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Improving Actigraph Sleep/Wake Classification with Cardio-Respiratory Signals

Related publications (63)

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Signal Processing in Space and Time

Francisco Pereira Correia Pinto

Sound waves propagate through space and time by transference of energy between the particles in the medium, which vibrate according to the oscillation patterns of the waves. These vibrations can be captured by a microphone and translated into a digital sig ...

EPFL2010

Frame Domain Signal Processing: Framework and Applications

Martin Vetterli, Amina Chebira

Besides basis expansions, frames representations play a key role in signal processing. We thus consider the problem of frame domain signal processing, which is more complex and challenging than transform domain processing. Examples of such processing aboun ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Power Efficient Hardware Implementation of a Fuzzy Neural Network

Rafal Tomasz Dlugosz

This paper presents a digital, transistor level implemented neo-fuzzy neural network. This type of neural network is particularly well suited for real-time applications like those encountered in signal processing and nonlinear system identification. We con ...

Technical University of Lodz2010

Sleep and Wake Classification With ECG and Respiratory Effort Signals

Dario Floreano, Claudio Mattiussi, Walter Karlen

We describe a method for the online classification of sleep/wake states based on cardiorespiratory signals produced by wearable sensors. The method was conceived in view of its applicability to a wearable sleepiness monitoring device. The method uses a Fas ...

2009

Endoscopic low coherence interferometry applied to tri-dimensional contouring of upper airways

Yves Delacrétaz

This thesis presents a novel approach for optical tri-dimensional contouring, requiring only one acquisition to extract a contour depth. It is based on an interferometric setup, using a reduced coherence light source, and is fully adaptable to endoscopic p ...

EPFL2009

Adaptive Sleep/Wake Classification Based on Cardiorespiratory Signals for Wearable Devices

Dario Floreano, Claudio Mattiussi, Walter Karlen

We describe a method to classify online sleep/wake states of humans based on cardiorespiratory signals for wearable applications. The method is designed to be embedded in a portable microcontroller device and to cope with the resulting tight power and weig ...

IEEE Press2007

Learning Multi-Modal Dictionaries

Pierre Vandergheynst, Rémi Gribonval, Gianluca Monaci, Philippe Jost

Real-world phenomena involve complex interactions between multiple signal modalities. As a consequence, humans are used to integrate at each instant perceptions from all their senses in order to enrich their understanding of the surrounding world. This par ...

2007

The Distributed Karhunen-Loève Transform

Martin Vetterli, Michael Christoph Gastpar, Pier Luigi Dragotti

The Karhunen–Loève transform (KLT) is a key ele- ment of many signal processing and communication tasks. Many recent applications involve distributed signal processing, where it is not generally possible to apply the KLT to the entire signal; rather, the K ...

2006

Sampling innovations

Pina Marziliano

Sampling theory has prospered extensively in the last century. The elegant mathematics and the vast number of applications are the reasons for its popularity. The applications involved in this thesis are in signal processing and communications and call out ...

EPFL2002

Fast Fourier transforms: A tutorial review and a state of the art

Martin Vetterli

The publication of the Cooley-Tukey fast Fourier transform (FIT) algorithm in 1965 has opened a new area in digital signal processing by reducing the order of complexity of some crucial computational tasks like Fourier transform and convolution from

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1990

Fast Fourier transforms: A tutorial review and a state of the art

Martin Vetterli

N^2

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1990