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Biomedical signal processing

CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG


Presence of interictal epileptiform discharges (IED) in the electroencephalogram (EEG) is indicative of epilepsy. Automated
software for annotating EEGs of Patients with suspected epilepsy is substantial for diagnosis and management of epilepsy.
A large amount of data is needed for training and evaluating the performance of an effective IED detection system. IEDs occur
infrequently in the EEG of most patients, hence, interictal EEG recordings contain mostly background waveforms. As the first

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Authors:
Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.Brandon Westover
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13 April 2018 - 5:07pm
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[1] Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.Brandon Westover, "CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2766. Accessed: Apr. 22, 2019.
@article{2766-18,
url = {http://sigport.org/2766},
author = {Elham Bagheri; Jing Jin; Justin Dauwels; Sydney Cash; M.Brandon Westover },
publisher = {IEEE SigPort},
title = {CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG},
year = {2018} }
TY - EJOUR
T1 - CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG
AU - Elham Bagheri; Jing Jin; Justin Dauwels; Sydney Cash; M.Brandon Westover
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2766
ER -
Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.Brandon Westover. (2018). CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG. IEEE SigPort. http://sigport.org/2766
Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.Brandon Westover, 2018. CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG. Available at: http://sigport.org/2766.
Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.Brandon Westover. (2018). "CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG." Web.
1. Elham Bagheri, Jing Jin, Justin Dauwels, Sydney Cash, M.Brandon Westover. CLASSIFIER CASCADE TO AID IN DETECTION OF EPILEPTIFORM TRANSIENTS IN INTERICTAL EEG [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2766

Ear-EEG for Detecting Inter-brain Synchronisation in Continuous Cooperative Multi-person Scenarios


The hyperscanning method simultaneously acquires and relates
cerebral data from two participants while performing
cooperative activities. The aim of this work is to evaluate
the performance of our novel EEG recording concept,
termed ear-EEG, against on-scalp EEG as an alternative,
user-friendly data acquisition approach for hyperscanning, in
the task of identifying the most robust, EEG subbands for
inter-individual neuronal synchrony detection in cooperative
multi-player gaming. This is achieved through the estimation

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Authors:
Valentin Goverdovsky
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13 April 2018 - 9:40am
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[1] Valentin Goverdovsky, "Ear-EEG for Detecting Inter-brain Synchronisation in Continuous Cooperative Multi-person Scenarios", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2702. Accessed: Apr. 22, 2019.
@article{2702-18,
url = {http://sigport.org/2702},
author = {Valentin Goverdovsky },
publisher = {IEEE SigPort},
title = {Ear-EEG for Detecting Inter-brain Synchronisation in Continuous Cooperative Multi-person Scenarios},
year = {2018} }
TY - EJOUR
T1 - Ear-EEG for Detecting Inter-brain Synchronisation in Continuous Cooperative Multi-person Scenarios
AU - Valentin Goverdovsky
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2702
ER -
Valentin Goverdovsky. (2018). Ear-EEG for Detecting Inter-brain Synchronisation in Continuous Cooperative Multi-person Scenarios. IEEE SigPort. http://sigport.org/2702
Valentin Goverdovsky, 2018. Ear-EEG for Detecting Inter-brain Synchronisation in Continuous Cooperative Multi-person Scenarios. Available at: http://sigport.org/2702.
Valentin Goverdovsky. (2018). "Ear-EEG for Detecting Inter-brain Synchronisation in Continuous Cooperative Multi-person Scenarios." Web.
1. Valentin Goverdovsky. Ear-EEG for Detecting Inter-brain Synchronisation in Continuous Cooperative Multi-person Scenarios [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2702

UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES


Parkinson’s disease (PD) produces several speech impairments in the patients. Automatic classification of PD patients is performed considering speech recordings collected in non- controlled acoustic conditions during normal phone calls in a unobtrusive way. A speech enhancement algorithm is applied to improve the quality of the signals. Two different classification approaches are considered: the classification of PD patients and healthy speakers and a multi-class experiment to classify patients in several stages of the disease.

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Authors:
T. Arias-Vergara, J.C. Vásquez-Correa, J.R. Orozco-Arroyave, P. Klumpp, E. Noeth
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13 April 2018 - 7:08am
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[1] T. Arias-Vergara, J.C. Vásquez-Correa, J.R. Orozco-Arroyave, P. Klumpp, E. Noeth, "UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2688. Accessed: Apr. 22, 2019.
@article{2688-18,
url = {http://sigport.org/2688},
author = {T. Arias-Vergara; J.C. Vásquez-Correa; J.R. Orozco-Arroyave; P. Klumpp; E. Noeth },
publisher = {IEEE SigPort},
title = {UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES},
year = {2018} }
TY - EJOUR
T1 - UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES
AU - T. Arias-Vergara; J.C. Vásquez-Correa; J.R. Orozco-Arroyave; P. Klumpp; E. Noeth
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2688
ER -
T. Arias-Vergara, J.C. Vásquez-Correa, J.R. Orozco-Arroyave, P. Klumpp, E. Noeth. (2018). UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES. IEEE SigPort. http://sigport.org/2688
T. Arias-Vergara, J.C. Vásquez-Correa, J.R. Orozco-Arroyave, P. Klumpp, E. Noeth, 2018. UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES. Available at: http://sigport.org/2688.
T. Arias-Vergara, J.C. Vásquez-Correa, J.R. Orozco-Arroyave, P. Klumpp, E. Noeth. (2018). "UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES." Web.
1. T. Arias-Vergara, J.C. Vásquez-Correa, J.R. Orozco-Arroyave, P. Klumpp, E. Noeth. UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2688

Diabetic Retinopathy Detection Based on Deep Convolutional Neural Networks

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Authors:
Yi-Wei Chen, Tung-Yu Wu, Wing-Hung Wong, Chen-Yi Lee
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13 April 2018 - 2:52am
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[1] Yi-Wei Chen, Tung-Yu Wu, Wing-Hung Wong, Chen-Yi Lee, "Diabetic Retinopathy Detection Based on Deep Convolutional Neural Networks", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2627. Accessed: Apr. 22, 2019.
@article{2627-18,
url = {http://sigport.org/2627},
author = {Yi-Wei Chen; Tung-Yu Wu; Wing-Hung Wong; Chen-Yi Lee },
publisher = {IEEE SigPort},
title = {Diabetic Retinopathy Detection Based on Deep Convolutional Neural Networks},
year = {2018} }
TY - EJOUR
T1 - Diabetic Retinopathy Detection Based on Deep Convolutional Neural Networks
AU - Yi-Wei Chen; Tung-Yu Wu; Wing-Hung Wong; Chen-Yi Lee
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2627
ER -
Yi-Wei Chen, Tung-Yu Wu, Wing-Hung Wong, Chen-Yi Lee. (2018). Diabetic Retinopathy Detection Based on Deep Convolutional Neural Networks. IEEE SigPort. http://sigport.org/2627
Yi-Wei Chen, Tung-Yu Wu, Wing-Hung Wong, Chen-Yi Lee, 2018. Diabetic Retinopathy Detection Based on Deep Convolutional Neural Networks. Available at: http://sigport.org/2627.
Yi-Wei Chen, Tung-Yu Wu, Wing-Hung Wong, Chen-Yi Lee. (2018). "Diabetic Retinopathy Detection Based on Deep Convolutional Neural Networks." Web.
1. Yi-Wei Chen, Tung-Yu Wu, Wing-Hung Wong, Chen-Yi Lee. Diabetic Retinopathy Detection Based on Deep Convolutional Neural Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2627

Cognitive Analysis of Working Memory Load from EEG, by a Deep Recurrent Neural Network


One of the common modalities for observing mental activity is electroencephalogram (EEG) signals. However, EEG recording is highly susceptible to various sources of noise and to inter-subject differences. In order to solve these problems, we present a deep recurrent neural network (RNN) architecture to learn robust features and predict the levels of the cognitive load from EEG recordings. Using a deep learning approach, we first transform the EEG time series into a sequence of multispectral images which carries spatial information.

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Authors:
Vassilis Athitsos, Nityananda Pradhan, Arabinda Mishra, K.R.Rao
Submitted On:
13 April 2018 - 1:42am
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[1] Vassilis Athitsos, Nityananda Pradhan, Arabinda Mishra, K.R.Rao, "Cognitive Analysis of Working Memory Load from EEG, by a Deep Recurrent Neural Network", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2607. Accessed: Apr. 22, 2019.
@article{2607-18,
url = {http://sigport.org/2607},
author = {Vassilis Athitsos; Nityananda Pradhan; Arabinda Mishra; K.R.Rao },
publisher = {IEEE SigPort},
title = {Cognitive Analysis of Working Memory Load from EEG, by a Deep Recurrent Neural Network},
year = {2018} }
TY - EJOUR
T1 - Cognitive Analysis of Working Memory Load from EEG, by a Deep Recurrent Neural Network
AU - Vassilis Athitsos; Nityananda Pradhan; Arabinda Mishra; K.R.Rao
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2607
ER -
Vassilis Athitsos, Nityananda Pradhan, Arabinda Mishra, K.R.Rao. (2018). Cognitive Analysis of Working Memory Load from EEG, by a Deep Recurrent Neural Network. IEEE SigPort. http://sigport.org/2607
Vassilis Athitsos, Nityananda Pradhan, Arabinda Mishra, K.R.Rao, 2018. Cognitive Analysis of Working Memory Load from EEG, by a Deep Recurrent Neural Network. Available at: http://sigport.org/2607.
Vassilis Athitsos, Nityananda Pradhan, Arabinda Mishra, K.R.Rao. (2018). "Cognitive Analysis of Working Memory Load from EEG, by a Deep Recurrent Neural Network." Web.
1. Vassilis Athitsos, Nityananda Pradhan, Arabinda Mishra, K.R.Rao. Cognitive Analysis of Working Memory Load from EEG, by a Deep Recurrent Neural Network [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2607

EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING


In the presented work, noisy ECG signal is decomposed into variational mode functions (VMFs) using variational mode decomposition (VMD) technique. The decomposed VMFs represents the different frequency band of the noisy ECG signal. The non-local similarity present in each VMFs were exploited using NLM estimation for effective ECG denoising. The two-stage VMD decomposition and NLM estimation process is performed on different set of VMFs at both stages. The proposed method is tested upon MIT-BIH Arrhythmia database.

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Authors:
Pratik Singh, Gayadhar Pradhan
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13 April 2018 - 12:49am
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[1] Pratik Singh, Gayadhar Pradhan, "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2594. Accessed: Apr. 22, 2019.
@article{2594-18,
url = {http://sigport.org/2594},
author = {Pratik Singh; Gayadhar Pradhan },
publisher = {IEEE SigPort},
title = {EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING},
year = {2018} }
TY - EJOUR
T1 - EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING
AU - Pratik Singh; Gayadhar Pradhan
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2594
ER -
Pratik Singh, Gayadhar Pradhan. (2018). EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. IEEE SigPort. http://sigport.org/2594
Pratik Singh, Gayadhar Pradhan, 2018. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. Available at: http://sigport.org/2594.
Pratik Singh, Gayadhar Pradhan. (2018). "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING." Web.
1. Pratik Singh, Gayadhar Pradhan. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2594

EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING


In the presented work, noisy ECG signal is decomposed into variational mode functions (VMFs) using variational mode decomposition (VMD) technique. The decomposed VMFs represents the different frequency band of the noisy ECG signal. The non-local similarity present in each VMFs were exploited using NLM estimation for effective ECG denoising. The two-stage VMD decomposition and NLM estimation process is performed on different set of VMFs at both stages. The proposed method is tested upon MIT-BIH Arrhythmia database.

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Authors:
Pratik Singh, Gayadhar Pradhan
Submitted On:
13 April 2018 - 12:49am
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[1] Pratik Singh, Gayadhar Pradhan, "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2593. Accessed: Apr. 22, 2019.
@article{2593-18,
url = {http://sigport.org/2593},
author = {Pratik Singh; Gayadhar Pradhan },
publisher = {IEEE SigPort},
title = {EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING},
year = {2018} }
TY - EJOUR
T1 - EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING
AU - Pratik Singh; Gayadhar Pradhan
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2593
ER -
Pratik Singh, Gayadhar Pradhan. (2018). EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. IEEE SigPort. http://sigport.org/2593
Pratik Singh, Gayadhar Pradhan, 2018. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. Available at: http://sigport.org/2593.
Pratik Singh, Gayadhar Pradhan. (2018). "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING." Web.
1. Pratik Singh, Gayadhar Pradhan. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2593

EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING


In the presented work, noisy ECG signal is decomposed into variational mode functions (VMFs) using variational mode decomposition (VMD) technique. The decomposed VMFs represents the different frequency band of the noisy ECG signal. The non-local similarity present in each VMFs were exploited using NLM estimation for effective ECG denoising. The two-stage VMD decomposition and NLM estimation process is performed on different set of VMFs at both stages. The proposed method is tested upon MIT-BIH Arrhythmia database.

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Authors:
Pratik Singh, Gayadhar Pradhan
Submitted On:
13 April 2018 - 12:49am
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[1] Pratik Singh, Gayadhar Pradhan, "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2592. Accessed: Apr. 22, 2019.
@article{2592-18,
url = {http://sigport.org/2592},
author = {Pratik Singh; Gayadhar Pradhan },
publisher = {IEEE SigPort},
title = {EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING},
year = {2018} }
TY - EJOUR
T1 - EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING
AU - Pratik Singh; Gayadhar Pradhan
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2592
ER -
Pratik Singh, Gayadhar Pradhan. (2018). EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. IEEE SigPort. http://sigport.org/2592
Pratik Singh, Gayadhar Pradhan, 2018. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. Available at: http://sigport.org/2592.
Pratik Singh, Gayadhar Pradhan. (2018). "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING." Web.
1. Pratik Singh, Gayadhar Pradhan. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2592

EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING


In the presented work, noisy ECG signal is decomposed into variational mode functions (VMFs) using variational mode decomposition (VMD) technique. The decomposed VMFs represents the different frequency band of the noisy ECG signal. The non-local similarity present in each VMFs were exploited using NLM estimation for effective ECG denoising. The two-stage VMD decomposition and NLM estimation process is performed on different set of VMFs at both stages. The proposed method is tested upon MIT-BIH Arrhythmia database.

Paper Details

Authors:
Pratik Singh, Gayadhar Pradhan
Submitted On:
13 April 2018 - 12:49am
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Type:
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[1] Pratik Singh, Gayadhar Pradhan, "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2591. Accessed: Apr. 22, 2019.
@article{2591-18,
url = {http://sigport.org/2591},
author = {Pratik Singh; Gayadhar Pradhan },
publisher = {IEEE SigPort},
title = {EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING},
year = {2018} }
TY - EJOUR
T1 - EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING
AU - Pratik Singh; Gayadhar Pradhan
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2591
ER -
Pratik Singh, Gayadhar Pradhan. (2018). EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. IEEE SigPort. http://sigport.org/2591
Pratik Singh, Gayadhar Pradhan, 2018. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. Available at: http://sigport.org/2591.
Pratik Singh, Gayadhar Pradhan. (2018). "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING." Web.
1. Pratik Singh, Gayadhar Pradhan. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2591

EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING


In the presented work, noisy ECG signal is decomposed into variational mode functions (VMFs) using variational mode decomposition (VMD) technique. The decomposed VMFs represents the different frequency band of the noisy ECG signal. The non-local similarity present in each VMFs were exploited using NLM estimation for effective ECG denoising. The two-stage VMD decomposition and NLM estimation process is performed on different set of VMFs at both stages. The proposed method is tested upon MIT-BIH Arrhythmia database.

Paper Details

Authors:
Pratik Singh, Gayadhar Pradhan
Submitted On:
13 April 2018 - 12:49am
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Type:
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[1] Pratik Singh, Gayadhar Pradhan, "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2590. Accessed: Apr. 22, 2019.
@article{2590-18,
url = {http://sigport.org/2590},
author = {Pratik Singh; Gayadhar Pradhan },
publisher = {IEEE SigPort},
title = {EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING},
year = {2018} }
TY - EJOUR
T1 - EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING
AU - Pratik Singh; Gayadhar Pradhan
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2590
ER -
Pratik Singh, Gayadhar Pradhan. (2018). EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. IEEE SigPort. http://sigport.org/2590
Pratik Singh, Gayadhar Pradhan, 2018. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING. Available at: http://sigport.org/2590.
Pratik Singh, Gayadhar Pradhan. (2018). "EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING." Web.
1. Pratik Singh, Gayadhar Pradhan. EXPLORING THE NON-LOCAL SIMILARITY PRESENT IN VARIATIONAL MODE FUNCTIONS FOR EFFECTIVE ECG DENOISING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2590

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