RIZZOTTI-KADDOURI, A., KUNZE, M., JEANNERET, L., et al. Learning from Demonstration for Collaborative Robots. Automation, Robotics & Communications for Industry 4.0, 2021, p. 45.
ALBERTETTI, Fabrizio, SIMALASTAR, Alena, et RIZZOTTI-KADDOURI, Aıcha. Stress Detection with Deep Learning Approaches Using Physiological Signals. In : IoT Technologies for HealthCare: 7th EAI International Conference, HealthyIoT 2020, Viana do Castelo, Portugal, December 3, 2020, Proceedings. Springer Nature. p. 95.
FREIBURGHAUS, Jonas, RIZZOTTI-KADDOURI, Aıcha, et ALBERTETTI, Fabrizio. A Deep Learning Approach for Blood Glucose Prediction of Type 1 Diabetes.
LD4Robots : Learning from Demonstration for collaborative Robots,The goal of this project is to design and prototype a learning system by imitation of a collaborative robot with industrial scenarios. The particularity of this project is the use of two modalities of capture of gestures and human movements, one based on a multi-channel vision system and the other on an inertial system. The transformation of captured gestures and movements is ensured by an expert system to be developed in the framework of the project.
AvalGlyc’project: A collaboration with the endocrinology and diabetology unit of CHUV, the goal in this project is to develop a system of POINT-OF-CARE type able to diagnose physiological parameters and glycemic levels for the type 1 diabetes patients, in order to predict, in near real-time, the future glucose levels. Our methods involve non-invasive measurements of physiological parameters that will be performed by use of wearable devices and biosensors.
DESY'project: The goal of this project is to develop a system able to quantitatively evaluate stress levels in non-invasive and continuous manner by means of wearable devices and biosensors. The system should inform a user about their stress level in an adequate manner
SelfData ‘project : The goal of this project is to develop a new method of collecting real and dynamic data, in the field of type I diabetes in adolescents, and to find the emotional indicators to analyze the patient's condition using the biosensors signals.
EL MALIKI, Tewfiq et RIZZOTTI-KADDOURI, Aïcha. Energy-aware Security Adaptation in Ubiquitous Mobile Network.in : SECURWARE 2016 The Tenth International Conference on Emerging Security Information, Systems and Technologies ISBN: 978-1-61208-493-0 July 24 - 28, 2016 Nice, France
MUCO’project: The goal of this project is to provide children with cystic fibrosis (or cystic fibrosis - Cystic Fibrosis - CF) with a smart sensor and a generic gaming platform and a serious games library allowing them to do their daily breathing exercises. Storiabox’project: project aimed at using smart phones and indoor localization technique for visitor guidance. There, BlueTooth Low Energy beacons have been used to estimate the location of a visitor’s smart phone in an indoor environment. Algorithms based on Received Signal Strength Indication (RSSI), triangulation and Kalman filtering have been implemented to track the visitor's location. Meazure'project : project aimed at providing new opportunities for in vitro compound testing to evaluate the effect on the Blood-Brain Barrier (BBB) and neural tissues integrating BBB restrictions in real-time. Such real-time monitoring allows to perform pharmacokinetic analysis during the tests involving chemical compounds while accounting for BBB permeability. Finally, the integration of the neural model combined with MEA-recordings will give additional physiological relevant information on effects at the neuronal level.
GeReC’project: This project aimed to develop a model of crowd movement based on the cognitive model. This model allows us to detect situations with panic behavior as soon as possible. This project allowed us also to develop techniques for highlighting risk areas in an event site. Publication: T.EL Maliki, A. Rizzotti 2016, Energy-aware Security adaptation in Ubiquitous Mobile Network (SENSORCOMM 2016 Nice)
ARPortable’project: in this project we have compared the performances achieved by an Augmented Reality application on a smartphone based on a General Purpose Processor such as the ARM, and on a smartphone based on a System-on-Chip (ARM+ DSP) such as the OMAP from Texas Instruments. iMoMo’project: While working on iMoMo project in Tanzania founded by Swiss Agency she was participating in a development of a novel, low-cost technology for better water resources management based on modern communication technologies. HBBTV‘project: in this project we have therefore put in place an infrastructure that makes it possible to mix locally, data from an HbbTV-based application and the audiovisual TV stream, from a common or separate storage.
Publication: Y.Rekik, A.Rizzotti, J-D.Schlaeppy 2010,Navigation multi-vues dans les résultats d’une recherche multicritères (IHM 2010 Luxembourg)
VICI'project: In this project a platform based on augmented reality technology on the two themes, museum and home automation, was realized.
EWP’project: Extraction of web data, classification and graphical representation for the purpose of simplified navigation in complex data, to simplify search in an engine regarding a particular theme. VMS’project: the goal in this was automation of multimedia application development (image and sound) by a module flow.
A.Rizzotti 2007, Une architecture logicielle pour le développement rapide d'applications de traitement de l'image ou du son / Flash informatique EPFL. 2007