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NPRP 4-1303-2-517- Progress Report Number 6- "Automated Neonatal EEG quality assessment and improvement using artefact filtering and signal segmentation"
(2016 , Report)
This is a progress report on the project NPRP 4 - 1303 - 2 – 517- Progress Report Number 6- "Automated Neonatal EEG quality assessment and improvement using artefact filtering and signal segmentation"
NPRP 6-885-2-364- Progress Report Number 4- "Localization of EEG Abnormalities for Improving Brain Monitoring of Newborn Babies at Risk of Brain Injury using a multichannel time-frequency signal processing approach"
(2016 , Report)
This is a project report on the project NPRP 6 - 885 - 2 – 364 - Progress Report Number 4- Localization of EEG Abnormalities for Improving Brain Monitoring of Newborn Babies at Risk of Brain Injury using a multichannel ...
Radar fall detectors: A comparison
(
SPIE
, 2016 , Conference Paper)
Falls are a major cause of accidents in elderly people. Even simple falls can lead to severe injuries, and sometimes result in death. Doppler fall detection has drawn much attention in recent years. Micro-Doppler signatures ...
Radar fall detection using principal component analysis
(
SPIE
, 2016 , Conference Paper)
Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. ...
Design of a Time-Frequency Algorithm for Automatic Eeg Artifact Removal
(
Hamad bin Khalifa University Press (HBKU Press)
, 2016 , Conference Paper)
The injuries suffered by newborns during birth are a major health issue. To improve the health outcomes of sick newborns using EEG measurements, a number of recent studies focused on the use of high-resolution Time-Frequency ...
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 ...
Time-frequency methods in communications
(
Elsevier Inc.
, 2016 , Book chapter)
The wide range of potential applications of time-frequency (t,f) methods made them an important tool in most fields of science and engineering. Telecommunications is one of the key industries where (t,f) methods started ...
Advanced implementation and realization of TFDs
(
Elsevier Inc.
, 2016 , Book chapter)
The design of efficient algorithms is the key to effective utilization of the properties of time-frequency distributions (TFDs) for real-life applications. This chapter presents the needed procedures, techniques, and ...
Time-frequency methods in radar, sonar, and acoustics
(
Elsevier Inc.
, 2016 , Book chapter)
The fields of radar and sonar are traditionally key application areas and testing grounds for advances in signal processing, including time-frequency (t,f) methodologies; their significance is demonstrated in seven ...
Advanced time-frequency signal and system analysis
(
Elsevier Inc.
, 2016 , Book chapter)
This chapter extends Part I by presenting additional advanced key principles underlying the use of time-frequency (t,f) methods. The topic is covered in 11 focused sections.
Section 4.1 describes the relationships between ...