Arrhythmia classification using Mahalanobis distance based improved Fuzzy C-Means clustering for mobile health monitoring systems

Research output: Contribution to journal › Article › peer-review

Keywords

@article{a3b0baf8458349589f822236d79f6c60,

title = "Arrhythmia classification using Mahalanobis distance based improved Fuzzy C-Means clustering for mobile health monitoring systems",

keywords = "E-Health, Arrhythmia, Fuzzy C-Means clustering, Body area network, Mahalanobis-Taguchi System (MTS)",

author = "Haldar, \{Nur Al Hasan\} and Khan, \{Farrukh Aslam\} and Aftab Ali and Haider Abbas",

year = "2017",

month = jan,

day = "12",

doi = "10.1016/j.neucom.2016.08.042",

language = "English",

volume = "220",

pages = "221--235",

journal = "Neurocomputing",

issn = "0925-2312",

publisher = "Elsevier BV",

}

TY - JOUR

T1 - Arrhythmia classification using Mahalanobis distance based improved Fuzzy C-Means clustering for mobile health monitoring systems

AU - Haldar, Nur Al Hasan

AU - Khan, Farrukh Aslam

AU - Ali, Aftab

AU - Abbas, Haider

PY - 2017/1/12

Y1 - 2017/1/12

KW - E-Health, Arrhythmia

KW - Fuzzy C-Means clustering

KW - Body area network

KW - Mahalanobis-Taguchi System (MTS)

U2 - 10.1016/j.neucom.2016.08.042

DO - 10.1016/j.neucom.2016.08.042

M3 - Article

SN - 0925-2312

VL - 220

SP - 221

EP - 235

JO - Neurocomputing

JF - Neurocomputing

ER -