Publications related to Automatic Mallampati Classification Using Active Appearance Models

Pencil Graphite Needle-Shaped Biosensor for Anaesthetic Monitoring in Human Serum

Sandro Carrara, Danilo Demarchi, Simone Aiassa

Direct and online continuous monitoring of anaesthetic intake by the patient's blood stream improves practices in the critical procedure of anaesthesia. Several systems have been proposed to address this challenge. Electrochemical techniques are highly app ...

IEEE2020

Oblivious Sketching of High-Degree Polynomial Kernels

Mikhail Kapralov, Amir Zandieh

Kernel methods are fundamental tools in machine learning that allow detection of non-linear dependencies between data without explicitly constructing feature vectors in high dimensional spaces. A major disadvantage of kernel methods is their poor scalabili ...

ASSOC COMPUTING MACHINERY2020

Live Demonstration: Quasi-Digital Portable Pen to Monitor Anaesthetics Delivery

Sandro Carrara, Danilo Demarchi, Francesco Grassi, Simone Aiassa

The live demonstration presents the innovative concept of a portable pen-device able to sense anaesthetic compounds over time for improved anaesthesiology practice. A custom Printed Circuit Board (PCB) manage in the event-based quasi-digital domain the sam ...

IEEE2019

Quasi-Digital Biosensor-Interface for a Portable Pen to Monitor Anaesthetics Delivery

Sandro Carrara, Francesca Stradolini, Abuduwaili Tuoheti, Danilo Demarchi, Simone Aiassa

Monitoring of patient response to the anaesthetic drugs is an attractive improvement for achieving a correct balance of sedation level, increasing the chance of success in the right procedure of anaesthesia. Nowadays, there are no commercial tools able to ...

IEEE2019

Towards 3D facial morphometry : facial image analysis applications in anesthesiology and 3D spectral nonrigid registration

Gabriel Louis Cuendet

In anesthesiology, the detection and anticipation of difficult tracheal intubation is crucial for patient safety. When undergoing general anesthesia, a patient who is unexpectedly difficult to intubate risks potential life-threatening complications with po ...

EPFL2017

Cascaded PID controller for anaesthesia delivery

Monia Guidi, Alena Simalatsar

The technologies for continuous measurement of the anaesthetic agents circulating in body fluids are not mature yet, though some preliminary prototypes exist already. We present a control algorithm that based on the real measurement of propofol plasma conc ...

2016

Facial Image Analysis for Fully-Automatic Prediction of Difficult Endotracheal Intubation

Jean-Philippe Thiran, Matteo Sorci, Gabriel Louis Cuendet, Anil Yuce, Hua Gao

Goal: Difficult tracheal intubation is a major cause of anesthesia related injuries with potential life threatening complications. Detection and anticipation of difficult airway in the preoperative period is thus crucial for the patients’ safety. We propos ...

Institute of Electrical and Electronics Engineers2015

Some Developments of the Cooray–Rubinstein Formula in the Time Domain

Farhad Rachidi-Haeri

A rigorous formula representing the counterpart of the Cooray-Rubinstein expression in the time domain has recently been derived by the authors. In this paper, the formula is particularized for the cases of a unit step and a linearly rising channel-base cu ...

Institute of Electrical and Electronics Engineers2015

The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Barbara Caputo

There has been increasing interest in applying learning algorithms to improve the dexterity of myoelectric prostheses. In this work, we present a large-scale benchmark evaluation on the second iteration of the publicly released NinaPro database, which cont ...

2014

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Frank Grégoire Jean de Morsier

The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...

EPFL2014

Evaluation of Atlas Fusion Strategies for Segmentation of Head and Neck Lymph Nodes for Radiotherapy Planning

Jean-Philippe Thiran, Meritxell Bach Cuadra, Subrahmanyam Venkata Ravi Mohana Sai Gorthi

Accurate segmentation of lymph nodes in head and neck (H&N) CT images is essential for the radiotherapy planning of the H&N cancer. Atlas-based segmentation methods are widely used for the automated segmentation of such structures. Multi-atlas approaches a ...

Ieee2012

Influence of Blade Aspiration on the Flow Quality of an Annular Axial Compressor Cascade

Peter Ott, Elia Colombo

Experimental and numerical investigations were performed in order to develop a technique of active flow control by aspiration applied to an annular axial compressor cascade. Continuous aspiration is applied through shaped slots located on the suction side ...

2011

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

Jean-Philippe Thiran, Meritxell Bach Cuadra, Subrahmanyam Venkata Ravi Mohana Sai Gorthi

In recent years, multi-atlas fusion methods have gained significant attention in medical image segmentation. In this paper, we propose a general Markov Random Field (MRF) based framework that can perform edge-preserving smoothing of the labels at the time ...

2011

Multi-Atlas based Segmentation of Head and Neck CT Images using Active Contour Framework

Jean-Philippe Thiran, Meritxell Bach Cuadra, Subrahmanyam Venkata Ravi Mohana Sai Gorthi

This paper presents the segmentation of bilateral parotid glands in the Head and Neck (H&N) CT images using an active contour based atlas registration. We compare segmentation results from three atlas selection strategies: (i) selection of “single-most-sim ...

2010

A Kernel Trick For Sequences Applied to Text-Independent Speaker Verification Systems

Samy Bengio

This paper present a principled SVM based speaker verification system. We propose a new framework and a new sequence kernel that can make use of any Mercer kernel at the frame level. An extension of the sequence kernel based on the Max operator is also pro ...

2007

Prior knowledge in Kernel methods

Alexei Pozdnoukhov

Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...

EPFL2006