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Biomedical signal processing

Seizure Prediction using Hilbert Huang Transform on Field Programmable Gate Array


Feature Distribution of Pre and Interictal Bandwidths

The Hilbert Huang Transform (HHT) has been used extensively in the time-frequency analysis of electroencephalography (EEG) signals and Brain-Computer Interfaces. Most studies utilizing the HHT for extracting features in seizure prediction have used intracranial EEG recordings. Invasive implants in the cortex have unknown long term consequences and pose the risk of complications during surgery. This added risk dimension makes them unsuitable for continuous monitoring as would be the requirement in a Body Area Network.

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Authors:
Lakshitha Wijesinghe, Sudaraka Mallawaarachchi
Submitted On:
23 February 2016 - 1:44pm
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Presentation - Seizure Prediction using HHT on FPGA.pdf

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[1] Lakshitha Wijesinghe, Sudaraka Mallawaarachchi, "Seizure Prediction using Hilbert Huang Transform on Field Programmable Gate Array", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/422. Accessed: Apr. 24, 2019.
@article{422-15,
url = {http://sigport.org/422},
author = {Lakshitha Wijesinghe; Sudaraka Mallawaarachchi },
publisher = {IEEE SigPort},
title = {Seizure Prediction using Hilbert Huang Transform on Field Programmable Gate Array},
year = {2015} }
TY - EJOUR
T1 - Seizure Prediction using Hilbert Huang Transform on Field Programmable Gate Array
AU - Lakshitha Wijesinghe; Sudaraka Mallawaarachchi
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/422
ER -
Lakshitha Wijesinghe, Sudaraka Mallawaarachchi. (2015). Seizure Prediction using Hilbert Huang Transform on Field Programmable Gate Array. IEEE SigPort. http://sigport.org/422
Lakshitha Wijesinghe, Sudaraka Mallawaarachchi, 2015. Seizure Prediction using Hilbert Huang Transform on Field Programmable Gate Array. Available at: http://sigport.org/422.
Lakshitha Wijesinghe, Sudaraka Mallawaarachchi. (2015). "Seizure Prediction using Hilbert Huang Transform on Field Programmable Gate Array." Web.
1. Lakshitha Wijesinghe, Sudaraka Mallawaarachchi. Seizure Prediction using Hilbert Huang Transform on Field Programmable Gate Array [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/422

Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine

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Authors:
Kun Qian, Fabien Ringeval, Björn Schuller
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23 February 2016 - 1:44pm
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Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine.pdf

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[1] Kun Qian, Fabien Ringeval, Björn Schuller, "Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/420. Accessed: Apr. 24, 2019.
@article{420-15,
url = {http://sigport.org/420},
author = {Kun Qian; Fabien Ringeval; Björn Schuller },
publisher = {IEEE SigPort},
title = {Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine},
year = {2015} }
TY - EJOUR
T1 - Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine
AU - Kun Qian; Fabien Ringeval; Björn Schuller
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/420
ER -
Kun Qian, Fabien Ringeval, Björn Schuller. (2015). Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine. IEEE SigPort. http://sigport.org/420
Kun Qian, Fabien Ringeval, Björn Schuller, 2015. Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine. Available at: http://sigport.org/420.
Kun Qian, Fabien Ringeval, Björn Schuller. (2015). "Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine." Web.
1. Kun Qian, Fabien Ringeval, Björn Schuller. Bird Sounds Classification by Large Scale Acoustic Features and Extreme Learning Machine [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/420

Enhancing the Reliability of Epileptic Seizure Alarms for Scalp EEG Signals

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23 February 2016 - 1:44pm
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Energy Ratio Paper.pdf

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[1] , "Enhancing the Reliability of Epileptic Seizure Alarms for Scalp EEG Signals", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/357. Accessed: Apr. 24, 2019.
@article{357-15,
url = {http://sigport.org/357},
author = { },
publisher = {IEEE SigPort},
title = {Enhancing the Reliability of Epileptic Seizure Alarms for Scalp EEG Signals},
year = {2015} }
TY - EJOUR
T1 - Enhancing the Reliability of Epileptic Seizure Alarms for Scalp EEG Signals
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/357
ER -
. (2015). Enhancing the Reliability of Epileptic Seizure Alarms for Scalp EEG Signals. IEEE SigPort. http://sigport.org/357
, 2015. Enhancing the Reliability of Epileptic Seizure Alarms for Scalp EEG Signals. Available at: http://sigport.org/357.
. (2015). "Enhancing the Reliability of Epileptic Seizure Alarms for Scalp EEG Signals." Web.
1. . Enhancing the Reliability of Epileptic Seizure Alarms for Scalp EEG Signals [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/357

The Influence of EM Estimation of Missing Nodes in DCM on Model Ranking)

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23 February 2016 - 1:44pm
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globalSIP2015_upload.pdf

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[1] , "The Influence of EM Estimation of Missing Nodes in DCM on Model Ranking)", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/352. Accessed: Apr. 24, 2019.
@article{352-15,
url = {http://sigport.org/352},
author = { },
publisher = {IEEE SigPort},
title = {The Influence of EM Estimation of Missing Nodes in DCM on Model Ranking)},
year = {2015} }
TY - EJOUR
T1 - The Influence of EM Estimation of Missing Nodes in DCM on Model Ranking)
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/352
ER -
. (2015). The Influence of EM Estimation of Missing Nodes in DCM on Model Ranking). IEEE SigPort. http://sigport.org/352
, 2015. The Influence of EM Estimation of Missing Nodes in DCM on Model Ranking). Available at: http://sigport.org/352.
. (2015). "The Influence of EM Estimation of Missing Nodes in DCM on Model Ranking)." Web.
1. . The Influence of EM Estimation of Missing Nodes in DCM on Model Ranking) [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/352

Stationary regime for Standing Wave Central Pattern Generator


Cover page Standing Wave CPG Roberto

The purpose of this research is to show that the spatio-temporal analysis on surface Electromyographic (sEMG) signals that originally confirmed existence of a standing wave Central Pattern Generator (CPG) along the spine are reproducible under less than ideal conditions and despite evolution of the entrainment technique, different hardware and data collection protocol. This analysis reveals a coherence at a distance between sEMG signals, which because of its large scale reproducibility could become a test for properly functioning Central Nervous System.

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Authors:
Edmond Jonckheere
Submitted On:
16 March 2018 - 3:14pm
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Presentation_Roberto_EJ_IEEE 2015.pdf

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[1] Edmond Jonckheere, "Stationary regime for Standing Wave Central Pattern Generator", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/346. Accessed: Apr. 24, 2019.
@article{346-15,
url = {http://sigport.org/346},
author = {Edmond Jonckheere },
publisher = {IEEE SigPort},
title = {Stationary regime for Standing Wave Central Pattern Generator},
year = {2015} }
TY - EJOUR
T1 - Stationary regime for Standing Wave Central Pattern Generator
AU - Edmond Jonckheere
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/346
ER -
Edmond Jonckheere. (2015). Stationary regime for Standing Wave Central Pattern Generator. IEEE SigPort. http://sigport.org/346
Edmond Jonckheere, 2015. Stationary regime for Standing Wave Central Pattern Generator. Available at: http://sigport.org/346.
Edmond Jonckheere. (2015). "Stationary regime for Standing Wave Central Pattern Generator." Web.
1. Edmond Jonckheere. Stationary regime for Standing Wave Central Pattern Generator [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/346

Handling High Level of Censoring For Endovascular Aortic Repair Prediction

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Authors:
Xianghong Ma
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23 February 2016 - 1:44pm
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GlobalSIP_Omneya3.pdf

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[1] Xianghong Ma, "Handling High Level of Censoring For Endovascular Aortic Repair Prediction", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/341. Accessed: Apr. 24, 2019.
@article{341-15,
url = {http://sigport.org/341},
author = {Xianghong Ma },
publisher = {IEEE SigPort},
title = {Handling High Level of Censoring For Endovascular Aortic Repair Prediction},
year = {2015} }
TY - EJOUR
T1 - Handling High Level of Censoring For Endovascular Aortic Repair Prediction
AU - Xianghong Ma
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/341
ER -
Xianghong Ma. (2015). Handling High Level of Censoring For Endovascular Aortic Repair Prediction. IEEE SigPort. http://sigport.org/341
Xianghong Ma, 2015. Handling High Level of Censoring For Endovascular Aortic Repair Prediction. Available at: http://sigport.org/341.
Xianghong Ma. (2015). "Handling High Level of Censoring For Endovascular Aortic Repair Prediction." Web.
1. Xianghong Ma. Handling High Level of Censoring For Endovascular Aortic Repair Prediction [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/341

Neural Correlates of Affective Context in Facial Expression Analysis: A Simultaneous EEG-fNIRS Study

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Authors:
Hasan Ayaz, Ali Akansu
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23 February 2016 - 1:44pm
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GlobalSIP_2015_Presentation_Sun.pdf

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[1] Hasan Ayaz, Ali Akansu, "Neural Correlates of Affective Context in Facial Expression Analysis: A Simultaneous EEG-fNIRS Study", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/335. Accessed: Apr. 24, 2019.
@article{335-15,
url = {http://sigport.org/335},
author = {Hasan Ayaz; Ali Akansu },
publisher = {IEEE SigPort},
title = {Neural Correlates of Affective Context in Facial Expression Analysis: A Simultaneous EEG-fNIRS Study},
year = {2015} }
TY - EJOUR
T1 - Neural Correlates of Affective Context in Facial Expression Analysis: A Simultaneous EEG-fNIRS Study
AU - Hasan Ayaz; Ali Akansu
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/335
ER -
Hasan Ayaz, Ali Akansu. (2015). Neural Correlates of Affective Context in Facial Expression Analysis: A Simultaneous EEG-fNIRS Study. IEEE SigPort. http://sigport.org/335
Hasan Ayaz, Ali Akansu, 2015. Neural Correlates of Affective Context in Facial Expression Analysis: A Simultaneous EEG-fNIRS Study. Available at: http://sigport.org/335.
Hasan Ayaz, Ali Akansu. (2015). "Neural Correlates of Affective Context in Facial Expression Analysis: A Simultaneous EEG-fNIRS Study." Web.
1. Hasan Ayaz, Ali Akansu. Neural Correlates of Affective Context in Facial Expression Analysis: A Simultaneous EEG-fNIRS Study [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/335

Epileptic focus localization using EEG based on discrete wavelet transform through full-level decomposition


Electroencephalogram (EEG) is a gold standard in epilepsy diagnosis and has been widely studied for epilepsy-related signal classification, such as seizure detection or focus localization. In the past few years, discrete wavelet transform (DWT) has been widely used to analyze epileptic EEG. However, one practical question unanswered is the optimal levels of wavelet decomposition. Deeper DWT can yield a more detailed depiction of signals but it requires substantially more computational time.

Paper Details

Authors:
Suiren Wan
Submitted On:
23 February 2016 - 1:38pm
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epileptic-focus-localization.pdf

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[1] Suiren Wan, "Epileptic focus localization using EEG based on discrete wavelet transform through full-level decomposition", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/216. Accessed: Apr. 24, 2019.
@article{216-15,
url = {http://sigport.org/216},
author = {Suiren Wan },
publisher = {IEEE SigPort},
title = {Epileptic focus localization using EEG based on discrete wavelet transform through full-level decomposition},
year = {2015} }
TY - EJOUR
T1 - Epileptic focus localization using EEG based on discrete wavelet transform through full-level decomposition
AU - Suiren Wan
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/216
ER -
Suiren Wan. (2015). Epileptic focus localization using EEG based on discrete wavelet transform through full-level decomposition. IEEE SigPort. http://sigport.org/216
Suiren Wan, 2015. Epileptic focus localization using EEG based on discrete wavelet transform through full-level decomposition. Available at: http://sigport.org/216.
Suiren Wan. (2015). "Epileptic focus localization using EEG based on discrete wavelet transform through full-level decomposition." Web.
1. Suiren Wan. Epileptic focus localization using EEG based on discrete wavelet transform through full-level decomposition [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/216

Wireless Body-Area Network Time Synchronization using R Peak Reference Broadcasts


Telemonitoring of biosignals is a growing area of research due to the aging world population. Telemonitoring utilizes a wireless body-area network (WBAN) consisting of wearable biosignal sensors equipped with ultra low power radios. The measured data from each sensor on the patient is sent to a smartphone, which then sends the data to a healthcare provider via the internet. To enable real-time telemonitoring of the biosignals, it is desirable to have accurate timestamped data from the sensors in the WBAN.

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Submitted On:
23 February 2016 - 1:43pm
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Ramlall SigPort 2.pdf

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[1] , "Wireless Body-Area Network Time Synchronization using R Peak Reference Broadcasts", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/215. Accessed: Apr. 24, 2019.
@article{215-15,
url = {http://sigport.org/215},
author = { },
publisher = {IEEE SigPort},
title = {Wireless Body-Area Network Time Synchronization using R Peak Reference Broadcasts},
year = {2015} }
TY - EJOUR
T1 - Wireless Body-Area Network Time Synchronization using R Peak Reference Broadcasts
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/215
ER -
. (2015). Wireless Body-Area Network Time Synchronization using R Peak Reference Broadcasts. IEEE SigPort. http://sigport.org/215
, 2015. Wireless Body-Area Network Time Synchronization using R Peak Reference Broadcasts. Available at: http://sigport.org/215.
. (2015). "Wireless Body-Area Network Time Synchronization using R Peak Reference Broadcasts." Web.
1. . Wireless Body-Area Network Time Synchronization using R Peak Reference Broadcasts [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/215

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