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Prediction of patient-reported physical activity scores from wearable accelerometer data: a feasibility study

Publications associées (38)

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In this thesis, I focus on monitoring of patients suffering from cardiovascular and neurological diseases through the use of wearable devices. The main diseases considered in this thesis are atrial fibrillation (AF), myocardial infarction (MI), and epileps ...

EPFL2020

On the Impact of Uncertainty for Path Planning

We consider the problem of planning paths on graphs with some edges whose traversability is uncertain; for each uncertain edge, we are given a probability of being traversable (e.g., by a learned classifier). We categorize different interpretations of the ...

2019

Real-Time Event-Driven Classification Technique for Early Detection and Prevention of Myocardial Infarction on Wearable Systems

David Atienza Alonso, Amir Aminifar, Dionisije Sopic

A considerable portion of government health-care spending is allocated to the continuous monitoring of patients suffering from cardiovascular diseases, particularly myocardial infarction (MI). Wearable devices present a cost-effective means of monitoring p ...

2018

Building a Question-Answering Chatbot using Forum Data in the Semantic Space

Pierre Dillenbourg, Marc Laperrouza, Khalil Mrini

We build a conversational agent which knowledge base is an online forum for parents of autistic children. We collect about 35,000 threads totalling some 600,000 replies, and label 1% of them for usefulness using Amazon Mechanical Turk. We train a Random Fo ...

2018

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While Machine Learning algorithms are key to automating organelle segmentation in large EM stacks, they require annotated data, which is hard to come by in sufficient quantities. Furthermore, images acquired from one part of the brain are not always repres ...

2016

Dictionary learning for fast classification based on soft-thresholding

Pascal Frossard, Alhussein Fawzi

Classifiers based on sparse representations have recently been shown to provide excellent results in many visual recognition and classification tasks. However, the high cost of computing sparse representations at test time is a major obstacle that limits t ...

Springer2015

Scene Recognition with Naive Bayes Non-linear Learning

Barbara Caputo, Marco Fornoni

A crucial feature of a good scene recognition algorithm is its ability to generalize. Scene categories, especially those related to human made indoor places or to human activities like sports, do present a high degree of intra-class variability, which in t ...

2014

Physical activity is an important determinant of health and well-being in older persons and contributes to their social participation and quality of life. Hence, assessment tools are needed to study this physical activity in free-living conditions. Wearabl ...

Mdpi Ag2014

Fast Object Detection with Entropy-Driven Evaluation

Pascal Fua, François Fleuret, Raphael Sznitman, Carlos Joaquin Becker

Cascade-style approaches to implementing ensemble classifiers can deliver significant speed-ups at test time. While highly effective, they remain challenging to tune and their overall performance depends on the availability of large validation sets to esti ...

2013

Fast Object Detection with Entropy-Driven Evaluation

Pascal Fua, François Fleuret, Raphael Sznitman, Carlos Joaquin Becker

2013