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Biomedical signal processing

COMMUNITY DETECTION FROM GENOMIC DATASETS ACROSS HUMAN CANCERS


Cancers originating from different organs can show similar genomic alterations whereas cancers originating from the same organ can vary across patients. Therefore cancer stratification that does not depend on the tissue of the origin can play an important role to better understand cancers having similar genomic patterns irrespective of their origins. In this work, we formulated the problem as a weighted graph and communities were found using a modularity maximization based graph clustering method. We classified 3,199 subjects from twelve different cancer types into five clusters.

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Authors:
Nandinee Haq, Z. Jane Wang
Submitted On:
8 December 2016 - 2:41pm
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[1] Nandinee Haq, Z. Jane Wang, "COMMUNITY DETECTION FROM GENOMIC DATASETS ACROSS HUMAN CANCERS", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1424. Accessed: Jul. 20, 2019.
@article{1424-16,
url = {http://sigport.org/1424},
author = {Nandinee Haq; Z. Jane Wang },
publisher = {IEEE SigPort},
title = {COMMUNITY DETECTION FROM GENOMIC DATASETS ACROSS HUMAN CANCERS},
year = {2016} }
TY - EJOUR
T1 - COMMUNITY DETECTION FROM GENOMIC DATASETS ACROSS HUMAN CANCERS
AU - Nandinee Haq; Z. Jane Wang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1424
ER -
Nandinee Haq, Z. Jane Wang. (2016). COMMUNITY DETECTION FROM GENOMIC DATASETS ACROSS HUMAN CANCERS. IEEE SigPort. http://sigport.org/1424
Nandinee Haq, Z. Jane Wang, 2016. COMMUNITY DETECTION FROM GENOMIC DATASETS ACROSS HUMAN CANCERS. Available at: http://sigport.org/1424.
Nandinee Haq, Z. Jane Wang. (2016). "COMMUNITY DETECTION FROM GENOMIC DATASETS ACROSS HUMAN CANCERS." Web.
1. Nandinee Haq, Z. Jane Wang. COMMUNITY DETECTION FROM GENOMIC DATASETS ACROSS HUMAN CANCERS [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1424

Error Probability Analysis for LDA-Bayesian Based Classification of Alzheimer's Disease and Normal Control Subjects


This paper provides a theoretical analysis on the classification accuracy of LDA-Bayesian based method with respect

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Authors:
Zhe Wang, Tianlong Song, Yuan Liang, Tongtong Li
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6 December 2016 - 12:51pm
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[1] Zhe Wang, Tianlong Song, Yuan Liang, Tongtong Li, "Error Probability Analysis for LDA-Bayesian Based Classification of Alzheimer's Disease and Normal Control Subjects", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1371. Accessed: Jul. 20, 2019.
@article{1371-16,
url = {http://sigport.org/1371},
author = {Zhe Wang; Tianlong Song; Yuan Liang; Tongtong Li },
publisher = {IEEE SigPort},
title = {Error Probability Analysis for LDA-Bayesian Based Classification of Alzheimer's Disease and Normal Control Subjects},
year = {2016} }
TY - EJOUR
T1 - Error Probability Analysis for LDA-Bayesian Based Classification of Alzheimer's Disease and Normal Control Subjects
AU - Zhe Wang; Tianlong Song; Yuan Liang; Tongtong Li
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1371
ER -
Zhe Wang, Tianlong Song, Yuan Liang, Tongtong Li. (2016). Error Probability Analysis for LDA-Bayesian Based Classification of Alzheimer's Disease and Normal Control Subjects. IEEE SigPort. http://sigport.org/1371
Zhe Wang, Tianlong Song, Yuan Liang, Tongtong Li, 2016. Error Probability Analysis for LDA-Bayesian Based Classification of Alzheimer's Disease and Normal Control Subjects. Available at: http://sigport.org/1371.
Zhe Wang, Tianlong Song, Yuan Liang, Tongtong Li. (2016). "Error Probability Analysis for LDA-Bayesian Based Classification of Alzheimer's Disease and Normal Control Subjects." Web.
1. Zhe Wang, Tianlong Song, Yuan Liang, Tongtong Li. Error Probability Analysis for LDA-Bayesian Based Classification of Alzheimer's Disease and Normal Control Subjects [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1371

PCA based Algorithm for Longitudinal Brain Tumor Stage Classification & Dynamical Modeling of Tumor Decay in response to VB-111 Virotherapy


In this dissertation, we propose the first, to the best of our knowledge, PCA based algorithm to noninvasively recognize and classify different temporal stages of brain tumors given a large time series of MRI images. We propose an algorithm that addresses the challenging task of classifying stage of tumor over period of time while the tumor is being treated with VB-111 virotherapy. Our approach treats stage tumor recognition as a two-dimensional recognition problem.

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16 November 2016 - 9:38am
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[1] , "PCA based Algorithm for Longitudinal Brain Tumor Stage Classification & Dynamical Modeling of Tumor Decay in response to VB-111 Virotherapy ", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1267. Accessed: Jul. 20, 2019.
@article{1267-16,
url = {http://sigport.org/1267},
author = { },
publisher = {IEEE SigPort},
title = {PCA based Algorithm for Longitudinal Brain Tumor Stage Classification & Dynamical Modeling of Tumor Decay in response to VB-111 Virotherapy },
year = {2016} }
TY - EJOUR
T1 - PCA based Algorithm for Longitudinal Brain Tumor Stage Classification & Dynamical Modeling of Tumor Decay in response to VB-111 Virotherapy
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1267
ER -
. (2016). PCA based Algorithm for Longitudinal Brain Tumor Stage Classification & Dynamical Modeling of Tumor Decay in response to VB-111 Virotherapy . IEEE SigPort. http://sigport.org/1267
, 2016. PCA based Algorithm for Longitudinal Brain Tumor Stage Classification & Dynamical Modeling of Tumor Decay in response to VB-111 Virotherapy . Available at: http://sigport.org/1267.
. (2016). "PCA based Algorithm for Longitudinal Brain Tumor Stage Classification & Dynamical Modeling of Tumor Decay in response to VB-111 Virotherapy ." Web.
1. . PCA based Algorithm for Longitudinal Brain Tumor Stage Classification & Dynamical Modeling of Tumor Decay in response to VB-111 Virotherapy [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1267

Wireless EEG Signal Acquisition and Robo-control

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Authors:
Rahul Kher and Rathang Shah
Submitted On:
27 August 2016 - 1:49am
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Wireless EEG Signal Acquisition and Robo Control.pptx

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[1] Rahul Kher and Rathang Shah, "Wireless EEG Signal Acquisition and Robo-control", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1145. Accessed: Jul. 20, 2019.
@article{1145-16,
url = {http://sigport.org/1145},
author = {Rahul Kher and Rathang Shah },
publisher = {IEEE SigPort},
title = {Wireless EEG Signal Acquisition and Robo-control},
year = {2016} }
TY - EJOUR
T1 - Wireless EEG Signal Acquisition and Robo-control
AU - Rahul Kher and Rathang Shah
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1145
ER -
Rahul Kher and Rathang Shah. (2016). Wireless EEG Signal Acquisition and Robo-control. IEEE SigPort. http://sigport.org/1145
Rahul Kher and Rathang Shah, 2016. Wireless EEG Signal Acquisition and Robo-control. Available at: http://sigport.org/1145.
Rahul Kher and Rathang Shah. (2016). "Wireless EEG Signal Acquisition and Robo-control." Web.
1. Rahul Kher and Rathang Shah. Wireless EEG Signal Acquisition and Robo-control [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1145

ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR

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Authors:
Rahul Kher, Shivang Gohel
Submitted On:
24 August 2016 - 6:45am
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ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR.pptx

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[1] Rahul Kher, Shivang Gohel, "ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1144. Accessed: Jul. 20, 2019.
@article{1144-16,
url = {http://sigport.org/1144},
author = {Rahul Kher; Shivang Gohel },
publisher = {IEEE SigPort},
title = {ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR},
year = {2016} }
TY - EJOUR
T1 - ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR
AU - Rahul Kher; Shivang Gohel
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1144
ER -
Rahul Kher, Shivang Gohel. (2016). ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR. IEEE SigPort. http://sigport.org/1144
Rahul Kher, Shivang Gohel, 2016. ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR. Available at: http://sigport.org/1144.
Rahul Kher, Shivang Gohel. (2016). "ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR." Web.
1. Rahul Kher, Shivang Gohel. ABNORMALITY CLASSIFICATION OF ECG SIGNAL USING DSP PROCESSOR [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1144

Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG)

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Authors:
Rahul Kher, Tanmay Pawar and Vishvjit Thakar
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24 August 2016 - 2:39am
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Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG).ppt

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[1] Rahul Kher, Tanmay Pawar and Vishvjit Thakar, "Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG)", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1143. Accessed: Jul. 20, 2019.
@article{1143-16,
url = {http://sigport.org/1143},
author = {Rahul Kher; Tanmay Pawar and Vishvjit Thakar },
publisher = {IEEE SigPort},
title = {Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG)},
year = {2016} }
TY - EJOUR
T1 - Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG)
AU - Rahul Kher; Tanmay Pawar and Vishvjit Thakar
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1143
ER -
Rahul Kher, Tanmay Pawar and Vishvjit Thakar. (2016). Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG). IEEE SigPort. http://sigport.org/1143
Rahul Kher, Tanmay Pawar and Vishvjit Thakar, 2016. Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG). Available at: http://sigport.org/1143.
Rahul Kher, Tanmay Pawar and Vishvjit Thakar. (2016). "Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG)." Web.
1. Rahul Kher, Tanmay Pawar and Vishvjit Thakar. Impact of Body Movement Activities on Wearable Ambulatory Electrocardiogram (A-ECG) [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1143

The intrinsic value of HFO features as a biomarker of epileptic activity

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Authors:
SV Gliske, WC Stacey, KR Moon, AO Hero III
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4 April 2016 - 11:56am
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[1] SV Gliske, WC Stacey, KR Moon, AO Hero III, "The intrinsic value of HFO features as a biomarker of epileptic activity", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1084. Accessed: Jul. 20, 2019.
@article{1084-16,
url = {http://sigport.org/1084},
author = {SV Gliske; WC Stacey; KR Moon; AO Hero III },
publisher = {IEEE SigPort},
title = {The intrinsic value of HFO features as a biomarker of epileptic activity},
year = {2016} }
TY - EJOUR
T1 - The intrinsic value of HFO features as a biomarker of epileptic activity
AU - SV Gliske; WC Stacey; KR Moon; AO Hero III
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1084
ER -
SV Gliske, WC Stacey, KR Moon, AO Hero III. (2016). The intrinsic value of HFO features as a biomarker of epileptic activity. IEEE SigPort. http://sigport.org/1084
SV Gliske, WC Stacey, KR Moon, AO Hero III, 2016. The intrinsic value of HFO features as a biomarker of epileptic activity. Available at: http://sigport.org/1084.
SV Gliske, WC Stacey, KR Moon, AO Hero III. (2016). "The intrinsic value of HFO features as a biomarker of epileptic activity." Web.
1. SV Gliske, WC Stacey, KR Moon, AO Hero III. The intrinsic value of HFO features as a biomarker of epileptic activity [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1084

CLASSIFICATION OF BISYLLABIC LEXICAL STRESS PATTERNS IN DISORDERED SPEECH USING DEEP LEARNING

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Authors:
Mostafa Shahin, Ricardo Gutierrez-Osuna, Beena Ahmed
Submitted On:
31 March 2016 - 7:04am
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[1] Mostafa Shahin, Ricardo Gutierrez-Osuna, Beena Ahmed, "CLASSIFICATION OF BISYLLABIC LEXICAL STRESS PATTERNS IN DISORDERED SPEECH USING DEEP LEARNING", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1076. Accessed: Jul. 20, 2019.
@article{1076-16,
url = {http://sigport.org/1076},
author = {Mostafa Shahin; Ricardo Gutierrez-Osuna; Beena Ahmed },
publisher = {IEEE SigPort},
title = {CLASSIFICATION OF BISYLLABIC LEXICAL STRESS PATTERNS IN DISORDERED SPEECH USING DEEP LEARNING},
year = {2016} }
TY - EJOUR
T1 - CLASSIFICATION OF BISYLLABIC LEXICAL STRESS PATTERNS IN DISORDERED SPEECH USING DEEP LEARNING
AU - Mostafa Shahin; Ricardo Gutierrez-Osuna; Beena Ahmed
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1076
ER -
Mostafa Shahin, Ricardo Gutierrez-Osuna, Beena Ahmed. (2016). CLASSIFICATION OF BISYLLABIC LEXICAL STRESS PATTERNS IN DISORDERED SPEECH USING DEEP LEARNING. IEEE SigPort. http://sigport.org/1076
Mostafa Shahin, Ricardo Gutierrez-Osuna, Beena Ahmed, 2016. CLASSIFICATION OF BISYLLABIC LEXICAL STRESS PATTERNS IN DISORDERED SPEECH USING DEEP LEARNING. Available at: http://sigport.org/1076.
Mostafa Shahin, Ricardo Gutierrez-Osuna, Beena Ahmed. (2016). "CLASSIFICATION OF BISYLLABIC LEXICAL STRESS PATTERNS IN DISORDERED SPEECH USING DEEP LEARNING." Web.
1. Mostafa Shahin, Ricardo Gutierrez-Osuna, Beena Ahmed. CLASSIFICATION OF BISYLLABIC LEXICAL STRESS PATTERNS IN DISORDERED SPEECH USING DEEP LEARNING [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1076

AN ALTERNATIVE APPROACH FOR AUDITORY ATTENTION TRACKING USING SINGLE-TRIAL EEG


Auditory selective attention plays a central role in the human capacity to reliably process complex sounds in multi-source environments. Stimulus reconstruction has been widely used for the investigation of selective auditory attention using multichannel electroencephalography (EEG). In particular, the influence of attention on sound representations in the brain has been modeled by linear time-variant filters and have been used to track the attentional state of individuals in multi-source environments.

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Authors:
Bradley Ekin, Les Atlas, Majid Mirbagheri, Adrian KC Lee
Submitted On:
28 March 2016 - 1:43pm
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[1] Bradley Ekin, Les Atlas, Majid Mirbagheri, Adrian KC Lee, "AN ALTERNATIVE APPROACH FOR AUDITORY ATTENTION TRACKING USING SINGLE-TRIAL EEG", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1059. Accessed: Jul. 20, 2019.
@article{1059-16,
url = {http://sigport.org/1059},
author = {Bradley Ekin; Les Atlas; Majid Mirbagheri; Adrian KC Lee },
publisher = {IEEE SigPort},
title = {AN ALTERNATIVE APPROACH FOR AUDITORY ATTENTION TRACKING USING SINGLE-TRIAL EEG},
year = {2016} }
TY - EJOUR
T1 - AN ALTERNATIVE APPROACH FOR AUDITORY ATTENTION TRACKING USING SINGLE-TRIAL EEG
AU - Bradley Ekin; Les Atlas; Majid Mirbagheri; Adrian KC Lee
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1059
ER -
Bradley Ekin, Les Atlas, Majid Mirbagheri, Adrian KC Lee. (2016). AN ALTERNATIVE APPROACH FOR AUDITORY ATTENTION TRACKING USING SINGLE-TRIAL EEG. IEEE SigPort. http://sigport.org/1059
Bradley Ekin, Les Atlas, Majid Mirbagheri, Adrian KC Lee, 2016. AN ALTERNATIVE APPROACH FOR AUDITORY ATTENTION TRACKING USING SINGLE-TRIAL EEG. Available at: http://sigport.org/1059.
Bradley Ekin, Les Atlas, Majid Mirbagheri, Adrian KC Lee. (2016). "AN ALTERNATIVE APPROACH FOR AUDITORY ATTENTION TRACKING USING SINGLE-TRIAL EEG." Web.
1. Bradley Ekin, Les Atlas, Majid Mirbagheri, Adrian KC Lee. AN ALTERNATIVE APPROACH FOR AUDITORY ATTENTION TRACKING USING SINGLE-TRIAL EEG [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1059

Classification Of Respiratory Effort And Disordered Breathing During Sleep From Audio and Pulse Oximetry Signals


Sleep-disordered breathing (SDB) is a highly prevalent condition associated with many adverse health problems. As the current means of diagnosis (polysomnography) is obtrusive and ill-suited for mass screening of the population, we explore a minimal-contact, automatic approach that uses acoustics-based methods in conjunction with pulse oximetry. We present a two-stage method for automatically classifying breathing sounds produced during sleep to track respiratory effort and predicting disordered breathing events using respiratory effort durations and oxygen desaturations.

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Authors:
Brian R. Snider, Alexander Kain
Submitted On:
25 March 2016 - 1:09am
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[1] Brian R. Snider, Alexander Kain, "Classification Of Respiratory Effort And Disordered Breathing During Sleep From Audio and Pulse Oximetry Signals", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1042. Accessed: Jul. 20, 2019.
@article{1042-16,
url = {http://sigport.org/1042},
author = {Brian R. Snider; Alexander Kain },
publisher = {IEEE SigPort},
title = {Classification Of Respiratory Effort And Disordered Breathing During Sleep From Audio and Pulse Oximetry Signals},
year = {2016} }
TY - EJOUR
T1 - Classification Of Respiratory Effort And Disordered Breathing During Sleep From Audio and Pulse Oximetry Signals
AU - Brian R. Snider; Alexander Kain
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1042
ER -
Brian R. Snider, Alexander Kain. (2016). Classification Of Respiratory Effort And Disordered Breathing During Sleep From Audio and Pulse Oximetry Signals. IEEE SigPort. http://sigport.org/1042
Brian R. Snider, Alexander Kain, 2016. Classification Of Respiratory Effort And Disordered Breathing During Sleep From Audio and Pulse Oximetry Signals. Available at: http://sigport.org/1042.
Brian R. Snider, Alexander Kain. (2016). "Classification Of Respiratory Effort And Disordered Breathing During Sleep From Audio and Pulse Oximetry Signals." Web.
1. Brian R. Snider, Alexander Kain. Classification Of Respiratory Effort And Disordered Breathing During Sleep From Audio and Pulse Oximetry Signals [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1042

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