A digitized approach for amplitude-integrated electroencephalogram transformation towards a standardized procedure
The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG alg...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Chen, Chen [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Independent influences of excessive body weight and elevated blood pressure from childhood on left ventricular geometric remodeling in adulthood - Yan, Yinkun ELSEVIER, 2017, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:66 ; year:2021 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.bspc.2021.102433 |
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| 520 | |a The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. | ||
| 520 | |a The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. | ||
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| 650 | 7 | |a aEEG transformation |2 Elsevier | |
| 650 | 7 | |a Amplitude-integrated electroencephalography |2 Elsevier | |
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| 700 | 1 | |a Wang, Zeyu |4 oth | |
| 700 | 1 | |a Sun, Chenglu |4 oth | |
| 700 | 1 | |a Zhao, Xian |4 oth | |
| 700 | 1 | |a Fan, Jiahao |4 oth | |
| 700 | 1 | |a Niemarkt, Hendrik |4 oth | |
| 700 | 1 | |a Andriessen, Peter |4 oth | |
| 700 | 1 | |a Wang, Laishuan |4 oth | |
| 700 | 1 | |a Chen, Wei |4 oth | |
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10.1016/j.bspc.2021.102433 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001510.pica (DE-627)ELV053550900 (ELSEVIER)S1746-8094(21)00030-6 DE-627 ger DE-627 rakwb eng 610 VZ 630 640 610 VZ Chen, Chen verfasserin aut A digitized approach for amplitude-integrated electroencephalogram transformation towards a standardized procedure 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. Cerebral function monitor Elsevier aEEG transformation Elsevier Amplitude-integrated electroencephalography Elsevier Xu, Yan oth Wang, Zeyu oth Sun, Chenglu oth Zhao, Xian oth Fan, Jiahao oth Niemarkt, Hendrik oth Andriessen, Peter oth Wang, Laishuan oth Chen, Wei oth Enthalten in Elsevier Yan, Yinkun ELSEVIER Independent influences of excessive body weight and elevated blood pressure from childhood on left ventricular geometric remodeling in adulthood 2017 Amsterdam [u.a.] (DE-627)ELV020088493 volume:66 year:2021 pages:0 https://doi.org/10.1016/j.bspc.2021.102433 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_60 AR 66 2021 0 |
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10.1016/j.bspc.2021.102433 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001510.pica (DE-627)ELV053550900 (ELSEVIER)S1746-8094(21)00030-6 DE-627 ger DE-627 rakwb eng 610 VZ 630 640 610 VZ Chen, Chen verfasserin aut A digitized approach for amplitude-integrated electroencephalogram transformation towards a standardized procedure 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. Cerebral function monitor Elsevier aEEG transformation Elsevier Amplitude-integrated electroencephalography Elsevier Xu, Yan oth Wang, Zeyu oth Sun, Chenglu oth Zhao, Xian oth Fan, Jiahao oth Niemarkt, Hendrik oth Andriessen, Peter oth Wang, Laishuan oth Chen, Wei oth Enthalten in Elsevier Yan, Yinkun ELSEVIER Independent influences of excessive body weight and elevated blood pressure from childhood on left ventricular geometric remodeling in adulthood 2017 Amsterdam [u.a.] (DE-627)ELV020088493 volume:66 year:2021 pages:0 https://doi.org/10.1016/j.bspc.2021.102433 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_60 AR 66 2021 0 |
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10.1016/j.bspc.2021.102433 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001510.pica (DE-627)ELV053550900 (ELSEVIER)S1746-8094(21)00030-6 DE-627 ger DE-627 rakwb eng 610 VZ 630 640 610 VZ Chen, Chen verfasserin aut A digitized approach for amplitude-integrated electroencephalogram transformation towards a standardized procedure 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. Cerebral function monitor Elsevier aEEG transformation Elsevier Amplitude-integrated electroencephalography Elsevier Xu, Yan oth Wang, Zeyu oth Sun, Chenglu oth Zhao, Xian oth Fan, Jiahao oth Niemarkt, Hendrik oth Andriessen, Peter oth Wang, Laishuan oth Chen, Wei oth Enthalten in Elsevier Yan, Yinkun ELSEVIER Independent influences of excessive body weight and elevated blood pressure from childhood on left ventricular geometric remodeling in adulthood 2017 Amsterdam [u.a.] (DE-627)ELV020088493 volume:66 year:2021 pages:0 https://doi.org/10.1016/j.bspc.2021.102433 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_60 AR 66 2021 0 |
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10.1016/j.bspc.2021.102433 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001510.pica (DE-627)ELV053550900 (ELSEVIER)S1746-8094(21)00030-6 DE-627 ger DE-627 rakwb eng 610 VZ 630 640 610 VZ Chen, Chen verfasserin aut A digitized approach for amplitude-integrated electroencephalogram transformation towards a standardized procedure 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. Cerebral function monitor Elsevier aEEG transformation Elsevier Amplitude-integrated electroencephalography Elsevier Xu, Yan oth Wang, Zeyu oth Sun, Chenglu oth Zhao, Xian oth Fan, Jiahao oth Niemarkt, Hendrik oth Andriessen, Peter oth Wang, Laishuan oth Chen, Wei oth Enthalten in Elsevier Yan, Yinkun ELSEVIER Independent influences of excessive body weight and elevated blood pressure from childhood on left ventricular geometric remodeling in adulthood 2017 Amsterdam [u.a.] (DE-627)ELV020088493 volume:66 year:2021 pages:0 https://doi.org/10.1016/j.bspc.2021.102433 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_60 AR 66 2021 0 |
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10.1016/j.bspc.2021.102433 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001510.pica (DE-627)ELV053550900 (ELSEVIER)S1746-8094(21)00030-6 DE-627 ger DE-627 rakwb eng 610 VZ 630 640 610 VZ Chen, Chen verfasserin aut A digitized approach for amplitude-integrated electroencephalogram transformation towards a standardized procedure 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. Cerebral function monitor Elsevier aEEG transformation Elsevier Amplitude-integrated electroencephalography Elsevier Xu, Yan oth Wang, Zeyu oth Sun, Chenglu oth Zhao, Xian oth Fan, Jiahao oth Niemarkt, Hendrik oth Andriessen, Peter oth Wang, Laishuan oth Chen, Wei oth Enthalten in Elsevier Yan, Yinkun ELSEVIER Independent influences of excessive body weight and elevated blood pressure from childhood on left ventricular geometric remodeling in adulthood 2017 Amsterdam [u.a.] (DE-627)ELV020088493 volume:66 year:2021 pages:0 https://doi.org/10.1016/j.bspc.2021.102433 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_60 AR 66 2021 0 |
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The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. |
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The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. |
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The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms. |
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