Smart rehabilitation

This thesis is born from a collaboration project between the HEIG-VD and the CHUV hospital in Lausanne, Switzerland. We study the problem of human grasp recognition from first-person RGB video input data. Grasping is the action of seizing and holding firmly an object and there exist many different types. The objective is to use grasp recognition for automating the monitoring of the rehabilitation sessions of patients with upper-limb neurological disorders. We compared three different approaches based on Deep Learning. Firstly, a naive image model that is trained with the entire images. Secondly, a video model, so apart from the spatial features it also takes advantage of the temporal dimension. Lastly, an image model that is trained with images cropped around the hands, so it focuses only on the part that determines the grasp. We used the Yale Grasping Dataset for training the models. To enhance the interpretability of the results we proposed a coarse-grained grasp grouping based on the Feix grasp taxonomy. We also captured our own small first-person video grasp dataset to test the applicability of the models to our setup, which differs from the training dataset in the camera location and angle. Considering the intrinsic challenges of the data such as the frequent hand-object occlusions or the dataset difficulties like its real-world setting and the low video quality, the results are relatively good. Nevertheless, they are insufficient for deploying a satisfactory system at the hospital and remark the difficulty of grasp recognition from just egocentric RGB data. It would be interesting to further research other data modalities such as depth data or to study the problem from the perspective of hand pose estimation and object detection. It is also clear that the field lacks a more modern and large dataset

Instalación eléctrica de un complejo de naves industriales

El presente proyecto trata de las instalaciones de un edificio destinado a naves industriales con vistas a su alquiler en un futuro como naves destinadas a almacenaje, dado esto se realizarán las instalaciones pensando en que dichas naves serán alquiladas por empresas dedicadas a depósitos y almacenajes. Las instalaciones a realizar serán las dedicadas a la media tensión (centro de transformación que dará servicio a las cuatro naves industriales, la referente a la instalación eléctrica de las naves dotándolas de alumbrado y tomas de corriente, la referente a la protección contra incendios dotando a las naves con bocas de incendio equipadas y sistemas de detección de incendios