Zobrazeno 1 - 10
of 15
pro vyhledávání: '"V. Nivitha Varghees"'
Publikováno v:
Healthcare Technology Letters (2018)
Accurate and reliable recognition of fundamental heart sounds (FHSs) plays a significant role in automated analysis of heart sound (HS) patterns. This Letter presents an automated wavelet-based FHS recognition (WFHSR) method using morphological and i
Externí odkaz:
https://doaj.org/article/cc5327e12e3945ae80bab4b6a7a936ec
Publikováno v:
Healthcare Technology Letters (2018)
Accurate and reliable recognition of fundamental heart sounds (FHSs) plays a significant role in automated analysis of heart sound (HS) patterns. This Letter presents an automated wavelet-based FHS recognition (WFHSR) method using morphological and i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::565277f43e7d45102bea1f5df6647b14
https://doi.org/10.1049/htl.2016.0109
https://doi.org/10.1049/htl.2016.0109
Publikováno v:
IEEE Sensors Journal. 17:3861-3872
Accurate measurement of heart sound and murmur parameters is of great importance in the automated analysis of phonocardiogram (PCG) signals. In this paper, we propose a novel unified PCG signal delineation and murmur classification method without the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42822988cb375068ea9dd50951bd014f
https://doi.org/10.1109/jsen.2017.2694970
https://doi.org/10.1109/jsen.2017.2694970
Publikováno v:
Biomedical Signal Processing and Control. 13:174-188
In automated heart sound analysis and diagnosis, a set of clinically valued parameters including sound intensity, frequency content, timing, duration, shape, systolic and diastolic intervals, the ratio of the first heart sound amplitude to second hea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5de2102ad3f990cfafadd9acf8bd499
https://doi.org/10.1016/j.bspc.2014.05.002
https://doi.org/10.1016/j.bspc.2014.05.002
Publikováno v:
2016 IEEE Students’ Technology Symposium (TechSym).
Phonocardiogram (PCG) segmentation is the crucial first step in automated heart sound analysis and diagnostic systems. Recently, the cardiac signals (including, electrocardiogram, phonocardiogram and photoplethysmogram) are simultaneously recorded fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1abbf3ff57a585a328a5ceb380f5a677
https://doi.org/10.1109/techsym.2016.7872701
https://doi.org/10.1109/techsym.2016.7872701
A robust multistage decision-based heart sound delineation (MDHSD) method is presented for automatically determining the boundaries and peaks of heart sounds (S1, S2, S3, and S4), systolic, and diastolic murmurs (early, mid, and late) and high-pitche
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::361b42615aac1488050254f91556781f
https://europepmc.org/articles/PMC4678455/
https://europepmc.org/articles/PMC4678455/
Publikováno v:
NCC
Detection and classification of heart murmurs play an important role in accurate diagnosis of different types of heart dysfunctions. In this paper, we present a noise-robust method for detection and classification of heart murmurs using stationary wa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f041cc584337f11fc731f4bcb59fa6d9
https://doi.org/10.1109/ncc.2015.7084904
https://doi.org/10.1109/ncc.2015.7084904
Publikováno v:
NCC
This paper presents an automated PCG signal delineation method for real-time wireless cardiac health monitoring and audio-visual stethoscope applications. The proposed method comprises the steps of: preprocessing, total variation filtering, smooth en
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c37b8c141375f4222c7918fdd70ab70d
https://doi.org/10.1109/ncc.2014.6811340
https://doi.org/10.1109/ncc.2014.6811340
Publikováno v:
2012 International Conference on Advances in Computing and Communications.
In this paper, we study a set of histogram and higher-order statistical (HOS) features for automatically identifying the presence of large background in the magnitude MR images. The robustness and discriminative power of each individual feature and c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ebd7553815ce8368b247450313402982
https://doi.org/10.1109/icacc.2012.17
https://doi.org/10.1109/icacc.2012.17
Publikováno v:
2012 International Conference on Advances in Computing & Communications; 1/ 1/2012, p82-85, 4p