Search
Now showing items 1-7 of 7
Classification of fetal movement accelerometry through time-frequency features
(
IEEE
, 2014 , Conference Paper)
This paper presents a time-frequency approach for fetal movement monitoring which is based on classification of accelerometry signals collected from pregnant women's abdomen. Features extracted from time-frequency distribution ...
Automated class-based compression for real-time epileptic seizure detection
(
IEEE Computer Society
, 2018 , Conference Paper)
The emergence of next generation wireless networking technologies has motivated a paradigm shift in development of viable mobile-Health applications for ubiquitous real-time healthcare monitoring. However, remote healthcare ...
Haralick feature extraction from time-frequency images for epileptic seizure detection and classification of EEG data
(
IEEE
, 2014 , Conference Paper)
This paper presents novel time-frequency (t-f) features based on t-f image descriptors for the automatic detection and classification of epileptic seizure activities in EEG data. Most previous methods were based only on ...
EEG-based automatic epilepsy diagnosis using the instantaneous frequency with sub-band energies
(
IEEE
, 2011 , Conference Paper)
This paper presents a novel approach for classifying the electroencephalogram (EEG) signals as normal or abnormal. This method uses features derived from the
instantaneous frequency (IF) and energies of EEG signals in ...
A Comparative Study of Machine Learning Approaches for Handwriter Identification
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
During the past few years, writer identification has attracted significant interest due to its real-life applications including document analysis, forensics etc. Machine learning algorithms have played an important role ...
Effectiveness of combined time-frequency imageand signal-based features for improving the detection and classification of epileptic seizure activities in EEG signals
(
IEEE
, 2014 , Conference Paper)
This paper presents new time-frequency (T-F) features to improve the detection and classification of epileptic seizure activities in EEG signals. Most previous methods were based only on signal features derived from the ...
Classification for Imperfect EEG Epileptic Seizure in IoT applications: A Comparative Study
(
Institute of Electrical and Electronics Engineers Inc.
, 2018 , Conference Paper)
Epileptic seizure detection could be detected through investigating the electroencephalography (EEG), which is deemed to be very important for IoT wearable sensor-based health systems. EEG-based classification is crucial ...