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السجلات المعروضة 11 -- 20 من 25
Performance evaluation for compression-accuracy trade-off using compressive sensing for EEG-based epileptic seizure detection in wireless tele-monitoring
(
IEEE
, 2013 , Conference Paper)
Brain is the most important part in the human body controlling muscles and nerves; Electroencephalogram (EEG) signals record brain electric activities. EEG signals capture important information pertinent to different ...
Innovative ad-hoc wireless sensor networks to significantly reduce leakages in underground water infrastructures
(
IEEE
, 2010 , Conference Paper)
This paper presents an ICT solution to overcome the problem of water dispersion in water distribution networks. Leakage prevention and breaks identification in water distribution networks are fundamental for an adequate ...
On the use of time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
This paper proposes new time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals. These features are obtained by translating and combining the most relevant time-domain ...
Time-frequency features for pattern recognition using high-resolution TFDs: A tutorial review
(
Elsevier Inc.
, 2015 , Article)
This paper presents a tutorial review of recent advances in the field of time-frequency (t, f) signal processing with focus on exploiting (t, f) image feature information using pattern recognition techniques for detection ...
Design of a high-resolution separable-kernel quadratic TFD for improving newborn health outcomes using fetal movement detection
(2012 , Conference Paper)
Prior to birth, fetus health can be monitored by the variety and scale of its movements. In addition, at birth, EEG signals are recorded from at-risk newborns. Studies have shown that both fetal movements and newborn EEGs ...
Detection of perinatal hypoxia using time-frequency analysis of heart rate variability signals
(2013 , Conference Paper)
This paper presents a time-frequency approach to detect perinatal hypoxia by characterizing the nonstationary nature of heart rate variability (HRV) signals. Quadratic time-frequency distributions (TFDs) are used to represent ...
On the selection of time-frequency features for improving the detection and classification of newborn EEG seizure signals and other abnormalities
(2012 , Conference Paper)
This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by translating some relevant time features or frequency features to the joint time-frequency domain. ...
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
(
Elsevier B.V.
, 2016 , Article)
Time-frequency (TF) based machine learning methodologies can improve the design of classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF feature extraction is performed on multi-channel ...
Principles of time-frequency feature extraction for change detection in non-stationary signals: Applications to newborn EEG abnormality detection
(
Elsevier Ltd
, 2015 , Article)
This paper considers the general problem of detecting change in non-stationary signals using features observed in the time-frequency (t,f) domain, obtained using a class of quadratic time-frequency distributions (QTFDs). ...
A review of time-frequency matched filter design with application to seizure detection in multichannel newborn EEG
(
Elsevier Inc.
, 2014 , Article)
This paper presents a novel design of a time-frequency (t-f) matched filter as a solution to the problem of detecting a non-stationary signal in the presence of additive noise, for application to the detection of newborn ...