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Biomedical signal processing

ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION

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Authors:
Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady
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22 November 2018 - 7:05pm
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[1] Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady, "ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3723. Accessed: Jul. 23, 2019.
@article{3723-18,
url = {http://sigport.org/3723},
author = {Ana P. Costa; Jakob S. Møller; Helle K. Iversen; Sadasivan Puthusserypady },
publisher = {IEEE SigPort},
title = {ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION},
year = {2018} }
TY - EJOUR
T1 - ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION
AU - Ana P. Costa; Jakob S. Møller; Helle K. Iversen; Sadasivan Puthusserypady
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3723
ER -
Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady. (2018). ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION. IEEE SigPort. http://sigport.org/3723
Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady, 2018. ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION. Available at: http://sigport.org/3723.
Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady. (2018). "ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION." Web.
1. Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady. ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3723

ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY

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26 November 2018 - 7:02pm
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globalsip.pdf

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[1] , "ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3722. Accessed: Jul. 23, 2019.
@article{3722-18,
url = {http://sigport.org/3722},
author = { },
publisher = {IEEE SigPort},
title = {ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY},
year = {2018} }
TY - EJOUR
T1 - ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3722
ER -
. (2018). ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY. IEEE SigPort. http://sigport.org/3722
, 2018. ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY. Available at: http://sigport.org/3722.
. (2018). "ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY." Web.
1. . ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3722

OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS


Speech production involves the synchronization of neural activity between the speech centers of the brain and the oralmotor system, allowing for the conversion of thoughts into

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Authors:
Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang
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22 November 2018 - 2:18pm
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[1] Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang, "OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3719. Accessed: Jul. 23, 2019.
@article{3719-18,
url = {http://sigport.org/3719},
author = {Debadatta Dash; Paul Ferrari; Saleem Malik; Jun Wang },
publisher = {IEEE SigPort},
title = {OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS},
year = {2018} }
TY - EJOUR
T1 - OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS
AU - Debadatta Dash; Paul Ferrari; Saleem Malik; Jun Wang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3719
ER -
Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang. (2018). OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS. IEEE SigPort. http://sigport.org/3719
Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang, 2018. OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS. Available at: http://sigport.org/3719.
Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang. (2018). "OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS." Web.
1. Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang. OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3719

Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring


To achieve real-time electrocardiography (ECG) telemonitoring, we need to overcome the scarce bandwidth. Compressed sensing (CS) emerges as a promising technique to greatly compress ECG signal with little computation. Furthermore, with edge-classification, we can reduce the data rate by transmitting abnormal ECG signals only. However, there are three main limitations: limited number of labeled ECG signal, tight battery constraint of edge devices and low response time requirement.

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Authors:
Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu
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12 December 2018 - 10:09pm
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[1] Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu, "Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3718. Accessed: Jul. 23, 2019.
@article{3718-18,
url = {http://sigport.org/3718},
author = {Kai-Chieh Hsu; Bo-Hong Cho; Ching-Yao Chou; and An-Yeu (Andy) Wu },
publisher = {IEEE SigPort},
title = {Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring},
year = {2018} }
TY - EJOUR
T1 - Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring
AU - Kai-Chieh Hsu; Bo-Hong Cho; Ching-Yao Chou; and An-Yeu (Andy) Wu
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3718
ER -
Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu. (2018). Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring. IEEE SigPort. http://sigport.org/3718
Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu, 2018. Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring. Available at: http://sigport.org/3718.
Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu. (2018). "Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring." Web.
1. Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu. Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3718

A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS


Canonical correlation analysis (CCA) is a data-driven method that has been successfully used in functional magnetic resonance imaging (fMRI) data analysis. Standard CCA extracts meaningful information from a data set by seeking pairs of linear combinations from two sets of variables with maximum pairwise correlation. So far, however, this method has been used without incorporating prior information available for fMRI data. In this paper, we address this issue by proposing a new CCA method named PCCA (for projection CCA).

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Authors:
Muhammad Ali Qadar and Abd-Krim Seghouane
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6 October 2018 - 1:34pm
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[1] Muhammad Ali Qadar and Abd-Krim Seghouane, "A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3487. Accessed: Jul. 23, 2019.
@article{3487-18,
url = {http://sigport.org/3487},
author = {Muhammad Ali Qadar and Abd-Krim Seghouane },
publisher = {IEEE SigPort},
title = {A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS},
year = {2018} }
TY - EJOUR
T1 - A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS
AU - Muhammad Ali Qadar and Abd-Krim Seghouane
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3487
ER -
Muhammad Ali Qadar and Abd-Krim Seghouane. (2018). A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS. IEEE SigPort. http://sigport.org/3487
Muhammad Ali Qadar and Abd-Krim Seghouane, 2018. A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS. Available at: http://sigport.org/3487.
Muhammad Ali Qadar and Abd-Krim Seghouane. (2018). "A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS." Web.
1. Muhammad Ali Qadar and Abd-Krim Seghouane. A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3487

Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy


Fourier Transform Interferometry (FTI) is an interferometric procedure for acquiring HyperSpectral (HS) data. Recently, it has been observed that the light source highlighting a (biologic) sample can be coded before the FTI acquisition in a procedure called Coded Illumination-FTI (CI-FTI). This turns HS data reconstruction into a Compressive Sensing (CS) problem regularized by the sparsity of the HS data. CI-FTI combines the high spectral resolution of FTI with the advantages of reduced-light-exposure imaging in biology.

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Authors:
Amirafshar Moshtaghpour, Laurent Jacques
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4 October 2018 - 9:29am
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Compressive Fourier Transform Interferometry

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[1] Amirafshar Moshtaghpour, Laurent Jacques, "Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3405. Accessed: Jul. 23, 2019.
@article{3405-18,
url = {http://sigport.org/3405},
author = {Amirafshar Moshtaghpour; Laurent Jacques },
publisher = {IEEE SigPort},
title = {Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy},
year = {2018} }
TY - EJOUR
T1 - Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy
AU - Amirafshar Moshtaghpour; Laurent Jacques
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3405
ER -
Amirafshar Moshtaghpour, Laurent Jacques. (2018). Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy. IEEE SigPort. http://sigport.org/3405
Amirafshar Moshtaghpour, Laurent Jacques, 2018. Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy. Available at: http://sigport.org/3405.
Amirafshar Moshtaghpour, Laurent Jacques. (2018). "Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy." Web.
1. Amirafshar Moshtaghpour, Laurent Jacques. Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3405

Enhancing the Reliability of Large-Scale Multiuser Molecular Communication Systems

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Authors:
Maheshi Buddhinee Dissanayake, Yansha Deng, Arumugam Nallanathan, Maged Elkashlan, and Urbashi Mitra
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20 June 2018 - 9:29am
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[1] Maheshi Buddhinee Dissanayake, Yansha Deng, Arumugam Nallanathan, Maged Elkashlan, and Urbashi Mitra, "Enhancing the Reliability of Large-Scale Multiuser Molecular Communication Systems", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3252. Accessed: Jul. 23, 2019.
@article{3252-18,
url = {http://sigport.org/3252},
author = {Maheshi Buddhinee Dissanayake; Yansha Deng; Arumugam Nallanathan; Maged Elkashlan; and Urbashi Mitra },
publisher = {IEEE SigPort},
title = {Enhancing the Reliability of Large-Scale Multiuser Molecular Communication Systems},
year = {2018} }
TY - EJOUR
T1 - Enhancing the Reliability of Large-Scale Multiuser Molecular Communication Systems
AU - Maheshi Buddhinee Dissanayake; Yansha Deng; Arumugam Nallanathan; Maged Elkashlan; and Urbashi Mitra
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3252
ER -
Maheshi Buddhinee Dissanayake, Yansha Deng, Arumugam Nallanathan, Maged Elkashlan, and Urbashi Mitra. (2018). Enhancing the Reliability of Large-Scale Multiuser Molecular Communication Systems. IEEE SigPort. http://sigport.org/3252
Maheshi Buddhinee Dissanayake, Yansha Deng, Arumugam Nallanathan, Maged Elkashlan, and Urbashi Mitra, 2018. Enhancing the Reliability of Large-Scale Multiuser Molecular Communication Systems. Available at: http://sigport.org/3252.
Maheshi Buddhinee Dissanayake, Yansha Deng, Arumugam Nallanathan, Maged Elkashlan, and Urbashi Mitra. (2018). "Enhancing the Reliability of Large-Scale Multiuser Molecular Communication Systems." Web.
1. Maheshi Buddhinee Dissanayake, Yansha Deng, Arumugam Nallanathan, Maged Elkashlan, and Urbashi Mitra. Enhancing the Reliability of Large-Scale Multiuser Molecular Communication Systems [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3252

Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection using phonocardiogarm signals


In this paper, we present completely automated cardiac anomaly detection for remote screening of cardio-vascular abnormality using Phonocardiogram (PCG) or heart sound signal. Even though PCG contains significant and vital cardiac health information and cardiac abnormality signature, the presence of substantial noise does not guarantee highly effective analysis of cardiac condition. Our proposed method intelligently identifies and eliminates noisy PCG signal and consequently detects pathological abnormality condition. We further present a unified model of hybrid feature selection method.

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Authors:
Arijit Ukil, Soma Bnadyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal
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27 April 2018 - 2:44am
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ICASSP_Paper_2030_final.pdf

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[1] Arijit Ukil, Soma Bnadyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal, "Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection using phonocardiogarm signals", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3184. Accessed: Jul. 23, 2019.
@article{3184-18,
url = {http://sigport.org/3184},
author = {Arijit Ukil; Soma Bnadyopadhyay; Chetanya Puri; Rituraj Singh; Arpan Pal },
publisher = {IEEE SigPort},
title = {Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection using phonocardiogarm signals},
year = {2018} }
TY - EJOUR
T1 - Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection using phonocardiogarm signals
AU - Arijit Ukil; Soma Bnadyopadhyay; Chetanya Puri; Rituraj Singh; Arpan Pal
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3184
ER -
Arijit Ukil, Soma Bnadyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal. (2018). Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection using phonocardiogarm signals. IEEE SigPort. http://sigport.org/3184
Arijit Ukil, Soma Bnadyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal, 2018. Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection using phonocardiogarm signals. Available at: http://sigport.org/3184.
Arijit Ukil, Soma Bnadyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal. (2018). "Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection using phonocardiogarm signals." Web.
1. Arijit Ukil, Soma Bnadyopadhyay, Chetanya Puri, Rituraj Singh, Arpan Pal. Effective Noise Removal and Unified Model of Hybrid Feature Space Optimization for Automated Cardiac Anomaly Detection using phonocardiogarm signals [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3184

EPILEPTIC STATE SEGMENTATION WITH TEMPORAL-CONSTRAINED CLUSTERING

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24 April 2018 - 7:37am
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[1] , "EPILEPTIC STATE SEGMENTATION WITH TEMPORAL-CONSTRAINED CLUSTERING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3165. Accessed: Jul. 23, 2019.
@article{3165-18,
url = {http://sigport.org/3165},
author = { },
publisher = {IEEE SigPort},
title = {EPILEPTIC STATE SEGMENTATION WITH TEMPORAL-CONSTRAINED CLUSTERING},
year = {2018} }
TY - EJOUR
T1 - EPILEPTIC STATE SEGMENTATION WITH TEMPORAL-CONSTRAINED CLUSTERING
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3165
ER -
. (2018). EPILEPTIC STATE SEGMENTATION WITH TEMPORAL-CONSTRAINED CLUSTERING. IEEE SigPort. http://sigport.org/3165
, 2018. EPILEPTIC STATE SEGMENTATION WITH TEMPORAL-CONSTRAINED CLUSTERING. Available at: http://sigport.org/3165.
. (2018). "EPILEPTIC STATE SEGMENTATION WITH TEMPORAL-CONSTRAINED CLUSTERING." Web.
1. . EPILEPTIC STATE SEGMENTATION WITH TEMPORAL-CONSTRAINED CLUSTERING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3165

Time-Varying Delay Estimation using Common Local All-Pass Filters with Application to Surface Electromyography


Estimation of conduction velocity (CV) is an important task in the analysis of surface electromyography (sEMG). The problem can be framed as estimation of a time-varying delay (TVD) between electrode recordings. In this paper we present an algorithm which incorporates information from multiple electrodes into a single TVD estimation. The algorithm uses a common all-pass filter to relate two groups of signals at a local level.

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Authors:
Adrian Bingham, Thierry Blu, Beth Jelfs
Submitted On:
22 April 2018 - 12:58am
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[1] Adrian Bingham, Thierry Blu, Beth Jelfs, "Time-Varying Delay Estimation using Common Local All-Pass Filters with Application to Surface Electromyography", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3128. Accessed: Jul. 23, 2019.
@article{3128-18,
url = {http://sigport.org/3128},
author = {Adrian Bingham; Thierry Blu; Beth Jelfs },
publisher = {IEEE SigPort},
title = {Time-Varying Delay Estimation using Common Local All-Pass Filters with Application to Surface Electromyography},
year = {2018} }
TY - EJOUR
T1 - Time-Varying Delay Estimation using Common Local All-Pass Filters with Application to Surface Electromyography
AU - Adrian Bingham; Thierry Blu; Beth Jelfs
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3128
ER -
Adrian Bingham, Thierry Blu, Beth Jelfs. (2018). Time-Varying Delay Estimation using Common Local All-Pass Filters with Application to Surface Electromyography. IEEE SigPort. http://sigport.org/3128
Adrian Bingham, Thierry Blu, Beth Jelfs, 2018. Time-Varying Delay Estimation using Common Local All-Pass Filters with Application to Surface Electromyography. Available at: http://sigport.org/3128.
Adrian Bingham, Thierry Blu, Beth Jelfs. (2018). "Time-Varying Delay Estimation using Common Local All-Pass Filters with Application to Surface Electromyography." Web.
1. Adrian Bingham, Thierry Blu, Beth Jelfs. Time-Varying Delay Estimation using Common Local All-Pass Filters with Application to Surface Electromyography [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3128

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