, hard hats, high visibility suits and workers with a dataset created from videos generated using sports cameras. With the trained system, an in-theopen case analysis is presented with a video recorded with a sports camera attached to the helmet of a metallurgical worker in a real construction site. The results are promising and show that the proposed strategy is adequate as implantable solution for these work environments

Hand Anthropometry of Colombian Caribbean College Students Using Software Based Method

A hand anthropometric characterization was made in the Colombian Caribbean Coast out of a sample of 41 males and females from Universidad del Norte. The measurements were taken by using a computer tool that was developed and validated with the traditional manual method. This research shows comparisons among the anthropometric parameters of different regions of the country and foreign countries. It also includes the estimation of the circumference of the fingers through a novel statistical approach. Results confirm the predicted diversity of the measurements within the country and abroad.</p

Ergonomic risk assessment based on computer vision and machine learning

We develop a novel method that performs accurate ergonomic risk assessment, automatically computing Rapid Upper Limb Assessment (RULA) scores from snapshots or digital video using computer vision and machine learning techniques. Our method overcomes the limitations in recent developments based on computer vision or in wearable measurement sensors, being able to perform unsupervised assessment handling multiple workers simultaneously, even under sub-optimal viewing conditions (e.g., poor illumination, occlusions, and unstable camera views). The processing workflow uses open-source neural networks to detect the workers’ skeletons, after which their body-joint positions and angles are inferred, with which RULA scores are computed. The method was tested with computer-generated, controlled real-world image datasets, and with freely available videos taken in outdoor working scenarios. The computed RULA scores were in close agreement with the assessments of seven specialists in the field, achieving a Cohen´s κ over 0.6 in most real-world experiments.Fil: Massiris Fernández, Manlio. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; ArgentinaFil: Fernández, Hernán Álvaro. Universidad de Extremadura; EspañaFil: Bajo, Juan Miguel. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentin

Convergent validity of an application for hand anthropometric measurement

There is a need to know the anthropometric parameters of each population to improve the ergonomic design of tools, workstations and personal protective equipment. In their regular work, humans use their hands to develop their activities, and the required equipment should match with the physical dimensions of the workers. The traditional manual method for measuring takes a long time because of the number of measures and the training of the measurer, who has to first learn how to take each measure, which is why the objective of the software is to diminish the time employed in the taking of the data by systemizing the process. This paper shows a compilation of 25 hand anthropometric measurements from a sample of 41 subjects from the Colombian Caribbean Coast. To take the measures, software was developed and validated with manually taken measures using the t-test for each dimension. The results showed that there was no significant difference between the two methods, which proves the precision of the software. The gather of more data employing the software may represent a reliable normative data set of the hand measurements.</p

Insecticidal application of essential oils loaded polymeric nanoparticles to control German cockroach: Design, characterization and lethal/sublethal effects

Essential oils (EO) from peppermint, palmarosa, geranium, lavender and rosemary were tested against the German cockroach, Blatella germanica L. (Blattaria: Blatellidae). Peppermint and palmarosa oils were the most effective and were included in a polyethylene glycol 6000 matrix to obtain EO loaded polymeric nanoparticles (EOPN). The physicochemical analyses indicated that, at 7 days postformulation, peppermint EOPN had sizes of 380 nm, the loading efficiency (LE) was 72.25% and the polydispersity index (PDI) was >0.4 (polydisperse sample). Palmarosa EOPN had sizes of 191 nm; LE was 89.75% and PDI was <0.25 (monodisperse sample). Peppermint and palmarosa EOPN enhanced the lethal and sublethal effects of the EO on B. germanica. These results suggest that the newly developed nanoinsecticides could be successfully used to control German cockroach.Fil: Yeguerman, Cristhian Alan. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Laboratorio de Zoología de Invertebrados II; ArgentinaFil: Jesser, Emiliano Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Laboratorio de Zoología de Invertebrados II; ArgentinaFil: Massiris, Manlio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Murray, Ana Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Werdin Gonzalez, Jorge Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentin

Essential oils loaded on polymeric nanoparticles: bioefficacy against economic and medical insect pests and risk evaluation on terrestrial and aquatic non-target organisms

This paper introduces the lethal, sublethal, and ecotoxic effects of peppermint and palmarosa essential oils (EOs) and their polymeric nanoparticles (PNs). The physicochemical analyses indicated that peppermint PNs were polydisperse (PDI > 0.4) with sizes of 381 nm and loading efficiency (LE) of 70.3%, whereas palmarosa PNs were monodisperse (PDI < 0.25) with sizes of 191 nm and LE of 89.7%. EOs and their PNs were evaluated on the adults of rice weevil (Sitophilus oryzae L.) and cigarette beetle (Lasioderma serricorne F.) and the larvae of Culex pipiens pipiens Say. On S. oryzae and L. serricorne, PNs increased EOs’ lethal activity, extended repellent effects for 84 h, and also modified behavioral variables during 24 h. Moreover, EOs and PNs generated toxic effects against C. pipiens pipiens. On the other hand, peppermint and palmarosa EOs and their PNs were not toxic to terrestrial non-target organisms, larvae of mealworm (Tenebrio molitor L.), and nymphs of orange-spotted cockroach (Blaptica dubia S.). In addition, PNs were slightly toxic to aquatic non-target organisms, such as brine shrimp (Artemia salina L.). Therefore, these results show that PNs are a novel and eco-friendly formulation to control insect pests.Fil: Yeguerman, Cristhian Alan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; ArgentinaFil: Urrutia, Rodrigo Iñaki. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; ArgentinaFil: Jesser, Emiliano Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: Massiris, Manlio. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Delrieux, Claudio Augusto. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Murray, Ana Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Werdin Gonzalez, Jorge Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; Argentin