Publications associées à Karl Pearson

Development of a Robotic Microsurgeon for Embryonic Research

Understanding how biological matter takes its shape is instrumental to biology, bioengineering, medicine, and bioinspired engineering. Gaining information on the principles of morphogenesis could enable clinicians to correct developmental abnormalities, ev ...

EPFL2023

Machine Learning for Musculoskeletal Modeling of Upper Extremity

Rahul Sharma

We propose a novel machine learning (ML)-driven methodology to estimate biomechanical variables of interest traditionally obtained from upper-extremity musculoskeletal (MSK) modeling. MSK models facilitate personalized modeling, perform "what-if" analyses, ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Wearable multifunctional sweat-sensing system for efficient healthcare monitoring

Giovanni De Micheli, Sandro Carrara, Mandresy Ivan Ny Hanitra, Irene Taurino, Francesca Criscuolo, Nicolò Oliva, Simone Aiassa

Despite the huge expansion in recent years of sweat sensing and wearable technologies, several challenges are still open, including poor sample collection, separate sampling and analysis, low multi-sensing capabilities and materials toxicity. In this work, ...

2020

Learning Trajectory Distributions for Assisted Teleoperation and Path Planning

Several approaches have been proposed to assist humans in co-manipulation and teleoperation tasks given demonstrated trajectories. However, these approaches are not applicable when the demonstrations are suboptimal or when the generalization capabilities o ...

2019

Cortical Dysconnectivity Measured by Structural Covariance Is Associated With the Presence of Psychotic Symptoms in 22q11.2 Deletion Syndrome

Dimitri Nestor Alice Van De Ville, Maude Schneider, Marie Schaer, Maria Carmela Padula

BACKGROUND: 22q11.2 deletion syndrome (22q11DS) is the third-largest known genetic risk factor for the development of psychosis. Dysconnectivity has consistently been implicated in the physiopathology of psychosis. Structural covariance of cortical morphol ...

2018

Computational aspects of correlation power analysis

Joppe Willem Bos, Paul Bottinelli

Since the discovery of simple power attacks, the cryptographic research community has developed significantly more advanced attack methods. The idea behind most algorithms remains to perform a statistical analysis by correlating the power trace obtained wh ...

Springer Heidelberg2017

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Jean-Philippe Thiran, Meritxell Bach Cuadra, Xavier Bresson, Nawal Houhou, Anca-Ramona Ciurte, Alessia Pica

Segmenting ultrasound images is a challenging problem where standard unsupervised segmentation methods such as the well-known Chan-Vese method fail. We propose in this paper an efficient segmentation method for this class of images. Our proposed algorithm ...

2011