Sara Grassi Pauletti

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In Contreras-Vidal and colleagues have shown the feasibility of inferring the linear and angular kinematics of treadmill walking from scalp EEG. Here, we apply a discrete approach to the same problem of decoding the human gait. By reducing the gait process ...

In this paper we present an efficient method for Content Based Image Retrieval (CBIR) of occluded images using DCT-phase. The proposed method utilizes a novel correlation metric for ternary-valued DCT-phase, as well as a region merging method to reconstruc ...

We propose a low complexity image recognition algorithm based on Content Based Image Retrieval (CBIR) suitable for handheld applications. The target application is an Alternative and Augmentative Communication (AAC) device used in speech rehabilitation and ...

We are developing an Alternative and Augmentative Communication (AAC) portable device called PictoBar which is used in speech rehabilitation therapy. PictoBar recognizes barcodes and images, such as pictograms and pictures. Then it plays a sound message as ...

We propose a fast and efficient method for Content Based Image Retrieval (CBIR) which uses color densities within concentric circular zones of the image, encompassing edge-pixels. This method is invariant to Rotation, Scale and Translation (RST). Small-siz ...

This paper describes the development of a sport watch, as well as the software and hardware required to design an integrated solution for getting feedback during and after walking and running activities. The developed system is autonomous, so that neither ...

Sara Grassi Pauletti

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Classification of stance and swing gait states during treadmill walking from non-invasive scalp electroencephalographic (EEG) signals

Retrieval of occluded images using DCT phase and region merging

Low complexity image recognition algorithm for handheld applications

Implementation of an image recognition algorithm on the DM6446 DaVinci Processor

Rotation, Scale and Translation invariant image retrieval method based on Circular Segmentation and Color Density

MEMS Inertial Motion Sensing Watch for Measuring Walking and Running Activities