Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment

In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS asses...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Weifeng Pan [verfasserIn] Aodi He [verfasserIn] Kaicheng Feng [verfasserIn] Yifan Li [verfasserIn] Dan Wu [verfasserIn] Guanzheng Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Congestive heart failure (CHF) heart rate variability (HRV) Hilbert-Huang transform (HHT) instantaneous frequency (IF) multi-frequency components analysis (MFCA)

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 7(2019), Seite 37708-37717
Übergeordnetes Werk:	volume:7 ; year:2019 ; pages:37708-37717

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2019.2896342

Katalog-ID:	DOAJ001919679

Internformat


LEADER	01000caa a22002652 4500
001	DOAJ001919679
003	DE-627
005	20230309164824.0
007	cr uuu---uuuuu
008	230225s2019 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.1109/ACCESS.2019.2896342 \|2 doi
035			\|a (DE-627)DOAJ001919679
035			\|a (DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a TK1-9971
100	0		\|a Weifeng Pan \|e verfasserin \|4 aut
245	1	0	\|a Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment
264		1	\|c 2019
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day.
650		4	\|a Congestive heart failure (CHF)
650		4	\|a heart rate variability (HRV)
650		4	\|a Hilbert-Huang transform (HHT)
650		4	\|a instantaneous frequency (IF)
650		4	\|a multi-frequency components analysis (MFCA)
653		0	\|a Electrical engineering. Electronics. Nuclear engineering
700	0		\|a Aodi He \|e verfasserin \|4 aut
700	0		\|a Kaicheng Feng \|e verfasserin \|4 aut
700	0		\|a Yifan Li \|e verfasserin \|4 aut
700	0		\|a Dan Wu \|e verfasserin \|4 aut
700	0		\|a Guanzheng Liu \|e verfasserin \|4 aut
773	0	8	\|i In \|t IEEE Access \|d IEEE, 2014 \|g 7(2019), Seite 37708-37717 \|w (DE-627)728440385 \|w (DE-600)2687964-5 \|x 21693536 \|7 nnns
773	1	8	\|g volume:7 \|g year:2019 \|g pages:37708-37717
856	4	0	\|u https://doi.org/10.1109/ACCESS.2019.2896342 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5 \|z kostenfrei
856	4	0	\|u https://ieeexplore.ieee.org/document/8649613/ \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/2169-3536 \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_11
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 7 \|j 2019 \|h 37708-37717

Indexfelder

author_variant	w p wp a h ah k f kf y l yl d w dw g l gl
matchkey_str	article:21693536:2019----::utfeunyopnnsnrpanvlerrtvraiiynieicne
hierarchy_sort_str	2019
callnumber-subject-code	TK
publishDate	2019
allfields	10.1109/ACCESS.2019.2896342 doi (DE-627)DOAJ001919679 (DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5 DE-627 ger DE-627 rakwb eng TK1-9971 Weifeng Pan verfasserin aut Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day. Congestive heart failure (CHF) heart rate variability (HRV) Hilbert-Huang transform (HHT) instantaneous frequency (IF) multi-frequency components analysis (MFCA) Electrical engineering. Electronics. Nuclear engineering Aodi He verfasserin aut Kaicheng Feng verfasserin aut Yifan Li verfasserin aut Dan Wu verfasserin aut Guanzheng Liu verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 37708-37717 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:37708-37717 https://doi.org/10.1109/ACCESS.2019.2896342 kostenfrei https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5 kostenfrei https://ieeexplore.ieee.org/document/8649613/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 37708-37717
spelling	10.1109/ACCESS.2019.2896342 doi (DE-627)DOAJ001919679 (DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5 DE-627 ger DE-627 rakwb eng TK1-9971 Weifeng Pan verfasserin aut Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day. Congestive heart failure (CHF) heart rate variability (HRV) Hilbert-Huang transform (HHT) instantaneous frequency (IF) multi-frequency components analysis (MFCA) Electrical engineering. Electronics. Nuclear engineering Aodi He verfasserin aut Kaicheng Feng verfasserin aut Yifan Li verfasserin aut Dan Wu verfasserin aut Guanzheng Liu verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 37708-37717 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:37708-37717 https://doi.org/10.1109/ACCESS.2019.2896342 kostenfrei https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5 kostenfrei https://ieeexplore.ieee.org/document/8649613/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 37708-37717
allfields_unstemmed	10.1109/ACCESS.2019.2896342 doi (DE-627)DOAJ001919679 (DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5 DE-627 ger DE-627 rakwb eng TK1-9971 Weifeng Pan verfasserin aut Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day. Congestive heart failure (CHF) heart rate variability (HRV) Hilbert-Huang transform (HHT) instantaneous frequency (IF) multi-frequency components analysis (MFCA) Electrical engineering. Electronics. Nuclear engineering Aodi He verfasserin aut Kaicheng Feng verfasserin aut Yifan Li verfasserin aut Dan Wu verfasserin aut Guanzheng Liu verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 37708-37717 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:37708-37717 https://doi.org/10.1109/ACCESS.2019.2896342 kostenfrei https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5 kostenfrei https://ieeexplore.ieee.org/document/8649613/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 37708-37717
allfieldsGer	10.1109/ACCESS.2019.2896342 doi (DE-627)DOAJ001919679 (DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5 DE-627 ger DE-627 rakwb eng TK1-9971 Weifeng Pan verfasserin aut Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day. Congestive heart failure (CHF) heart rate variability (HRV) Hilbert-Huang transform (HHT) instantaneous frequency (IF) multi-frequency components analysis (MFCA) Electrical engineering. Electronics. Nuclear engineering Aodi He verfasserin aut Kaicheng Feng verfasserin aut Yifan Li verfasserin aut Dan Wu verfasserin aut Guanzheng Liu verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 37708-37717 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:37708-37717 https://doi.org/10.1109/ACCESS.2019.2896342 kostenfrei https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5 kostenfrei https://ieeexplore.ieee.org/document/8649613/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 37708-37717
allfieldsSound	10.1109/ACCESS.2019.2896342 doi (DE-627)DOAJ001919679 (DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5 DE-627 ger DE-627 rakwb eng TK1-9971 Weifeng Pan verfasserin aut Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day. Congestive heart failure (CHF) heart rate variability (HRV) Hilbert-Huang transform (HHT) instantaneous frequency (IF) multi-frequency components analysis (MFCA) Electrical engineering. Electronics. Nuclear engineering Aodi He verfasserin aut Kaicheng Feng verfasserin aut Yifan Li verfasserin aut Dan Wu verfasserin aut Guanzheng Liu verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 37708-37717 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:37708-37717 https://doi.org/10.1109/ACCESS.2019.2896342 kostenfrei https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5 kostenfrei https://ieeexplore.ieee.org/document/8649613/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 37708-37717
language	English
source	In IEEE Access 7(2019), Seite 37708-37717 volume:7 year:2019 pages:37708-37717
sourceStr	In IEEE Access 7(2019), Seite 37708-37717 volume:7 year:2019 pages:37708-37717
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Congestive heart failure (CHF) heart rate variability (HRV) Hilbert-Huang transform (HHT) instantaneous frequency (IF) multi-frequency components analysis (MFCA) Electrical engineering. Electronics. Nuclear engineering
isfreeaccess_bool	true
container_title	IEEE Access
authorswithroles_txt_mv	Weifeng Pan @@aut@@ Aodi He @@aut@@ Kaicheng Feng @@aut@@ Yifan Li @@aut@@ Dan Wu @@aut@@ Guanzheng Liu @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
hierarchy_top_id	728440385
id	DOAJ001919679
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ001919679</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309164824.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230225s2019 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1109/ACCESS.2019.2896342</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ001919679</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TK1-9971</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Weifeng Pan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p &lt;; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p &lt;; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Congestive heart failure (CHF)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">heart rate variability (HRV)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Hilbert-Huang transform (HHT)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">instantaneous frequency (IF)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">multi-frequency components analysis (MFCA)</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Electrical engineering. Electronics. Nuclear engineering</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Aodi He</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Kaicheng Feng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yifan Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Dan Wu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Guanzheng Liu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">IEEE Access</subfield><subfield code="d">IEEE, 2014</subfield><subfield code="g">7(2019), Seite 37708-37717</subfield><subfield code="w">(DE-627)728440385</subfield><subfield code="w">(DE-600)2687964-5</subfield><subfield code="x">21693536</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:7</subfield><subfield code="g">year:2019</subfield><subfield code="g">pages:37708-37717</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1109/ACCESS.2019.2896342</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://ieeexplore.ieee.org/document/8649613/</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2169-3536</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">7</subfield><subfield code="j">2019</subfield><subfield code="h">37708-37717</subfield></datafield></record></collection>
callnumber-first	T - Technology
author	Weifeng Pan
spellingShingle	Weifeng Pan misc TK1-9971 misc Congestive heart failure (CHF) misc heart rate variability (HRV) misc Hilbert-Huang transform (HHT) misc instantaneous frequency (IF) misc multi-frequency components analysis (MFCA) misc Electrical engineering. Electronics. Nuclear engineering Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment
authorStr	Weifeng Pan
ppnlink_with_tag_str_mv	@@773@@(DE-627)728440385
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut aut aut
collection	DOAJ
remote_str	true
callnumber-label	TK1-9971
illustrated	Not Illustrated
issn	21693536
topic_title	TK1-9971 Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment Congestive heart failure (CHF) heart rate variability (HRV) Hilbert-Huang transform (HHT) instantaneous frequency (IF) multi-frequency components analysis (MFCA)
topic	misc TK1-9971 misc Congestive heart failure (CHF) misc heart rate variability (HRV) misc Hilbert-Huang transform (HHT) misc instantaneous frequency (IF) misc multi-frequency components analysis (MFCA) misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Congestive heart failure (CHF) misc heart rate variability (HRV) misc Hilbert-Huang transform (HHT) misc instantaneous frequency (IF) misc multi-frequency components analysis (MFCA) misc Electrical engineering. Electronics. Nuclear engineering
topic_browse	misc TK1-9971 misc Congestive heart failure (CHF) misc heart rate variability (HRV) misc Hilbert-Huang transform (HHT) misc instantaneous frequency (IF) misc multi-frequency components analysis (MFCA) misc Electrical engineering. Electronics. Nuclear engineering
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	IEEE Access
hierarchy_parent_id	728440385
hierarchy_top_title	IEEE Access
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)728440385 (DE-600)2687964-5
title	Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment
ctrlnum	(DE-627)DOAJ001919679 (DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5
title_full	Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment
author_sort	Weifeng Pan
journal	IEEE Access
journalStr	IEEE Access
callnumber-first-code	T
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2019
contenttype_str_mv	txt
container_start_page	37708
author_browse	Weifeng Pan Aodi He Kaicheng Feng Yifan Li Dan Wu Guanzheng Liu
container_volume	7
class	TK1-9971
format_se	Elektronische Aufsätze
author-letter	Weifeng Pan
doi_str_mv	10.1109/ACCESS.2019.2896342
author2-role	verfasserin
title_sort	multi-frequency components entropy as novel heart rate variability indices in congestive heart failure assessment
callnumber	TK1-9971
title_auth	Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment
abstract	In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day.
abstractGer	In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day.
abstract_unstemmed	In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p <; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p <; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700
title_short	Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment
url	https://doi.org/10.1109/ACCESS.2019.2896342 https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5 https://ieeexplore.ieee.org/document/8649613/ https://doaj.org/toc/2169-3536
remote_bool	true
author2	Aodi He Kaicheng Feng Yifan Li Dan Wu Guanzheng Liu
author2Str	Aodi He Kaicheng Feng Yifan Li Dan Wu Guanzheng Liu
ppnlink	728440385
callnumber-subject	TK - Electrical and Nuclear Engineering
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.1109/ACCESS.2019.2896342
callnumber-a	TK1-9971
up_date	2024-07-03T23:04:39.313Z
_version_	1803600925101654016
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ001919679</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309164824.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230225s2019 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1109/ACCESS.2019.2896342</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ001919679</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ7ebea7976ca141a1a3bffdcb021b54c5</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TK1-9971</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Weifeng Pan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In this paper, novel heart rate variability (HRV) indices were extracted for the autonomic nervous system (ANS) activity assessment in congestive heart failure (CHF). It has been reported that CHF is a chronic cardiovascular syndrome along with ANS dysfunction, and HRV is a useful tool for ANS assessment. The multi-frequency components Entropy (MFC-En), which is obtained by the Hilbert-Huang transform and the entropy algorithm, was proposed as novel HRV indices for analyzing ANS with CHF. This paper included 24-h HRV signals of 98 subjects collected with Holter (54 healthy, 12 low-risk CHF, and 32 high-risk CHF subjects). The MFC-En indices successfully showed a statistical significance between the control and CHF groups (p &lt;; 0.001). The CHF classification accuracy of the MFC-En was 86.7%, while the ratio of the lowand high-frequency power was only 79.6%. Moreover, statistical significances were found among the control, low-risk CHF, and high-risk CHF groups (p &lt;; 0.01). Therefore, the MFC-En is a useful tool for CHF assessment that revealed the ANS of CHF patient is more activated by measuring the complexity of the rhythms changes of the ANS throughout the day.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Congestive heart failure (CHF)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">heart rate variability (HRV)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Hilbert-Huang transform (HHT)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">instantaneous frequency (IF)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">multi-frequency components analysis (MFCA)</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Electrical engineering. Electronics. Nuclear engineering</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Aodi He</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Kaicheng Feng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yifan Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Dan Wu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Guanzheng Liu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">IEEE Access</subfield><subfield code="d">IEEE, 2014</subfield><subfield code="g">7(2019), Seite 37708-37717</subfield><subfield code="w">(DE-627)728440385</subfield><subfield code="w">(DE-600)2687964-5</subfield><subfield code="x">21693536</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:7</subfield><subfield code="g">year:2019</subfield><subfield code="g">pages:37708-37717</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1109/ACCESS.2019.2896342</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/7ebea7976ca141a1a3bffdcb021b54c5</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://ieeexplore.ieee.org/document/8649613/</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2169-3536</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">7</subfield><subfield code="j">2019</subfield><subfield code="h">37708-37717</subfield></datafield></record></collection>
score	7.3994236

Nicht das Richtige dabei?

Schreiben Sie uns!

Multi-Frequency Components Entropy as Novel Heart Rate Variability Indices in Congestive Heart Failure Assessment

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?