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Biomedical signal processing

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
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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: Jul. 23, 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: Jul. 23, 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
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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/2593. Accessed: Jul. 23, 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.

Paper Details

Authors:
Pratik Singh, Gayadhar Pradhan
Submitted On:
13 April 2018 - 12:49am
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ICASSP2018_pratik_ppt

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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: Jul. 23, 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
Short Link:
Type:
Event:
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ICASSP2018_pratik_ppt

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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: Jul. 23, 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
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
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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: Jul. 23, 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

A Mobile EEG System for Practical Applications


In this study, we present a new 64-channel mobile EEG system (NeusenW, Neuracle Inc.), and compare it to a state-of-the-art wired laboratory EEG system and evaluate the EEG signal quality. Previous studies were only performed on seated participants in laboratory environments, and only a very limited number focus on motion conditions. In this study, we instead implemented experiments in standing, walking and running conditions.

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Authors:
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao
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13 November 2017 - 4:08pm
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[1] Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao, "A Mobile EEG System for Practical Applications", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2341. Accessed: Jul. 23, 2019.
@article{2341-17,
url = {http://sigport.org/2341},
author = {Xiaoshan Huang; Erwei Yin; Yijun Wang; Rami Saab; Xiaorong Gao },
publisher = {IEEE SigPort},
title = {A Mobile EEG System for Practical Applications},
year = {2017} }
TY - EJOUR
T1 - A Mobile EEG System for Practical Applications
AU - Xiaoshan Huang; Erwei Yin; Yijun Wang; Rami Saab; Xiaorong Gao
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2341
ER -
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. (2017). A Mobile EEG System for Practical Applications. IEEE SigPort. http://sigport.org/2341
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao, 2017. A Mobile EEG System for Practical Applications. Available at: http://sigport.org/2341.
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. (2017). "A Mobile EEG System for Practical Applications." Web.
1. Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. A Mobile EEG System for Practical Applications [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2341

OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES


Individuals with auditory neuropathy spectrum disorder (ANSD) or auditory processing disorders (APDs) often suffer from temporal processing deficits leading to degraded speech perception. The situation becomes worse in the presence of background noise. Evidence exists that the exaggeration of speech envelope may enhance intelligibility, although a comprehensive evaluation of envelope enhancement algorithms is lacking.

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10 November 2017 - 7:17pm
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[1] , "OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2301. Accessed: Jul. 23, 2019.
@article{2301-17,
url = {http://sigport.org/2301},
author = { },
publisher = {IEEE SigPort},
title = {OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES},
year = {2017} }
TY - EJOUR
T1 - OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2301
ER -
. (2017). OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES. IEEE SigPort. http://sigport.org/2301
, 2017. OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES. Available at: http://sigport.org/2301.
. (2017). "OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES." Web.
1. . OBJECTIVE ASSESSMENT OF ENVELOPE ENHANCEMENT ALGORITHMS FOR ASSISTIVE HEARING DEVICES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2301

Heart Sound Segmentation using Switching Linear Dynamical Models


Localization of exact positions of the fundamental heart sounds (FHS) is an essential step towards automatic analysis of heart sound phonocardiogram (PCG) recordings, the automatic segmentation allows for data-driven classification of heart pathological events. Current approach using probabilistic models such as hidden Markov models (HMMs) has improved accuracy of heart sound segmentation.

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Authors:
Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu
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10 November 2017 - 10:14am
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[1] Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu, "Heart Sound Segmentation using Switching Linear Dynamical Models", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2293. Accessed: Jul. 23, 2019.
@article{2293-17,
url = {http://sigport.org/2293},
author = {Fuad Noman; Sh-Hussain Salleh; Chee-Ming Ting; Hadri Hu },
publisher = {IEEE SigPort},
title = {Heart Sound Segmentation using Switching Linear Dynamical Models},
year = {2017} }
TY - EJOUR
T1 - Heart Sound Segmentation using Switching Linear Dynamical Models
AU - Fuad Noman; Sh-Hussain Salleh; Chee-Ming Ting; Hadri Hu
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2293
ER -
Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu. (2017). Heart Sound Segmentation using Switching Linear Dynamical Models. IEEE SigPort. http://sigport.org/2293
Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu, 2017. Heart Sound Segmentation using Switching Linear Dynamical Models. Available at: http://sigport.org/2293.
Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu. (2017). "Heart Sound Segmentation using Switching Linear Dynamical Models." Web.
1. Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hu. Heart Sound Segmentation using Switching Linear Dynamical Models [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2293

ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD


Afternoon sleepiness in daily life reduces arousal level, performance, and so on. It has been cleared that short naps are effective to cancel the sleepiness. Sleep stage 2 is one of important factors about sleeping especially in short time nap. Sleep spindles are especially important hallmarks of sleep stage 2. Therefore, it is necessary to find a spindle for analysis in sleep stage 2.

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Authors:
Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa
Submitted On:
12 November 2017 - 9:20am
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GSIP_kawashima4.pdf

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[1] Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa, "ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2285. Accessed: Jul. 23, 2019.
@article{2285-17,
url = {http://sigport.org/2285},
author = {Takashi Yoshida; Mitsuo Hayashi; Naoyuki Aikawa },
publisher = {IEEE SigPort},
title = {ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD},
year = {2017} }
TY - EJOUR
T1 - ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD
AU - Takashi Yoshida; Mitsuo Hayashi; Naoyuki Aikawa
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2285
ER -
Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa. (2017). ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD. IEEE SigPort. http://sigport.org/2285
Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa, 2017. ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD. Available at: http://sigport.org/2285.
Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa. (2017). "ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD." Web.
1. Takashi Yoshida, Mitsuo Hayashi, Naoyuki Aikawa. ENHANCED SLEEP SPINDLE DETECTOR BASED ON THE FUJIMORI METHOD [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2285

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